The Visuo-Spatial Sketchpad and Eye-Movements · Web viewincluded Mandarin characters, and participants were screened for prior knowledge of Chinese writing systems. The purpose of

Running head: EXAMINING EYE GAZE IN A DMTS TASK 1

Examining the Behavior of Remembering Utilizing Eye Movements in a

Delayed Match to Sample Task

Elisa Hegg

Simmons College

Author Note

Research conducted by Elisa Hegg, Simmons College, as part of the requirement for the

doctoral program in Behavior Analysis.

The co-authors and the members of the dissertation committee for this study were Dr.

Ron Allen, Department of Behavior Analysis, and Dr. Gretchen Dittrich, Department of

Behavior Analysis, Simmons College, and Dr. Dave Palmer, Department of Psychology, Smith

College.

Special thanks to Dr. Teresa Mitchell, and the Eunice Kennedy Shriver Center –

University of Massachusetts Medical School for her assistance with this study.

Correspondence regarding this study can be sent to: Elisa Hegg, Department of Behavior

Analysis, Simmons College, 300 The Fenway, Boston, MA 02115. Email:

[email protected]

Gretchen Allison Dittrich, 04/26/17,

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EXAMINING EYE GAZE IN A DMTS TASK 2

Table of Contents

Table of Contents………………………………………………………………………………….2

Abstract……………………………………………………………………………………………5

Introduction………………………………………………………………………………………..6

Cognitive Theories of Memory………………………………………………………………...7

The Visuo-spatial Sketchpad and Eye-Movements……………………………………………8

Behavior Analysis and Memory………………………………………………………………16

Empirical Work on Complex Human Behavior……………………………………………....22

Purpose………………………………………………………………………………………..24

Experiment 1 Method..…………………………………………………………………………..25

Subject Selection……………………………………………………………………………...25

Participants……………………………………………………………………………………26

Setting and Apparatus………………………………………………………………………...26

DMTS Task…………………………………………………………………………………...27

DMTS stimulus sets……………………………………………………………………...27

Stimulus set presentation………………………………………………………………...28

Eye tracking software……………………………………………………………………29

Dependent variables and measurement……………………………………………………….30

Accuracy of match……………………………………………………………………….30

Visual gaze definitions…………………………………………………………………..30

Procedures…………………………………………………………………………………….31

Interobserver Agreement……………………………………………………………………..32


Experiment 1 Results...…………………………………………………………………………..32

Accuracy……………………………………………………………………………………..32

Latency……………………………………………………………………………………….33

Observing Responses………………………………………………………………………...34

Delay……………………………………………………………………………………..34

Comparison………………………………………………………………………………36

Experiment 1 Discussion………..……………………………………………………………….39

Accuracy……………………………………………………………………………………..39

Latency……………………………………………………………………………………….40


Delay……………………………………………………………………………………..41

Comparison………………………………………………………………………………44

Experiment 2 Introduction………………………...……………………………………………..47

Experiment 2 Methods…...………………………………………………………………………48

Participants, Setting and Materials…………………………………………………………..48

DMTS Task…………………………………………………………………………………..48

Dependent Variable and Definitions…………………………………………………………49

Procedure…………………………………………………………………………………….49

Experiment 2 Results...…………………………………………………………………………..51

Accuracy……………………………………………………………………………………..51

Latency……………………………………………………………………………………….51


Delay……………………………………………………………………………………..52


Comparison………………………………………………………………………………54

Experiment 2 Discussion..……………………………………………………………………….55

Accuracy and Latency………………………………………………………………………..55


Delay……………………………………………………………………………………..56

Comparison………………………………………………………………………………57

General Discussion………………………………………………………………………………58

Utility of Eye Tracking in a DMTS Task……………………………………………………59

Utility of DMTS task…………………………………………………………………….59

Utility of eye gaze measures……………………………………………………………..61

Evaluation of Eye Gaze in the DMTS Task………………………………………………….63

Delay……………………………………………………………………………………..63

Comparison………………………………………………………………………………64

Behavioral Explanations……………………………………………………………………..64

Covert seeing…………………………………………………………………………….65

CMO-T…………………………………………………………………………………...65

Behavioral repetition……………………………………………………………………..66

Future Research………………………………………………………………...……………66

Limitations…………………………………………………………………………………...70

Conclusion…………………………………………………………………………………...72

References……………………………………………………………………………………74

Appendix A.………………………………………………………………………………….81

Appendix B…………………………………………………………………………………..91


Abstract

Measures of eye gaze fixations, including the number and duration, were examined during the

delay and comparison in a delayed match-to-sample task. In Experiment 1 participants responded

yes or no using a key press to indicate whether the comparison matched any of the one, two, or

four stimuli from the initial sample. Experiment 2 was developed as pilot study. Participants

responded using a key press to indicate which quadrant of the screen the comparison had been

presented in, moving from two- to four-stimulus initial samples. Across both Experiment 1 and

Experiment 2 the increase in number of stimuli resulted in an increase in complexity, indicated

by a decrease in accuracy across all participants. The average frequency, and total average

duration, of eye movements during the delay increased as the number of stimuli increased. Data

on observing responses from the time that the comparison was presented up to the participant’s

response were more variable. Together, these results extend the research on complex human

behavior by utilizing an objective measure to examine an otherwise largely covert behavior.

Keywords: visual memory, complex human behavior, eye tracking, covert behavior


Experiment 1


Pages?


Examining the Behavior of Remembering Utilizing Eye Movements in a Delayed Match to

Sample Task

What memory is, and how it works, has been a topic within the field of psychology since

the field’s inception, and prior to that it was a topic for philosophers. Our ability to analyze and

respond to things that are no longer present is so commonplace within the human experience that

this performance is taken for granted; yet our ability to understand how we do this remains open

to theory and research. Complicating our ability to view and understand memory objectively is

how deeply intermixed the languages of the layman and the scientist are in this area. Both

scientists studying memory, and average people discussing their own experience of memory,

invoke metaphors of storage and retrieval, often without any acknowledgement of the

metaphorical nature of their description. An alternative to a metaphorical understanding of

memory may be to consider remembering as a behavior rather than as a structure. This may

allow for the interpretation and understanding of this everyday phenomenon using only the

principles of behavior that have been uncovered through independent and rigorous

experimentation. While the realm of behavior analytic theory has put forward plausible accounts

of how complex behavior, such as memory, might develop through the application of the

principles of behavior (Donahoe & Palmer, 2004; Skinner, 1953; Skinner, 1974) little empirical

work exists to support these accounts. This gap in behavioral research on complex behavior

leaves the field open to the domain of cognitive psychology, and the continued reliance on

metaphor and explanatory variables that cannot be independently studied.

Cognitive Theories of Memory

An initial way of categorizing cognitive theories of memory is as single-store or dual-store

theories. In single-store models memory is viewed as unitary across time, from seconds to


nearly a lifetime, and is influenced by the association with items and their context (Howard &

Kahana, 2002). Dual-store models of memory, on the other hand, theorize a functional

distinction between long-term memory and short-term memory (Atkinson & Shiffrin, 1968).

Following processing in short-term or working memory, some information will enter into long-

term memory, where it may decay over time or it may persist indefinitely, and the size of the

storage capacity is perhaps unlimited. Long-term memories may further be categorized as being

implicit, such as the muscle memory necessary to execute a task, or explicit, such as our ability

to remember and describe events from our childhood (Atkinson & Shiffrin, 1968). Short-term

memory, on the other hand, is conceived as being a system that holds and actively works on

information for a brief span of time prior to it either entering into long-term memory store or

actively being emitted as some form of overt action, or both. Short-term memory lasts only a

matter of seconds, and can hold only a limited amount of information (Atkinson & Shiffrin,

1968). This “modal-model” has been thoroughly detailed by Shiffrin and colleagues in the

1960’s, and this conceptualization has influenced much of the memory theory and research that

has followed.

While the concept of short-term memory does not necessitate or imply active manipulation

for the storage or emission of information, working-memory is a theoretical framework that

describes structures and processes that actively engage with information for both short-term

retention, as well as allowing the use of information for reasoning, comprehension, and eventual

emission of overt behavior. Hitch and Baddeley (1976) provided the initial description for their

multi-component model of working memory (see Baddeley, 1986 for a thorough description of

the early work leading to the development of his influential working memory model).

The initial working memory framework hypothesized a central executive system that

monitors the activity of two slave systems, each responsible for working on a different type of


information: verbal and visual (Baddeley, 1986). Later, Baddeley added a third slave system: the

episodic buffer (Baddeley, 2000). Information that enters the system phonologically, either

through hearing or reading language, is worked on by the phonological loop, where information

may be covertly re-articulated as a rehearsal mechanism. The visuo-spatial sketchpad is the

slave system responsible for maintaining and manipulating visually presented information, and

may be further broken down into systems responsible for spatial information, and information on

the shape, color, or other dimensions and aspects of viewed objects or scenes (Baddeley, 1986).

The episodic buffer is responsible for integrating information from each slave system, as well as

maintaining chronological order (Baddeley, 2000). Much of the research on working-memory

has used verbal information to evaluate the utility of the concept of the phonological loop with

regards to maintaining information for immediate use. However, the concept of visual memory

has received more research in recent years.

The Visuo-Spatial Sketchpad and Eye-Movements

The hypothesized role of the visuo-spatial sketchpad is to retain and analyze information

about what we see. The metaphor of a sketchpad was utilized by Baddeley (1986) to suggest a

system that would function in much the same way that a pad of paper might be utilized by

someone trying to work out a geometric problem to temporarily hold and work on spatial

information. This initial system has since been functionally partitioned into object (i.e., the

appearance of individual objects and arrays) and spatial components (Della Sala, Gray,

Baddeley, Allamano, & Wilson, 1999; Logie, 1995), similar to observations that the functional

organization of working memory may mirror the what/where organization of the visual system

(Postle, Idzikowski, Della Sala, Logie, & Baddeley, 2006).

In a series of studies completed in the 1970’s, described briefly in his book on working

memory, Baddeley and colleagues examined the connection between visual working memory


omit


:


:


and the visual motor system (Baddeley, 1986). The initial studies were then gathered together

and reprinted, along with a more recent study, as a reflection of the impact that the initial line of

research has had on subsequent investigation on visual working memory (Postle et al., 2006).

Together, the experiments examined the importance of eye movements themselves on the

formation and maintenance of spatial information in working memory, the role of voluntary eye

movements on the same visual imagery task, and whether eye movements, or their control

processes, are involved both in the creation and processing of an imagined scene, or if the role of

eye movements is restricted to the processing of the imagined information. Using a task that had

been shown by Brooks (1967) to emphasize either spatial or verbal encoding of information in

working memory, the first two experiments evaluated the effect of voluntary and involuntary eye

movements on recall (Postle et al., 2006). The task presented a script of information to the

participant that either described a path of numbers from 1 to 8 through a 4 X 4 matrix, or

nonsense sentences. Successful recall of the spatial material was considered to be reliant on the

participant’s ability to visualize the spatial relationships, whereas the nonsense sentences are

difficult to visualize, and so were considered reliant on verbal working memory exclusively

(Postle et al., 2006). Neither task presented any visual stimuli as an antecedent. In the initial

experiment to test whether eye movements per se were important for recall of the spatial

information, nystagmus (involuntary movements of the eyes, usually from side to side) was

induced by spinning the participants after they were presented with the to-be remembered

information for 45s. Eye tracking equipment was used to measure the extent of the nystagmus as

a measure of the integrity of the independent variable. The results indicated memory

performance was not disrupted for either the visual or verbal information in either spin or no-

spin conditions (Postle et al., 2006).


Omit comma herePostle et al., 2006


In the second experiment described by Postle, et al. (2006), voluntary control of eye

movements was disrupted. Eye tracking equipment was again used to measure the integrity of

the independent variable, whether the participants controlled their eye movements as instructed.

During the delay interval participant’s voluntary use of eye movements was controlled by

requiring that they either track a moving object across a stationary visual field, track a moving

object across a moving visual field, or fix on a stationary object in front of a moving visual field.

A free eye-movement control condition was also included. The results demonstrated that recall

for spatial information was most accurate in the free eye-movement condition, slightly lower in

the fixed-eye condition, and markedly lower in the conditions where they were required to move

their eyes. Recall for the verbal information was not disrupted by any of the tasks. These results

were taken by the authors to suggest that while, eye movements per se do not play a role in

working memory for spatial information, the allocation of eye movements to another task

disrupted rehearsal for the spatial information (Postle et al., 2006).

Finally by Baddeley and colleagues (Postle et al., 2006) examined whether the voluntary

use of eye movements was important during the initial encoding of the material. They evaluated

whether; the participants needed to move their eyes along the path through the matrix as is it was

being described to demonstrate successful recall; free eye movements to scan the image already

entered into the working memory store; or both to optimize performance on the recall task. Using

the same task described in Experiment 2, the authors required control of voluntary eye

movements to either a fixed or moving location during presentation of the material, during recall,

and both during presentation and recall. Results indicated that free use of eye movements was

necessary during recall, and might be necessary during encoding. Recall performance was

disrupted to a slight, but significant, degree for both the spatial and verbal material when

voluntary eye-movements were restricted during presentation, indicating that perhaps the


The authors or Baddeley and colleagues (year)…


,


disruption in performance was due to interference with a joint system within the model, rather

than interfering with just the spatial working memory system (Postle et al., 2006).

These early studies provide some initial suggestive evidence that recall for material that is

considered based on visual or spatial material may rely to some extent on the use of, or control

of, eye movements. However, while the Brooks (1967) task is considered to be reliant on spatial

memory, it does not make use of visually presented materials. Also, the use of eye-tracking

technology was restricted to ensuring integrity of the independent variable, that is, whether the

participant’s eyes were moving in the manner intended, either as a result of the rotational

nystagmus, or voluntarily using the eyes to fixate or track the specified stimulus. Further, the

eye-tracking equipment from the 1970’s was described as being less sensitive than more modern

technology (Postle et al., 2006).

The final study described in Postle and colleagues (2006) was an extension of a previous

study by Postle, D’Esposito, and Corkin (2005). It utilized more sensitive eye tracking

equipment to ensure that participants were moving their eyes according to the experimental

instructions, while also measuring some aspects of the eye movements, including the number of

saccades (quick movements of both eyes between periods of fixation) and the distance travelled

by the eye during one of the distraction conditions (Postle et al., 2006). The task that the Postle

and colleagues (2006) utilized was also changed from the Brook’s (1967) task to a delayed

recognition task, with a spatial condition and a shape condition. The shapes that were utilized by

Postle and colleagues (2006) were initially developed by Attneave and Arnoult (1956), and then

expanded and modified by Postle and D’Esposito (1999), and had been demonstrated to have a

low likelihood of prior learning history (Vanderplas & Garvin, 1959). The delayed recognition

task was used in part because of the temporal separation between stimulus encoding periods and

response periods, allowing for disruption of the maintenance period in between. There were



and (ampersands should only be used parenthetically)


Which?


omit


three disruption conditions tested in both the spatial and the shape main conditions: a) saccadic

distraction, where participants were instructed to move their eyes in any manner they choose

during the delay; b) word-reading distraction, where the participant was instructed to read 12

words per distraction interval; and c) a no distraction control condition. The results of this study

found that when participants were required to move their eyes, using the eye muscles but

supposedly not involving other aspects of attention, recognition for spatial information was

disrupted, but not shape recognition (Postle et al,. 2006). When participants were required to read

words, on the other hand, recognition for shapes was disrupted, but not spatial recognition.

Taken together the authors (Postle et al., 2006) suggested that the results from the four

experiments provided empirical evidence for the theory Baddeley presented in his 1986 book

that, analogous to the importance of sub-vocal rehearsal to the phonological loop, visual

rehearsal may derive from the cognitive resources that support the control of eye movements.

Studies have provided evidence for the hypothesized role of eye movements as the

rehearsal mechanism for the visuo-spatial sketchpad (Bochynska & Laeng, 2015; Della Sala, et

al., 1999; Laeng, Bloem, S’Ascenzo, & Tommasi, 2014; Logie, 1995; Postle et al., 2005).

However, most have relied on a dual-task paradigm, where the concurrent task is assumed to be

selectively disruptive to visual versus verbal memory processes. Rather than using fixed item

presentation and a concurrent task to examine the role of eye movements, Tremblay, Saint-

Aubin, and Jalbert (2006) utilized a serial position task and measured eye movements and

performance data to provide a direct measure of rehearsal based on eye movements. In a

computerized task participants were presented with a sequence of seven dots. All seven dots

were then presented on the screen simultaneously. After a 10 s retention interval participants

were required to point to each dot in the order in which it was originally presented. Rehearsal

was measured as the number of different adjacent locations of dot pairs looked at in the correct



Omit comma


; and c) a no …


: a)


order. A pattern of recall emerged that the Tremblay and colleagues (2006) suggested was

similar to what was found in verbal recall studies. Rehearsed pairs from the beginning and end

of the series were recalled with greater accuracy than pairs presented in the middle of the series.

Furthermore, the results indicated that greater numbers of rehearsed pairs during the retention

interval led to better overall recall performance, and that specific rehearsed pairs had a far greater

probability of recall compared with non-rehearsed dot pairs. In a second experiment participants

were presented with the same recall task, but were prevented from moving their eyes during the

retention interval (Tremblay et al., 2006). When rehearsal in the form of eye movements was

prevented, a similar pattern of recall emerged compared with Experiment 1, in terms of primacy

and recency effects; however overall recall accuracy suffered. The authors concluded that overt

rehearsal in the form of eye movements did take place and may aid in the serial recall of spatial

information (Tremblay et al., 2006). However, the authors also noted that while rehearsal in the

form of overt eye movements did lead to better accuracy, overall accuracy was still high even on

trials where there were no rehearsed pairs and when the free use of eye movements was

prevented (Tremblay et al., 2006). For both experiments the to-be-remembered (TBR) stimuli

were kept on the screen during the retention interval (Tremblay et al., 2006). It is unclear what

role eye movements would have had if stimulus cues were not available during the interval.

In contrast to the potential role of overt eye movements as a rehearsal mechanism indicated

in research conducted by Tremblay and colleagues (2006), Godijn and Theeuwes (2012)

provided evidence that suggested that overt rehearsal did not assist in recall of serial information.

In a study by Godijn and Theeuwes (2012) participants were presented with the numbers one

through six in ascending order at various semi-random locations on a computer screen. The

experimental manipulations included requiring that the participants hold their eyes in a fixed

position in the middle of the screen, requiring that they allocate a prescribed number of seconds


did


suggeste



Research conducted by Tremblay and colleagues (2006)


to numbers at the beginning of the series, requiring that they allocate a prescribed number of

seconds to numbers at the end of the series, and finally, allowing for free eye movements during

the retention interval. The results indicated that when participants allocated attention to the

lower digits their recall for the location of those digits was improved. However, requiring that

saccades be allocate to the higher digits impeded recall for the location of all digits. Further,

there was no difference in recall between the free eye movement and fixed eye conditions.

Godijn and Theeuws (2012) note that during the free eye movement condition, participants were

more likely to allocate saccades to the lower digits, and these digits were the ones that were best

recalled. However, the authors stated that this does not mean that this is due to the superiority of

overt rehearsal over covert rehearsal. Rather they see a role for covert shifts of attention as the

mechanism for maintaining spatial information (Awh, Jonides & Reuter-Lorenz, 1998, Awh &

Jonides 2001), noting that it is plausible that even during fixed or restricted eye movement

conditions that covert attention is allocated to the low digits (Godijn & Theeuws, 2012). Godijn

and Theeuwes (2012) further noted that during the initial observation of the sample, participants

allocated more observing time to the lower digits, suggesting that the allocation of saccades to

these locations during the retention interval may be incidental to the attention being paid to those

locations. Eye movements, in this view, may follow the shifts in attention, but not be a

necessary part of the rehearsal, though hypothesis was not directly tested in this study (Godijn &

Theeuws, 2012).

Logie (1995) has suggested that rather than the eye movements per se being necessary for

spatial memory, it is the active system involved in the planning of movements, including eye

movements, which is responsible for rehearsal of visual information. This alternate theory is

based on demonstrations of disruption for visual information happening with different forms of

task-irrelevant movements, such as finger tapping (Farmer, Berman, & Fletcher, 1986), arm


specify


movements (Smyth & Scholey, 1994), as well as eye movements (Lawrence, Myerson, Oonk, &

Abrams, 2001). However, the task-irrelevant movements may have required spatial attention,

and that may have led to the disruptive effects rather than the planning per se (Logie, 1995).

Awh and colleagues (Awh, et al., 1998; Awh & Jonides, 2001) proposed that it was shifts

in spatial selective attention that was responsible for item maintenance in visual memory. Awh,

et al., (1998) conducted three experiments to evaluate their model of visuo-spatial working

memory that utilized shifts in selective attention as a mechanism to promote maintenance. Based

on prior evidence that given a choice task individuals demonstrated greater efficiency in

responding when spatial attention was already directed at the location where the choice stimuli

appear, Awh and colleagues (1998) presented participants with a dual task requiring both spatial

recall and a choice task. Unlike previous studies (Postle et al., 2006; Tremblay et al., 2006;

Godijn & Theeuws, 2012) the choice task that was required during the retention interval was not

intended to disrupt recall on the spatial task, but rather to see if reaction time was faster to the

choice task when the choice stimulus appeared in the same location as the TBR spatial

information. The results of the experiments indicated that reaction time was faster in the choice

task when the to be remembered (TBR) information was spatial, rather than related to item

identity, when participants were required to keep their eyes fixated during the entire trial (Awh et

al., 1998; Awh & Jonides, 2001). This data indicated that eye movements were not necessary for

item maintenance in visuo-spatial memory. The Awh and Jonides (2001) suggest that the eye

movement hypothesis may be reconciled with the spatial-attention hypothesis if one considers

that spatial-attention may be shifted to a location prior to eye movements being directed at that

location.

In summary, the previous research has provided data in support of a modal-model of

memory, with a dedicated visual working memory subsystem (Bochynska & Laeng, 2015; Della


omit


ed


specify


ed


was


Sala, et al., 1999; Laeng, Bloem, S’Ascenzo, & Tommasi, 2014; Logie, 1995; Postle et al., 2005;

Postle et al., 2006; Tremblay et al., 2006). In providing data to support a particular hypothesized

mechanism for item maintenance in visual memory, most of the studies utilized a dual-task

paradigm, where the hypothesized maintenance mechanism was disrupted by a secondary task

that should require the same cognitive resources (Postle et al., 2005; Postle et al., 2006). In most

of the studies, the use of eye-tracking equipment was limited to ensuring procedural integrity,

recording whether participants did or did not move their eyes in accord with the independent

variable (Postle et al., 2005; Postle et al, 2006). Furthermore, much of the aforementioned

research focused on recall for spatial information, rather than item identity. The exception to this

was the work conducted by Postle and colleagues (2005; 2006)

The purpose of the experiments Postle and colleagues (2005; 2006) was in part to compare

spatial recall with recall for a nonsense shape. They found that saccadic eye movements

disrupted performance on the location task, but not for non-spatial information (Postle et al.,

2005; Postle et al., 2006). Further, in reviewing the literature, only one study was found that

tracked eye movements as a dependent variable during a serial recall task (i.e., Tremblay et al.,

1996). In this study, however, the stimulus array was visible for the entire trial. Godijn and

Theeuwes (2012) did measure eye movements during the observation and retention intervals

during a spatial memory task. Their results indicated that overt use of eye movements did not

contribute to recall for the spatial location of presented digits. However, this research evaluated

material presented in a serial order and recall for spatial information (Godijn & Theeuws, 2012).

The stimuli Godijn and Theeuws (2012) used were the digits one through six, which may have

allowed the participant to use the repetition of the numbers as part of their recall strategy. In

reviewing the available literature no studies were found that assessed the role of eye movements

in the recall for visually presented items, rather than spatial information.


focused onor evaluated


and



i.e., Tremblay et al., 1996


Specify or rephrase


Behavior analysis and memory

All of the visual memory theories discussed previously in the manuscript have started from

an initial theoretical position that presumes cognitive structures involved in the temporary

maintenance and manipulation of information (Baddeley, 1986; Baddeley & Logie, 1999).

Behavior analysis, on the other hand, seeks to account for the current performance of a behavior

as a function of environmental variables. This poses a problem when it comes to responses that

are traditionally thought of as memory processes, as the environmental stimuli are no longer

present to allow for a simple environmental explanation. For example when asked, “what are you

eating?” while having breakfast the response of “corn flakes” can be accounted for by the

presence of the bowl of corn flakes. When asked later on in the day “what did you eat for

breakfast?” the same response of “corn flakes” requires a different explanation. The corn flakes

are no longer present to act as a discriminative stimulus evoking the tact in the presence of the

question. And the question alone cannot account for the response as the answer may vary day-

to-day depending on what was eaten. That individuals are able to respond about past events is

evident, however an analysis that relies exclusively on observable variables appears to be

insufficient to describe and predict such everyday performances. The difficulty that the field of

behavior analysis has in accounting for such responses allows ample room for cognitively based

philosophical and psychological explanations to step in, and for metaphorical language to take on

the role of scientific explanation.

One difficulty in developing a behavior analytic account of memory is that the level of

control available in the laboratory is not easily achievable for covert activities, thus requiring a

degree of inference in the explanation. Palmer and Donahoe have extensively discussed the role

of interpretation in the science of behavior (Donahoe & Palmer, 2004; Palmer, 1991; Palmer &

Donahoe, 1992). According to Palmer and Donahoe, all sciences have a degree of interpretation,


according to Palmer and Donahoe, all


Previously in this manuscript


where phenomena that are not directly observable are explained by principles that have been

demonstrated in analogous conditions. A behavior analytic account of complex human behavior,

including memory, is necessarily going to be interpretive for several reasons. For one, the

precise levels of control necessary for empirical research may be difficult to achieve. Further, the

units of behavior are likely to be less discrete. And finally, all parts of the stimulus-response-

stimulus chain may not be independently observable. As in other scientific interpretive

explanations, the description and explanation for the phenomenon of memory should be

constrained by the principles that have been the subject of rigorous experimental study.

Introducing explanatory variables that have not been the subject of independent and objective

observation and manipulation moves the explanation from interpretive to speculative (Donahoe

& Palmer, 2004).

One of the central tenets of behaviorism as a philosophy is that a science of behavior is

possible, and further that it is a natural science (Skinner, 1953; Watson, 1913). As a natural

science the implication is that behaviors are events that are explained by other natural events, and

that the explanations will be sufficient to explain all important phenomena (Baum, 2005). Two

important branches of behaviorist thinking are methodological behaviorism and radical

behaviorism. A primary distinguishing feature between these two views is what is included as

important phenomena in need of an explanation. Methodological behaviorists consider only

observable stimuli and responses within their analysis of behavior (Baum, 2001). Internal, or

cognitive, events are either denied as existing (Watson, 1920), or they are considered to be

unimportant as a subject matter (see Baum, 2011 for a recent example). While this approach to

behaviorism has strength in its rigorous adherence to empiricism, its denial of the existence or

importance of internal events rings as false to the ear of the majority of people who would claim


to feel, think, dream, and remember. This leaves those people looking to other disciplines to

answer the questions of how and why these experiences occur.

Radical behaviorism, on the other hand, is often defined by its consideration of what are

termed private events. Private events are the covert stimuli and responses that make up what we

would otherwise describe as our conscious experiences (Day, 1971, in Leigland, 1992).

Advocates of radical behaviorism are careful to distinguish between private events and mental

events. Mental events, such as the account of visual working memory processes described

previously, are events and structures that take place in an inner space and have no necessary

relation to independently verifiable variables found in nature. Mental events are taken as

explanations for the overt events that make up the datum of both cognitive and behavioral

scientists. Private events, in contrast, are not necessary to explain behavior, but rather are

themselves stimuli and behaviors that are subject to the same explanatory variables as overt

stimuli and behaviors (Skinner, 1953).

In Science and Human Behavior (1953) Skinner presented one of the earliest formulations

of a behavior analytic approach to what he termed private events. Rather than viewing the

environment within one’s skin as being different than the environment outside the skin, Skinner

stated that “a private event may be distinguished by its limited accessibility but not, so far as we

know, by any special nature or structure (Skinner, 1953, p. 257). Thus the data that we have

access to by considering our own covert experience is not necessarily wrong, but rather it lacks

independent verifiability. The assumption made by the radical behaviorist is, however, that if we

could independently collect data on private or covert events we would see that these events

respond to behavior principles of respondent and operant conditioning in the same way as the

behaviors that we can independently observe and record (Skinner, 1953).


ed


In Skinner’s consideration of perception, he begins by presuming that seeing is a behavior.

And like verbal behavior, the behavior of seeing can be emitted to such a slight degree as to be

undetectable to an outside observer. In the case of verbal behavior we would describe this as

engaging in covert speech or thinking, in the case of perceptual behaviors, such as seeing, we

engage in remembering, imagining, and visualizing (Skinner, 1976). Thus when we “call an

image to mind” we are responding by seeing in the absence of the thing seen because of other

stimuli in the environment that have stimulus control over that response (Skinner, 1976).

Skinner provided two ways that this response might be conditioned using the behavioral

principles that underlie respondent and operant conditioning.

Skinner described respondent seeing as being instances in which we see something that is

not truly there because in the past that stimulus was present at the same time as a stimulus that

we are currently being exposed to (Skinner, 1953). He provides the example of the dinner bell

making us “see” food, as well as salivating. Understanding salivation as a behavior in the

respondent paradigm is well established. Skinner (1953) suggested that we can replace “seeing

food” for salivating in much the same way. Thus, when we are exposed to the smell of freshly

baked cookies, we may engage is several responses that were initially conditioned with this

smell, including seeing, or remembering, a kitchen from our childhood. Because several

responses may be elicited in a cascade of covert perceptual behavior, we might experience the

memory as a reminiscence giving us the feeling that we are reliving our previous experiences

(Donahoe & Palmer, 2004).

Seeing in the absence of the thing itself may also be conditioned by consequences as an

operant. If seeing a stimulus is reinforcing based on its previous conditioning history, then we

may arrange opportunities to be in the presence of that stimulus, or representations of it

(Donahoe & Palmer, 2004). Gazing at the tranquil blue waters off a Caribbean beach may be





reinforcing for an individual. In order to contact that reinforcer, they might take a vacation that

will allow them to relax on the beach and gaze at the ocean. Or they might buy a travel

magazine or watch travel shows that feature scenes of blue lagoon and white sandy beaches. Or

they might picture the scene to themselves, evoking remembered sights from the previously

viewed stimuli. Skinner points out that in this type of conditioned seeing, as opposed to the

seeing that has been developed through respondent conditioning, the behavior is controlled by

deprivation and reinforcement (Skinner, 1953). Thus, the longer it has been since a beach

vacation, the more likely it becomes that an individual will engage in behaviors that bring them

into overt or covert contact with the stimuli.

Further in his chapter on the nature of private of events in a natural science Skinner (1953),

described how covert seeing might contact reinforcers beyond the automatic reinforcement of

being in contact with reinforcing stimuli, for example in solving a problem. He provided the

following example:

“Think of a cube, all six surfaces of which are painted red. Divide the cube into twenty-seven equal cubes by making two horizontal cuts and two sets of two vertical cuts each. How many of the resulting cubes will have three faces painted red, how many two, how many one and how many none?” (Skinner, 1953, p 273)

This problem could possibly be worked out through an extensive verbal chain describing

the nature of a cube and its surfaces, but as Skinner (1953) pointed out, it is easier to solve

visually. He further suggested that it can be solved visually without having access to the visual

stimulus by generating a covert image that can be “seen” and manipulated. The degree to which

any given individual is able to use this problem solving technique is likely to be based on their

individual reinforcement history with regards to the stimuli, their reinforcement history with

regards to covert seeing, and the resulting skill at describing the resulting stimulation (Skinner,

1953).




Omit – only use page numbers when you are quoting content


Following a radical behavioristic approach to the nature of private events and conditioned

perception, an initial step in attempting an experimental analysis of private events, such as

memory, would be to reframe it as an action rather than a structure. As a behavior, remembering

is likely to be a chain of behaviors leading to a terminal response rather than a single discrete

response (Palmer, 2010). While analyzing every step in the chain may never be possible,

determining relations between behaviors within the chain may further the goal of interpreting

complex human behavior from a behavior analytic perspective. The boundary between what is

private and what is public shifts depending on the technologies available to the observer. For

example, a heartbeat is a private event until the observer uses a stethoscope. Similarly, the

behaviors involved in private events may occur to such a small degree that they are not detectible

to an observer without the use of specialized equipment. The experience of visual memory

would be inferred to involve the same or similar behaviors to what we would observe when

someone is seeing a stimulus that is currently present, but perhaps to a much smaller degree.

These behaviors might include movement of the eyes, perhaps following a similar pattern to the

initial observation of the stimulus. Through the use of eye tracking apparatuses, the behaviors

that happen at a smaller level during the experience of conditioned seeing may become

detectable, allowing for some data to supplement the role of interpretation (Palmer, 2010).

Empirical work on complex human behavior

Complex behavior is often the end result of a chain of very small behavioral events, the

scale of which is so small that it is difficult to bring to bear the experimental methods that

underpin our experimental and applied understanding of behavior (Palmer, 2010). As a result,

behavior analytic research on these areas remains limited, with much of the research that has

been done in the area of language. Experimental procedures often draw from similar areas in

cognitive research, such as the use of priming procedures and electroencephalogram (EEG)


For example, a


readings in language (Barnes-Holmes et al., 2004; Haimson, Wilkinson, Rosenquist, Oimet, &

McIlvane, 2009; Hayes & Bissett, 1998).

In cognitive research the use of response latency has been used to measure the strength of

relationships between words, based on features such as semantic linkages, associational,

meditational and others (Barnes-Holmes et al., 2004). In priming procedures, a word is briefly

presented, followed by a second word. The latency to respond to the second word, for instance

by indicating that it is a word or non-word, is on average shorter when the words are related

(Barnes-Holmes et al., 2004). Response latency is a measure of behavior that has been used to

measure non-behavioral structural accounts of complex human behavior; however, as a measure

it has also been used to evaluate behavior-based accounts of language, such as stimulus

equivalence (Hayes & Bisset, 1998). For example, Hayes and Bisset (1998) used the priming

paradigm to measure responding to word pairs based on pairings derived through stimulus

equivalence. Their results indicated that responding was significantly faster for word pairs

generated through equivalent relations than unrelated word pairs (Hayes & Bisset, 1998). The

use of priming procedures has then been further refined with the use of electroencephalograms

(EEGs) readings measuring the event-related potential (ERP) between the presentation of the

stimulus and electrical activity within the brain (Barnes-Holmes, et al., 2005; Haimson, et al.,

2009). The use of ERPs is considered to possibly be more sensitive than overt responding as a

measure, as it occurs prior to the yes/no judgment, and can allow for measurement of the

emergent relations prior to testing, preventing the problem of learning through testing (Barnes-

Holmes, et al., 2005; Haimson, et al., 2009).

The priming studies previously described utilized the technology of cognitive psychology

in order to examine behavior principles. The eye tracking technology that has been utilized in

visual memory research has also been used to provide a behavioral measure of the primarily




covert complex human activity of attention. Dube, Balsamo, Fowler, Dickson, Lombard, and

Gerson (2006) used eye tracking equipment to measure the relation between eye movements and

duration of gaze and accuracy in a delayed matching-to-sample (DMTS) procedure. Participants

were exposed to 2-sample and 4-sample DMTS tasks. All participants had high accuracy scores

for the 2-sample trials. However, when the task became more difficult with the 4-sample

stimulus set, accuracy scores fell for two of the four participants. The data from the eye tracking

equipment indicated that subjects with both high and low accuracy made similar numbers of

observations to the sample stimuli; however, the duration of the observations for those with

higher accuracy scores was longer (Dube et al., 2006). Observation is necessary for stimulus

control to occur (Dinsmoor, 1985); the results of this study indicated that the duration of

observation may be an important variable in establishing accurate performance (Dube et al.,

2006): accuracy for the low-accuracy participants was improved through prompts to engage in

longer duration observations to each stimulus in the sample.

Purpose

Behavior analytic theory has ventured into the realm of complex human behavior, such as

memory and remembering; however, there is little empirical evidence to lend support to these

theories. The topic of visual memory has received attention in the field of cognitive psychology;

however, the methods utilized often include confounding verbal information (see Godijn &

Threeuw, 2012; Postle et al., 2005; Postle et al., 2006), or rely on spatial recall rather than item

recall (Tremblay et al., 2006). Within the field of cognitive psychology the dominant theory of

working memory for visual material incorporates the covert use of a visuo-spatial sketchpad as a

rehearsal and processing mechanism for visually presented stimuli (Baddeley, 1986). While the

field of behavior analysis includes only independently and empirically demonstrated principles

into accounts of behavior, excluding storage accounts and mental sketchpads, we may have




: accuracy…


; the results…


explanatory variables that can account for the experience of human memory. By considering

Skinner’s accounts of conditioned perception and covert seeing (Skinner, 1953; Skinner 1974) it

can be hypothesized that the behaviors that occur when the item is first seen are conditioned to

the stimuli present, and that under similar stimulus conditions the same behavior may occur at a

much smaller, or covert, level. Thus, when we are asked to respond to previously viewed stimuli

we may engage in some of the same seeing behaviors that we engaged in when we first viewed

the stimuli. One aspect of seeing that may occur as part of covert seeing may include moving

one’s eyes in a pattern similar to what would be expected if the stimuli were present.

The purpose of the current study was to utilize eye tracking equipment to measure the

relation between the number and duration of eye gaze fixations to the locations of previously

viewed visual stimuli in a delayed match-to-sample task. In order to control for the potential

confound of covert echoic rehearsal contributing to performance on the DMTS task, stimuli

included Mandarin characters, and participants were screened for prior knowledge of Chinese

writing systems. The purpose of Experiment 1 was to evaluate the role of eye gaze in an item

identification task. Experiment 2 was designed as a pilot study to begin to explore the role of eye

movements in a task that required a response based on location.

Experiment 1: Method

In Experiment 1 participants were presented with a DMTS task that began with an initial

sample containing one, two or four stimuli located in the four corners of the screen. Eye tracking

data were gathered during the initial sample observation, and during the 5 sec delay interval up

to and including the response to the comparison. Participants then responded to the comparison

with a ‘Yes’ or ‘No’ key press to indicate whether the comparison matched one of the initial

sample stimuli. Utilizing similar methodology to Dube, et al., 2006 the relations between the

number and duration of eye-gaze fixations and correct responding on the DMTS task were


this paragraph should appear in the method section, rather than the purpose statement.


italicize


examined. In addition the probability that the last location viewed prior to a correct ‘Yes’

response matching the location of the initial sample was calculated.

Subject Selection

Participants were recruited from a medical school campus. Flyers were posted around the

campus with a brief description of what potential participants would have to do, the requirements

of participating, and the experimenter’s contact information. Participants had to be 18 years or

older and have their own transportation to the study site. Potential participants were informed

that they would be receiving monetary compensation in the amount of $25 upon completion of

the study. Potential participants contacted the experimenter, who provided materials about the

study, including a consent form, as well as a description of the equipment to be used. Potential

participants were informed that they would be able to end experimental sessions at any time and

that they could withdraw from the study at any time without any detrimental effect towards the

participant. Exclusion criteria included self-reported prior knowledge of, or ability to read,

Mandarin characters.

Participants

Participants were four adults (3 males and 1 female), who were enrolled in their first year

of medical school. All were aged 22-25 years old. None of the participants had any known

clinical conditions, and all had vision that was considered adequate to drive, with or without

corrective lenses.

Prior to taking part in the study, participants read and signed a consent form that described

the eye tracking apparatus as “used to measure certain characteristics of your eye (e.g. pupil size)

during computerized learning tasks.” (this was based odd the methods used by Schroeder &


This was based off of the methods used by…


,


omit


Extra indentation


Holland, 1968). This deception was included to preserve the natural eye movements that the

individual would typically make during this type of task.

Setting and apparatus

Experimental sessions were conducted in a designated research room in a medical school

campus building. The participant was seated on an adjustable office chair in front of a chin rest.

The chin rest could be raised or lowered by the participant so that it was comfortable for them for

the duration of the session, though they were not required to use the chin rest past calibration of

the equipment. A standard keyboard was placed on the table in front of the participant to record

their responses. The keyboard was marked with four circular stickers to indicate the response

keys, though only two response keys were utilized in Experiment 1. The ‘yes’ response key had a

green sticker placed over top of it and replaced the ‘Z’ key on the standard computer keyboard.

The ‘no’ response key had a red sticker placed over top of it and replaced the ‘/’ key on the

standard keyboard. The spacebar was the only other active key after the initial instruction

screen. A color monitor was used to present sample and comparison stimuli.

On a separate table, located perpendicular to the participant table, were seats for the

experimenter along with two computer monitors and two keyboards. One of the experimenter

computers was used to calibrate the ISCAN © system; following calibration the experimenter

could monitor the eye tracking apparatus, seeing the current point-of-regard for the participant on

this computer. The second experimenter computer was used to start up and follow the stimulus

presentation being viewed by the participant. Neither of the experimenter monitors were visible

to the participant.

The eye-tracking apparatus was an ISCAN © Point-of-Regard system. The ISCAN ©

system shone a laser beam into the participant’s eye and the refraction angle between a point of

light on the participant’s pupil, and the point of light on the participant’s lens was measured to






calculate the point-of-regard. A real-time image of what the participant was looking at was

available on the experimenter’s computer, with a cursor to show the precise location of the

participant’s eye gaze. The beam of light was harmless to the eye, and did not disrupt regular

vision.


DMTS stimulus sets. The stimuli used in the DMTS task were black characters from the

Mandarin alphabet created using Microsoft Word 2007 ®. All characters were in 72pt font, and

presented on a white background. The stimulus set for each trial was drawn at random from a

pool of 210 different characters, without replacement. When all characters had been exhausted

from the pool, and then stimuli were re-drawn from the pool, at random, with the restriction that

correct comparisons from previous trials were not reused.

The stimulus array was initially created using Microsoft PowerPoint ® (2007). Sample

stimulus presentation slides were created containing one-, two-, or four-stimuli per slide, as a

way of increasing the complexity of the DMTS task. Sessions consisted of eight one-stimulus

trials, followed by a block of 24 two-stimulus trials, and a block of 24 four-stimulus trials.

Stimuli were located in the corners of the screen, with the number of corners occupied varying

depending on the number of stimuli presented. The specific corner for each stimulus was semi-

randomly determined using a random number generator, with the criteria that stimuli had to

appear in each location an equal number of times.

Trials were designated as either matched or unmatched using a random number

generator, with a criterion that there were an equal number of each trial type. For the one-

stimulus trials either the same stimulus that was presented as a sample was presented as a

comparison (i.e., matched), or a randomly selected stimulus from the pool was presented (i.e.,

unmatched). For the matched two- and four-stimulus trials one of the stimuli from the initial


criterion


criteria


sample was semi-randomly selected, with the criterion that the match was initially presented in

each of the four screen locations an equal number of times. Unmatched comparisons were

selected in the same manner as one-stimulus trials. The comparison stimulus was presented in

the middle of the screen, equidistant from the top and bottom, and right and left sides.

Stimulus set presentation. The PowerPoint® stimulus presentation slides were converted

into bitmap (BMP) images and entered into Presentation™ software. The Presentation™

software was used to present each slide as a JPEG image according to programmed timing rules.

This software collected data on the latency to respond from the presentation of the comparison

stimulus, as well as accuracy information on whether the response was correct or incorrect as

defined for each trial. Stimulus randomization took place prior to entry into the Presentation™

software, and the order of trials remained fixed for all participants.

Trials were programmed so that each trial started with the initial sample, which remained

on the screen until the participant pressed the spacebar on the computer keyboard. Following the

initial sample presentation the participant viewed a blank white screen for the 5 s delay interval.

Following the delay, the comparison stimulus was presented and remained on the screen until the

participant responded by pressing either of the two response keys. There was a 5 s intertrial

interval between each trial, during which the participant again viewed a blank screen.

Eye tracking software. The eye tracking PRZ™ software collected information on all

locations on the computer screen that the participant viewed during the experiment. Prior to the

experiment, specific areas of the screen were designated as regions of interest (ROI) using the

PRZ software such that data on the number and duration of fixations within these ROI could be

gathered. The initial step in this process was to take the already converted BMP images and

register them using the PRZ software, which converted the image to an IGR file. Once images


criterion


were saved as registered files, they were then overlaid with the ROI and saved as element (EMT)

files.

A grid with five ROI were used for each slide viewed by the participant during a trial,

including the blank delay screen. The grid had a box for each corner and one box was also placed

in the middle of the screen. In order to register the images with the ROI each registered image

(IGR) file was brought up in the PRZ software, the grid was visible around each stimulus that

was presented on the screen, as well as the remaining locations where stimuli were not currently

located. This screen with the ROI were then saved as an element EMT file.

Dependent variables and measurement

Accuracy of match. Data were collected on the accuracy of the participant’s responses

during the DMTS task. A correct response included instances of the participant pressing the

‘yes’ key on the keyboard when the comparison stimulus matched any one of the initial stimuli

presented in the sample presentation, or pressing the ‘no’ key if the comparison stimulus did not

match any of the initial stimuli. An incorrect response included instances of the participant

responding by pressing ‘yes’ on trials where the comparison did not match any of the initial

sample stimuli, as well as instances of the participant responding by pressing the ‘no’ key when

the comparison stimulus did match one of the initial samples.

Visual gaze definitions. The PRZ software collected data on the number, duration and,

pattern of eye gaze fixations directed at the ROI specified in the element entry grid. A fixation,

or observation, was defined as any instance of the point-of-regard cursor remaining within a

region of interest for at least 100 ms. This definition of fixation was programmed into the PRZ

software, which collected and organized the data. Data on fixations were considered for the

initial sample screen, the delay interval, and for the comparison screen separately. Data on

visual gaze were not collected during the intertrial interval.


The number of fixations within one of the ROI was defined as the frequency of observing

responses lasting at least 100 ms within the previously registered element boxes. The number of

observations were recorded during the initial sample viewing, during the delay interval and

during the time the comparison is on the screen, up to the participant’s response.

The duration of fixations were recorded for each of the ROI. Duration was recorded for

fixations lasting at least 100 ms, and ended when the point-of-regard cursor left the region of

interest for at least 100 ms. Duration was aggregated for the total duration that each region was

fixated on during the initial sample presentation, during the delay, and while the comparison was

presented up to the participant’s response.

Procedures

Participants first read and signed a consent form that described the apparatus as “used to

measure certain characteristics of your eyes (e.g. pupil size) during computerized learning trials”

(after Schroeder & Holland, 1968). Any further questions about the apparatus were deferred

until a debriefing following the end of participation in the study.

On entering the eye tracking room, participants took a seat in front of the chin rest to

prepare for calibration. Each session began with a brief calibration routine in which participants

were asked to keep their head still and on the chin rest, and to fixate on targets that appeared in

various locations on the stimulus display monitor. The target stimuli were unrelated to stimuli

used in the experimental procedures. Following calibration, participants were told that they no

longer needed to hold their head still. They were then presented with an instruction screen that

read:

“In this experiment characters will appear on the screen. After you have finished viewing

all of the characters press the spacebar. When you press the spacebar the characters will

disappear. After a few seconds a single character will appear in the middle of the screen.


Your task is to decide whether you saw this character on the prior screen. Press the GREEN

button if the second shape matches any of the characters from the previous screen. Press

the RED button if it does not match any of the previous characters. It is most important to

be accurate, but try to work as fast as you can. Press any key to start.”

Participants were asked to read the instructions aloud, and the session started when the subject

pressed any key on the keyboard. After pressing one of the keys, the participant began with the

one-stimulus trials. One-stimulus sessions consisted of eight delayed match to sample trials.

Immediately following the one-stimulus trials were 24 two-stimulus trials, followed by 24

four-stimulus trials. The participant was presented with the initial sample screen which they

could view for as long as they wanted. Pressing the spacebar removed the initial stimulus and

initiated the delay interval which presented a blank white screen for 5 s. Following the delay, the

comparison stimulus appeared on the screen and remained until the participant responded by

pressing either ‘yes’ or ‘no’. After one of these two keys had been pressed the, screen again

went blank for a 5 s intertrial interval. The next trial then automatically began. Participants did

not receive feedback on whether their response was correct or incorrect.

Interobserver agreement

The Presentation software collected data on the accuracy of responses. The PRZ software

collected data on the number and duration of fixations. Because all data were collected by a

computer interobserver, agreement was not calculated.

Results

Accuracy

Overall accuracy on the DMTS task is displayed as a percentage of correct responses over

total responses in the first row of Tables 1, 2, and 3, which show the data for one-, two-, and

four-stimulus trials, respectively. Each column displays the data for one participant. All


This looks like it is indented tooLabel = “Results”


participants demonstrated a high level of accuracy on the one-stimulus trials, with only

Participant 1 making one error. Overall there was a decrease in accuracy as the task became

more complex. The exceptions were Participant 4 who didn’t make any errors on either one- or

two-stimulus trials, and Participant 2 who had the same overall score of 79.2% accuracy on both

two- and four-stimulus trials.

The second and third rows on Tables 1, 2, and 3 display each participant’s accuracy on

matched and unmatched trials. On the one stimulus trials the, single error made by Participant 1

was on an unmatched trial. On two- and four-stimulus trials, three of the four participants had

better accuracy scores on the unmatched compared with the matched trials. The exception to this

was Participant 4, who had better accuracy on matched than unmatched four-stimulus trials.

Latency

The average latency to respond for each participant is shown in Table 4. Major columns

show the data for each participant, with sub-columns showing data for one-, two-, and four-

stimulus trials. The top row presents the overall latency at each level of complexity, and data on

correct and incorrect as well as matched and unmatched trials follow. The latency to respond to

the comparison increased as the complexity of the task increased for three of the four

participants. The exception is Participant 3, who had a shorter overall latency on the two-

stimulus trials compared with one- and four-stimulus trials. There was minimal difference in

overall latency between one- and four-stimulus trials for this participant.

The data for Participant 1, 2, and 3 indicate that there was a longer latency to respond on

incorrect trials compared with correct trials across all trial types, with the exception of one-

stimulus trials for Participant 1. It should be noted that data presented represents only a single

trial. Participant 4, who only responded incorrectly on four-stimulus trials, had a longer latency

to respond on correct trials compared with incorrect trials.


Both across and within participants there was variability on whether a longer or shorter

latency to respond was associated with matched or unmatched trials. Participant 1 had a shorter

average latency to respond on matched trials compared with unmatched on all trial types.

Participant 2 and Participant 3, on the other hand, had a shorter average latency to respond to

unmatched trials across all trial types. Participant 4 showed greater variability in the correlation

between trial type and latency to respond. Participant 4 had a shorter average latency to respond

to unmatched one-stimulus trials, and matched two- stimulus trials. Participants 2, 3, and 4 had

very similar latencies to respond to the comparison on matched and unmatched four-stimulus

trials.

Observing responses

Delay. Data on the average number and duration of fixations made during the delay are

presented in Tables 1, 2, and 3, as well as on Table 5. Tables 1, 2, and 3 display the average

number of observations, or fixations, made to areas of the screen that did and did not display

stimuli during the initial sample presentation, on one-, two-, and four-stimulus trials,

respectively. On one-stimulus trials, all of the participants had a higher average number of

fixations and a longer average duration of observations to locations that contained a sample

during the initial display compared with previously empty locations. The same pattern was

repeated on two-stimulus trials, with all participants having a higher average number of fixations

and longer average duration to the ROI where a stimulus had been presented. On four-stimulus

trials, all ROI displayed stimuli during the sample presentation. For all participants, this

condition had the highest average number of fixations and longest average duration of fixations.

Table 5 shows the average number of observations to ROI that displayed stimuli during the

sample presentation, with average duration shown in brackets. Each panel represents the data for

one participant, with the columns displaying the data per trial type, and the row displaying data


for trials that were ultimately correct or incorrect. The (*) symbol is used to indicate when there

was only one trial of a given type. Across participants there is variability in whether a greater

number of fixations was associated with trials that were ultimately correct or incorrect across the

matched and unmatched trials at each level of complexity. Participant 1 had a higher average

number, and longer average duration, of fixations during the delay on trials that were ultimately

correct on one- and two-stimulus trials, though it should be noted that there was only one

incorrect one-stimulus trial. On four-stimulus trials, the average number and average duration of

observations made during the delay were comparable for matched trials that were ultimately

correct and incorrect. On unmatched four-stimulus trials, the trials that were ultimately correct

were correlated with a higher average number and longer average duration of fixations compared

with the trials that were ultimately incorrect. Participant 2 did not have any incorrect responses

on one-stimulus trials. On two- and four-stimulus trials, there is variability on whether having a

higher average number of fixations was correlated with trials that were ultimately correct. On

unmatched two-stimulus trials, there was a slightly higher average frequency of observations

during the delay for correct trials, and on four-stimulus trials there was a higher average number

of observations made on correct matched trials. However, the highest average number and

longest average duration of observations occurred on unmatched trials that were ultimately

incorrect. Both Participant 3 and Participant 4 made very few errors across all levels of

complexity, and each of them had the highest average number and longest average duration of

fixations during the delay. For Participant 3, there was only one error on a matched two-stimulus

trial, and one error each for matched and unmatched four-stimulus trials. The highest number of

fixations to ROI during the delay occurred on an unmatched trial that was ultimately incorrect. In

all other instances, there was a higher number of observations made during the delay on trials

that were ultimately correct. Participant 4 made no errors on one- and two-stimulus trials, and no



errors on matched four-stimulus trial. The errors that were made on four-stimulus trials were on

unmatched trials, and while there was a higher average number of observations on the incorrect

unmatched trials compared with correct unmatched trials, the highest average number of

observations made by this participant occurred on matched trials that were ultimately correct.

Comparison. In addition to displaying accuracy and observation data collected during the

delay, Tables 1, 2, and 3 also present the mean frequency and duration of observations made

while the comparison screen was displayed, up to the participant’s response. Data on

observations made to ROI that did and did not initially display a sample, as appropriate, are

shown in the bottom rows below the similar data collected during the delay. Table 1 presents the

data for one-stimulus trials. At this level of complexity all participants had the same, or higher,

average number of fixations to regions that did not display a stimulus during the initial sample.

Participant 1, who had the same average number of fixations to areas that did and did not contain

a sample, had a longer average duration of observations to the locations that did display the

initial sample. For the other three participants, the average duration of observations was also

shorter to locations that displayed the initial sample.

Table 2 shows the data for the two-stimulus trials. Participant 1 made no observations to

the ROI where stimuli were initially presented during the comparison. Participant 2 and 4 both

made a higher average number of fixations, and had a longer average duration of fixations, to

screen locations where stimuli had been presented compared with locations that had been blank.

Participant 3, on the other hand, had only a slightly higher average number and duration of

observations to previously occupied regions compared with unoccupied. Table 3 shows the data

for the four-stimulus trials. As previously mentioned, this Table does not allow comparison

between locations that did and did not present stimuli as all four ROIed held a stimulus on the


sample screen. Across all four participants, the highest average number of observations and

longest average durations occurred during the four-stimulus trials.

Similar to Table 5, Table 6 presents the data on observations made during the comparison

as a function of whether the trial was matched or unmatched and correct or incorrect. Each

participant’s data is presented in a separate panel. The columns present the level of complexity,

with sub-columns for matched and unmatched trials. The top row in each panel present data on

correct trials, and the bottom row incorrect trials. The average number of fixations is presented

with the average duration presented in brackets. The (*) symbol is used to indicate when there is

only one trial of a given type. The data for Participant 1 is shown in the top panel. On one

stimulus trials the, only fixations made back to initial sample locations occurred on correct

matched trials. There were no incorrect matched trials, and no observations made back to

occupied ROI on either correct or incorrect unmatched trials. On two-stimulus trials Participant 1

made no observations back to ROI that had initially displayed stimuli. During four-stimulus

trials, Participant 1 had the higher average number of observations on matched correct trials,

compared with unmatched. However, the overall highest average number of observations was

made on incorrect unmatched trials. No observations were made during the comparison on

incorrect matched trials. The data for Participant 2 is shown in the second panel. On one-

stimulus trials, there were no incorrect trials. On matched trials, Participant 2 made no

observations back to locations were stimuli were previously displayed, compared with an

average number of 0.333 observations on correct unmatched trials. On two- and four-stimulus

trials, Participant 2 had fixations back to ROI where stimuli had been presented on all trial types.

On two-stimulus trials, Participant 2 had a higher average number of observations on correct and

incorrect matched trials compared with unmatched trials. The longest average duration of

observations occurred on correct matched trials. Unmatched trials had a far lower average


trials,


number of observations, though the average duration was comparable. Correct unmatched trials

had a higher average number of observations compared with incorrect unmatched trials. On four-

stimulus trials, Participant 2 had a similar average number of observations to ROI that had

previously displayed stimuli on both correct and incorrect matched trials. On unmatched trials,

Participant 2 had a lower average number of observations on correct trials, and the highest

average number of observations on incorrect trials, as well as the longest average duration.

Participant 3 had a higher average number and longer average duration on correct unmatched

compared with correct matched one-stimulus trials. There were no incorrect trials at this level of

complexity for this participant. On two-stimulus trials, however, there was a higher average

number of observations on correct matched trials compared with correct unmatched trials.

Finally, on four-stimulus trials, Participant 3 had a higher average number of observations on

both correct and incorrect unmatched trials compared with matched. The highest number, and

longest duration, of fixations occurred on an incorrect, unmatched trial, though it should be noted

that there was only one trial of this type. The bottom panel of Table 6 shows the data for

Participant 4. There were no incorrect one- or two-stimulus trials. The only incorrect trials were

unmatched four-stimulus. Across correct trials Participant 4 had similar average number of

observations on both matched and unmatched trials. One one-stimulus trials this number was 0.

On two-stimulus trials, Participant 4 made an average of 1 and 1.167 fixations on matched and

unmatched respectively, with comparable average durations of observations. On four-stimulus

trials, Participant 4 had an average of 2.333 fixations during the comparison on matched trials,

and an average of 2.11 on unmatched trials, again with highly comparable average durations.

Similar to the other three participants, Participant 4 had the highest average number, and highest

average duration, of observations on incorrect unmatched trials.


Figure 1 is a bar graph presenting the proportion of matched two- and four-stimulus trials

where the participant made at least one observation back to the region of interest where the

correct sample was located during the comparison slide. The X-axis shows the data for each

participant. The solid bars represent an overall percentage of matched two- and four-stimulus

trials with at least one observation made to the region of interest where the correct sample was

presented. The bar with diagonal lines represents the percentage of correct trials with at least one

observation back to the initial sample location, and the bar with vertical lines represents incorrect

matched trials. Data are presented as a percentage of trials. Participant 1 made no observations to

the location where the correct match had been presented during the comparison. Participant 2

made observations to the region of interest where the matched sample had been presented in 30%

of trials. Of correct trials 40% had at least one fixation to the location of the initial sample, and

on incorrect trials only 10% had at least one fixation back to the location of the initial sample.

Participant 3 had a lower proportion (13%) of matched trials where at least one fixation was

made back to the initial location of the matched stimulus, though all of those fixations were

made on correct trials. Participant 4 made at least one observation back to the region of interest

where the correct match had been presented on 25% of trials. Participant 4 made no errors on

matched trials.

Discussion

Accuracy

Across participants, accuracy on the DMTS task decreased as the number of sample stimuli

increased, indicating that the task was becoming more complex. When considering matched

versus unmatched trials, across all participants and levels of complexity, the accuracy score for

unmatched trials was either equal to (at 100%) or higher than for matched trials. The exceptions

were Participant 1 during the one-stimulus trials, where the single error made was on an


Is this also indented?Label this “Discussion” – since it appears under the main heading of Experiment 1 initially, it is understood that it is the discussion for E1, and another experiment is to follow



are


unmatched trial, and Participant 4 during the four-stimulus trials. Excluding these exceptions, it

appears that matching identical stimuli was somewhat more challenging for these participants

than responding to a lack of identity. While it is not clear why this would be the case, and it is

outside the scope of this study to evaluate, it does open an area for future research utilizing

similar eye gaze equipment and measures. For example, it may be fruitful to compare the

fixation pattern when perceiving the initial sample to the fixation pattern when considering the

comparison, and evaluating patterns in how the two stimuli are viewed. For instance, it may be

that a high degree of similarity in viewing patterns is correlated with correctly identifying a

match, and deviations in viewing patterns leads to incorrectly identifying a match as unmatched.

Alternatively, for unmatched stimuli it could be informative to consider how early the viewing

patterns, if they exist, can diverge from each other and result in the participant correctly

identifying the two stimuli as being non-identical.

Latency

Along with the increase in complexity there was also an increase in latency to respond to

the comparison as more stimuli were initially presented. The exception was Participant 3, who

had a lower latency on two-stimulus trials compared with one- and four-stimulus trials. This

participant maintained a fairly consistent latency, of about 2.5s, across all trial types. The other

participants all demonstrated an increasing latency as the number of initial samples went up.

However, while there was overall a pattern across participants demonstrating a greater level of

accuracy on unmatched trials, there was not a similar pattern in the latency to respond correlated

with trial type. On one hand, for all participants with the exception of Participant 4, there was on

average a longer latency to respond on incorrect trials compared with correct trials. Participant 4,

who only made incorrect responses on four-stimulus trials, had a longer latency to respond on

correct trials. When considering whether trials were matched or unmatched there was variability


across participants. This variability indicates that there are individual differences, and possibly

differences within one individual, depending on characteristics of the stimuli, in the length of

time it takes to determine identity versus non-identity. It is unclear how this might relate to eye

gaze patterns, if at all.

Observing responses

In considering accuracy across the four participants, their performance can be roughly

grouped into those with high and low accuracy on each trial type. With the exception of

Participant 2, who had perfect accuracy on one-stimulus trials, Participant 1 and 2 demonstrated

lower accuracy compared with Participant 3 and 4 across all trial types. Participant 1 and 2 also

had a lower average number and duration of fixations to ROI that previously displayed stimuli

across all trial types compared with Participants 3 and 4. Patterns in observing responses during

the delay and comparison will be considered both within each participant and across the broadly

defined groupings of high and low accuracy responders.

Behavior during the delay interval. Despite the fact that the delay screen was blank,

and offered no further stimulation related to the DMTS task, all participants made eye gaze

fixations back to the locations where the stimuli were initially located during the delay. While

the role of these fixations cannot be definitively determined from the current study, there are

patterns both within and between participants that can be examined.

When considering the one- and two-stimulus trials, the comparison between previously

occupied and previously empty locations is possible. On these trials, all participants had a higher

average number and longer average duration of observations to locations where the stimuli had

initially been presented compared with locations that had been blank. For Participants 1, 3, and

4, the average number of fixations to occupied locations was more than four times the average

number of fixations to previously empty locations. For Participant 2, the difference was less


striking, though still more fixations occurred to previously occupied than to empty locations

during the delay. On four-stimulus trials, all locations contained stimuli during the initial sample,

and so the same comparison between occupied and empty regions is not possible. However, the

highest average frequency and longest average duration of fixations to the ROI is seen in this

condition for three out of four participants. Considering the eye gaze data across the increasing

levels of complexity, Participants 2, 3, and 4 displayed an increasing trend in the mean frequency

and duration of fixations as the number of initially presented stimuli increased. The mean

frequency and duration of fixations exhibited by Participant 1, on the other hand, displayed a

decreasing trend, having the highest mean frequency and longest average duration of fixations

during the delay on one-stimulus trials, and the lowest on the four-stimulus trials.

While the data indicate that on the DMTS task participants tended to look back to the

locations where stimuli had been when presented with a blank screen during the delay, the role

of eye gaze cannot be definitively determined. The fixations made during the delay may be

assistive, perhaps covertly re-seeing the stimuli in a manner similar to covertly repeating a list of

items in a verbal recall task. Alternatively the observations made during the delay may be a

corollary behavior, demonstrating a tendency to move one’s eyes, but neither helping nor hurting

accuracy on the matching task. Evidence for the assistive role of eye gaze fixations made during

the delay can be inferred by considering the data across participants, though such a comparison

should be made with caution. Participant 1 and 2 had a lower level of accuracy across all levels

of complexity compared with Participant 3 and 4. Additionally Participant 1 and 2 had a lower

mean frequency and duration of observations to the ROI that displayed an initial sample during

the delay compared with Participant 3 and 4 across all levels of complexity. This may indicate

that making more observations back to the prior locations results in better accuracy. Eye

movements made during the delay may act as a rehearsal mechanism, and individuals who have


e


better accuracy may be better utilizers of this rehearsal strategy. This interpretation would be

consistent with the metaphor of the visuo-spatial sketchpad proposed by Baddeley and

colleagues (Postle et al., 2006; Postle et al., 2005; Baddeley, 1986).

However, when we consider the data within each participant, it is apparent that having a

higher average frequency and/or longer average duration is not necessarily associated with a

greater likelihood of being correct on either matched or unmatched trials. So, while it may be

that individuals with better accuracy are also individuals who happen to fixate more and longer

while engaged in remembering, more and longer fixations do not appear to automatically lead to

better remembering. This is consistent with the results of the study by Godijn and Theeuwes

(2012) who found that, while eye movements did tend to occur during a recall task for a

sequence of visually presented numbers, disrupting the ability for participants to move their eyes

freely did not have a dramatic impact on recall. The interpretation of Awh and colleague was that

it was shifts in attention that aided in memory to visual tasks, and that eye movements were

coincidental with the shifts in attention, rather than being independently necessary (Awh et al.,

1998; Awh & Jonides, 2001).

A final potential interpretation offered here is that it also may also be the case that

individuals simply have a tendency to move their eyes, rather than holding them still. In the

absence of further stimulation during the blank delay screen, fixating back to the location of the

prior samples may be more likely than looking around the room because of the stimulus control

of the computer screen. And a tendency to repeat movements that were recently reinforced may

account for the difference in fixations to locations where stimuli were previously observed,

compared to locations that were blank. In this case, it could be posited that fixating to the

locations of the samples was reinforced by the presence of the samples, and that the behavior of

fixating back to those locations is more likely during the delay as a result. A possible means of


May be


evaluating this explanation could be to have a screen briefly presented after the sample screen,

but before the delay, with stimuli that are irrelevant to the task that draw the participant’s

observations, such as colored dots. The patterns of eye movements could then be evaluated to

determine if participants were more likely to look back to the locations of the initially presented

stimuli, or if they were more likely to look back to the locations of the colored dots, the last

places where they may have been reinforced for fixating. No examples of this type of

manipulation were found in the literature reviewed on visual memory.

Future research could also include strategies for interrupting eye movements, such as

requiring participants to fixate on one location during the delay, similar to the procedures

described by Godijn and Theeuwes (2012). Comparisons could be made between free eye

movement conditions and restricted eye movement conditions on the level of accuracy.

Alternatively, low accuracy responders could receive supplemental stimulation to prompt a

greater number and/or duration of eye movements during the delay, and data could be evaluated

to determine whether there is an impact on accuracy. This strategy was utilized by Dube and

colleagues (2006). In their study on eye gaze patterns, during initial observation of a stimulus

array, the authors found that two of their four participants had high accuracy on the DMTS task,

and the other two had lower accuracy, particularly on the four-stimulus trials. Dube and

colleagues found that the high accuracy responders had a more consistent pattern of eye

movements during observation, as well as a longer duration of fixations. As a follow up the

authors used prompting strategies to encourage the low accuracy participants to utilize a similar

pattern of observations, and showed that they were able to increase accuracy following

prompting (Dube et al., 2006). If a similar strategy of prompting eye movements during the delay

back to the regions where stimuli were initially presented resulted in an increase in accuracy, this

may provide additional support to the assistive aspect of eye movements during the delay.


Dube and colleagues



Comparison. The pattern of observations made during the comparison demonstrates a less

clear pattern compared with observations made during the delay. While participants did make

observations to the ROI where sample stimuli were initially displayed on two- and four- stimulus

trials, on one-stimulus trials all participants had either the same average number of observations

to regions that did or did not display a stimulus, in the case of Participant 1, or more observations

were allocated on average to the areas of the screen where a stimulus had not been presented, in

the case of the other three participants. The data for Participant 1 on the one-stimulus trials does

indicate that, while the same average number of observations were made to areas that did and did

not display a stimulus, the average duration of fixations was greater for the regions where the

initial sample had been presented. On two-stimulus trials, Participant 1 had no recorded

observations back to any of the ROI during the comparison screen. The other three participants

all made fixations back to the ROI. Participant 2 and 4 both had a higher average frequency to

areas that had presented the initial samples. Participant 2 also had a longer average duration of

observations, whereas Participant 4 displayed a comparable average duration to locations that did

and did not initially display stimuli. Participant 3 had a similar average number and duration of

observations to regions that did and did not display stimuli on the two-stimulus trials. All

participants made the highest average number and longest average duration of fixations on four-

stimulus trials. This is consistent with the increase in latency as the number of sample stimuli

increased.

While the average overall latency to respond increased along with the complexity of the

task for three of the four participants, it was still shorter than the 5s delay interval. The initial

instruction screen indicated for participants to try to be accurate, but also to work quickly. A

future study could place a greater focus on being correct, perhaps by providing feedback on

correct and incorrect responses. With a greater emphasis on accuracy, it may be that participants


would exhibit an increased latency to respond. The effect a longer latency might have on the

pattern of eye movements could then be evaluated. To put it in everyday terms, whether a greater

focus on accuracy would lead to participants using more time to “think” about their response, and

whether that “thinking” would include the orderly use of eye gaze fixations prior to making a

selection.

As with the data from the delay, it isn’t possible determine the role of eye movements

during the comparison. Unlike the data from the delay, there isn’t a clear relation between the

average frequency and duration of observation and accuracy. The highest average frequency and

duration of observations made during the comparison were from Participant 2 and Participant 4

on two- and four-stimulus trials. While Participant 1, who had lower accuracy levels on both

two- and four-stimulus trials, had the lowest average number and duration of observations during

the comparison. Participant 3, however, had a high level of accuracy on two-stimulus trials and

the highest level of accuracy on the four-stimulus trials, but demonstrated much lower average

frequency and duration of observations compared with Participant 2 and 4. Considering each

participant’s data individually, they each had the highest average number and longest average

duration of observations on incorrect, unmatched, four-stimulus trials, though in the case of

Participant 3 this includes just one trial.

In considering trials where at least one eye gaze fixation was allocated back to the location

of the correct matched sample (Figure 1), a similar pattern exists across three of the four

participants. Participants 2 and 4 were the most likely to look at least once at the location of the

correct match when viewing the comparison, though neither did so on more that 30% of trials.

Participant 3 looked back at the location where the matched sample had been presented in just

15% of trials, while having some of the highest accuracy scores. For all three of these

participants, they were more likely to look back at the location of the sample on trials that were


F


ultimately correct than incorrect. Participant 1 never looked back to the location of the sample

that matched the comparison.

A confound that may not have been thoroughly controlled for in this study was the use of

verbal behavior. Mandarin characters were selected as stimuli due to their complexity, and it was

presumed that this may impede the tendency to apply labels, or tacts, to the stimuli. However,

participants may still have attempted to apply labels to parts, or the whole, of each stimulus. This

strategy may have played a particular role while viewing the comparison, up to the point of

responding. Future research could utilize both difficult to label stimuli and easy to label stimuli,

such as common objects or written words or numerals, and evaluate the effect that has on eye

movements.

The purpose of Experiment 1 was to evaluate the use of eye movements during the delay in

an increasingly complex object identity DMTS task, and to begin to examine the utility of

utilizing eye gaze measures within a DMTS task to gain access to observable correlates to the

mostly covert behavior of remembering. The increased complexity of the task can be inferred

from the decreasing accuracy as the number of stimuli increased. For three of the four

participants, the latency to respond to the comparison also increased. Across all participants, eye

movements were allocated back to the location where the stimuli were initially located during the

delay, and the average number and duration of eye movements increased as the complexity

increased. Taken together, this provides evidence that the use of eye tracking equipment to

measure eye movements during a DMTS task may provide fruitful data to supplement the

conceptual analysis of a covert behavior, such as remembering. However, the pattern of eye

movements while viewing the comparison did not indicate a strong tendency to use a strategy of

covertly re-seeing stimuli while making a decision on identity. Prior research on visual memory

from the cognitive literature has largely focused on spatial information over object information.


Prior to conducting Experiment 1, Experiment 2 was developed as a pilot to gather some

additional data from the already-secured participants.

Experiment 2

Experiment 2 was developed as a pilot study in order to evaluate eye movement patterns

when a different question was asked within an otherwise very similar DMTS task. While the

purpose of Experiment 1 was to extend the research to include a lexical decision making task

based on identity, the purpose of Experiment 2 was to provide a preliminary extension of the

cognitive literature utilizing spatial information by incorporating location information. Similar to

Experiment 1, participants were presented with a DMTS task. However, instead of responding

based on the identity of the comparison to one of the initial samples, participants were asked to

respond with the location of the previously viewed stimulus. Other features of the task, such as

the nature of the stimuli and the timing rules, were kept consistent across Experiments 1 and 2.

Because Experiment 2 was developed as a pilot there were fewer trials both within each trial

type, and overall.

Methods

Participants, Setting, and Materials

The participants, setting, and materials were all the same from Experiment 1 to

experiment 2. As part of gaining consent for Experiment 1, participants were asked if they would

be willing to participate in additional trials. They were informed that their participation in

Experiment 1 did not obligate them to participate in Experiment 2, though all of the participants

did agree to continue. The additional trials were presented immediately after the trials from

Experiment 1 were completed. No additional financial compensation was provided.

The same computer keyboard was utilized, and all four keys that were marked with a

colored sticker were activated. As in Experiment 1, the green and red stickers were placed over




Experiment



were


Experiments


omit


Omit “Introduction”



the ‘Z’ and ‘/’ keys, though in Experiment 2, they represented the lower left and lower right

quadrants of the screen, respectively. A yellow sticker was placed over the letter ‘W’ to represent

the upper left quadrant, and a blue sticker was placed over the letter ‘P’ for the upper right

quadrant. The spacebar was again used to move the slides forward, and all other keys were made

inactive.


The same pool of Mandarin characters used for Experiment 1 were utilized in Experiment

2. The stimulus set for each trial was drawn at random from the pool, with the restriction that

stimuli that were matched comparisons in Experiment 1 were excluded. The construction of the

stimulus array was the same in both studies.

In Experiment 2, participants completed 12 two-stimulus trials and 12 four-stimulus trials.

For the two-stimulus trials, each possible combination of corners were utilized, with the correct

location for the comparison occupying each location once. For example, the initial sample screen

presented stimuli in the upper right and upper left corners twice, with the correct comparison

location being the upper right once and upper left once. For the four-stimulus trials, the matched

sample was located in each of the three corners three times. The order of trials was randomized

prior to entry into the Presentation TM software, and remained fixed for all participants.

As was the case in Experiment 1, trials were programmed to start with the initial sample

screen, which remained up until the participant pressed the spacebar on the keyboard. Following

the initial sample, there was a 5 s delay, followed by the comparison screen. The comparison

stimulus was one of the two or four stimuli that had been shown on the sample screen. The

comparison remained on the screen until the participant pressed one of the response keys.

Dependent Variable and Definitions



12


12





See comment in Experiment 1 re: abbreviating the heading – I do not recall the rule here – check it to make sure it does not need to be changed.



In Experiment 2, correct responding was defined as the participant pressing the color

coded key that corresponded to the location on the sample screen where the comparison was

initially presented. An incorrect response was defined as pressing one of the color-coded keys

that did not correspond with the initial sample location of the comparison. All other visual gaze

definitions were the same from Experiment 1.

Procedure

Following the completion of the experiment 1 trials, participants were offered a break

from the research room before beginning Experiment 2. All of the participants elected to remain

seated, with the eye tracking equipment still calibrated, and immediately moved on to the second

set of trials. The trials for Experiment 2 began with an instruction screen that read:

“In this experiment you will be presented with two or four characters. After

viewing all of the characters press the spacebar. When you press the spacebar

the characters will disappear. After a few seconds a single character will

appear in the middle of the screen. Your task will be to identify the location

where you initially viewed the character. If the character was initially in the

TOP LEFT press the YELLOW button; for the TOP RIGHT press BLUE; for

BOTTOM LEFT press GREEN; and for BOTTOM RIGHT press RED. Press

any key to begin”

Participants were asked to read the instructions aloud, and the session began when the participant

pressed any key on the keyboard.

After pressing one of the keys, the participant began with the two-sample trials. The two-

sample sessions consisted of 12 DMTS trials, immediately followed by 12 four-sample trials.

The participant was presented with the initial sample screen, which they could view for as long

as they wanted. Pressing the spacebar removed the initial stimulus array and initiated the delay


12


12






interval, which presented a blank screen for 5 s. Following the delay, the comparison stimulus

appeared on the screen and remained on until the participant responded by pressing one of the

colored keys corresponding to the location of the comparison on the initial sample screen. After

one of the keys had been pressed, the screen again went blank for a 5 s intertrial interval. The

next trial then automatically began. Participants did not receive feedback on whether their

response was correct or incorrect.

Results

Because Experiment 2 was developed as a pilot study, there were only 12 presentations of

each trial type. Due to the low number of trials, the calculated means are easily skewed, and all

data should be interpreted with caution.

Accuracy

The accuracy scores on the two- and four-stimulus location DMTS trials is shown in the

first row of Table 7 and 8, respectively. On the two-stimulus trials, Participant 1 made one error,

which translated to 91.7% correct. On the four-stimulus trials, the accuracy for Participant 1

dropped to 66.7%. Participant 2 had the lowest accuracy on the two-stimulus trials at 83.3%, and

the same level of accuracy (83.3%) on the four-stimulus trials. Both Participant 3 and Participant

4 made no errors on the two-stimulus trials, and they each made one error on the four-stimulus

trials.

Latency

Overall latency to respond to the comparison is presented on the second row of Tables 7

and 8 for two-and four-stimulus trials, respectively. Participant 1 responded in 1.876 s to the

comparison on two-stimulus trials and 3.236 s on the four-stimulus trials. Participant 2

responded to the comparison in 1.987s on two-stimulus trials and 2.454 s on four-stimulus trials.

On two-stimulus trials, Participant 3 had a response latency of 1.451 s, and 2.148 s on four-


Or: interpreted with caution


12 presentations of…


were



stimulus trials. Finally, Participant 4 had a 2.433 s latency to respond to the comparison on two-

stimulus trials, and 4.640 s latency to respond on the four-stimulus trials.

Latency is further broken down in rows three and four of Tables 7 and 8 to display average

latency on correct and incorrect trials on two- and four-stimulus trials, respectively. On two-

stimulus trials, Participant 1 had a longer latency to respond on correct trials (1.382 s) compared

with incorrect trials (0.622 s). It should be noted that because Participant 1 made only one

incorrect response on the two-stimulus trials, the latency to respond is presented as an average

for correct responses only. Participant 2 had a longer average latency to respond on incorrect

two-stimulus trials (2.928 s) compared with correct trials (1.987 s). Neither Participant 3 nor 4

had any incorrect two-stimulus trials. On four-stimulus trials, Participant 1 responded to the

comparison after an average of 3.501 s for correct trials and 2.706 s for incorrect trials.

Participant 2 responded after an average of 2.339 s for correct trials, compared with 3.028s for

incorrect trials. Participant 3 and 4 each made one error on four-stimulus trials, so the latency for

correct trials is presented as an average; whereas the latency presented for incorrect trials is for

the one trial. On the four stimulus trials, Participant 3 had an average latency of 2.179 s on

correct trials, and took 1.807 s to respond on the incorrect trial. Participant 4 had an average

latency of 4.596 s on correct trials, compared with 5.136 s on the incorrect trial.

Observing Responses

Delay. The data on the mean frequency and duration of observations during the delay on

two-stimulus trials is presented in Table 7. For all participants, there was a much greater average

frequency of fixations to ROI that initially presented a sample compared with the regions that

were blank. Three of the four participants also had a longer mean duration of fixations.

Participant 1 made an average of 8.5 fixations to locations that had presented a sample,

compared with 0.083 to locations that had been blank, with an average duration of 0.434s,




compared with 0.003s, respectively. Participant 2 made an average of 11.5 fixations, with an

average duration of 0.527s, to occupied ROI, compared with 1.5 fixations and an average

duration of 0.061s. Participant 3 had the highest mean number of fixations (19.75) during the

delay to ROI where a sample had initially been shown, and the mean duration of fixations was

0.068s. Finally, Participant 4 had an average of 11.917 fixations to the region of interest that

contained a sample, compared with 4.833 fixations to a region that did not have a sample. In

addition to having the smallest difference in mean number of fixations between occupied and

empty corners of the screen, this participant also had a higher average duration of fixations to

previously blank regions compared to regions where a stimulus had been presented.

The data during the delay for four-stimulus trials is shown in Table 8. As with Experiment

1, all ROI presented stimuli, so the same comparison between previously occupied and empty

regions of the screen cannot be made. On the four-stimulus trials, Participant 1 and 2 had a lower

mean frequency of fixations compared with the two-stimulus trials. Participant 1 displayed a

mean frequency of 6.583 fixations, and Participant 2 demonstrated mean frequency of 9.917

observations. Participant 1 had a longer mean duration of observations at 0.313s, compared with

the two-stimulus location trials to locations where the stimuli had been shown. The mean

duration of observations made by Participant 2 was 0.525s on the four stimulus location trials,

which is just over a third of the average duration of observations made by this participant on

similar two-stimulus trials. Participant 3 and 4 both demonstrated a higher mean number of

fixations on the four-stimulus trials compared with the two-stimulus trials. Participant 3 had the

highest mean frequency of fixations at 22.333, though the mean duration of fixations was slightly

shorter than for two-stimulus trials at 1.557s. Participant 4 displayed an average of 17 fixations

to the ROI during the four-stimulus trials, with a mean duration of 1.297s.


During the four-stimulus location trials, with a mean…


is this across participants or 4 v 2 stimulus trials?


demonstrated


(value)


this is a little confusing.Perhaps:“Participant 1 had a longer mean duration of observations (0.313s) to locations where the stimuli had been shown on the four-stimulus location trials, as compared with the two-stimulus location trials, in which the average duration was x.xxx s”


is this on four-stimulu trials?


demonstrated



Provide the values, since you have done so with all other participants


What about to the regions that were blank?


In most of your paper, you list the duration as “x.xxx s”. However, in this section, you are listing it as “x.xxxs”Check to make sure you are listing it consistently throughout the manuscript. I noticed it here, but do not recall if it occurred in previous areas.


omit


Table 9 displays the mean frequency of observations for each participant during the delay

and comparison for two- and four-stimulus trials as a function of whether the trial was ultimately

correct or incorrect. The columns present the data for each participant, with sub-columns for

trials that were correct and incorrect. The mean duration of fixations is shown in brackets.

Participant 1 had substantially more fixations to locations where stimuli had been located on

two-stimulus trials that were ultimately correct compared with those that were ultimately

incorrect. On four-stimulus trials, on the other hand, the average number of observations is only

slightly higher for correct than for incorrect trials. Participant 2, on the other hand, had very

similar average numbers of observations on both correct and incorrect two-stimulus trials. On

four-stimulus trials, however, a higher average number and longer average duration of fixations

occurred on incorrect trials. Participant 3 and 4 had no incorrect two-stimulus trials, and one

incorrect trial each on the four-stimulus set. On four-stimulus trials, Participant 3 made on

average almost twice as many fixations to occupied ROI on the incorrect trial compared with the

average number for correct trials. Participant 4 had a much higher average number and duration

of fixations on correct trials compared with the incorrect trial data point.

Comparison. The average frequency and durations of observations made while the

comparison slide was presented, up to the participant’s response is presented in Table 7 and 8 for

two- and four-stimulus trials, respectively. Table 9 also presents data gathered during the

comparison as a function of whether the trial was correct or incorrect. On two-stimulus trials, all

participants made a higher average number and longer average duration of fixations to regions of

the screen where stimuli were initially presented compared with regions that had been blank.

Participant 1 had an average of 0.167 fixations to occupied regions of the screen compared with

0 to previously blank regions. Participant 2 had an average of 1.75 fixations to the occupied ROI

as well as the longest average duration of fixations to those regions at 0.417s. Participant 3 and 4


had the highest average frequency of observations to ROI where stimuli had been presented.

Participant 3 made an average of 2.5 fixations to sample presentation regions, compared with

0.167 to blank regions during the comparison slide. Participant 4 had an average of 2.833

fixations to ROI where a sample had been presented, compared with 0.75 to ROI that had been

blank. Both participants also had a longer average duration of fixations to areas where stimuli

had been presented.

Comparison data for four-stimulus trials is shown in Table 8 in the bottom two rows. As

previously mentioned, all regions of the screen displayed stimuli during the sample presentation.

Participant 1 had an identical average number of fixations to the ROI on four-stimulus trials as

on two-stimulus at 0.167. Participant 2 and 3 both had a lower average frequency and duration of

observations on four-stimulus trials compared with the average number of observations to

regions where stimuli were presented on two-stimulus trials. Finally, Participant 4 had a slightly

higher average number of observations, and a slightly shorter average duration of observations,

on four-stimulus trials compared with two-stimulus trials.

Table 9 displays average observation frequency and duration data as a function of whether

the trial was correct or incorrect, with the comparison data presented in the bottom rows for two-

and four-stimulus trials. The average frequency of observations is shown as the top number with

the average duration presented in brackets below. The observations made by Participant 1 during

the comparison on both two- and four-stimulus trials were all made on trials that were correct.

Participant 2 had a higher average number of observations on correct two-stimulus trials

compared with incorrect trials. On four-stimulus trials, however, there was a substantially higher

average number of observations on incorrect trials, though the average duration of observations

was longer on correct trials. Neither Participant 3 nor 4 had incorrect two-stimulus trials. Both


had a higher average frequency and duration of observations on correct four-stimulus trials,

though as mentioned previously, there was only one incorrect four-stimulus trial for comparison.

Discussion

The results of Experiment 2 are consistent with the results of Experiment 1 in terms of

accuracy, latency, and observing responses during the delay and comparison. Where differences

emerge is in the numbers for the average frequency and duration of observations made,

especially during the delay, but also the comparison. In considering the observing responses, the

average frequency and duration of fixation made to the locations where stimuli had initially been

presented were higher for some participants compared with the similarly complex trials for

Experiment 1.

Accuracy and Latency

While the nature of the DMTS task differed in that participants were asked to match

location rather than identity, the results of Experiment 2 replicated the results of Experiment 1 in

that the increase in the number of stimuli led to a decrease in the accuracy of responding across

all participants. The change from two-stimulus trials to four-stimulus trials may therefore be

interpreted as being an increase in task complexity. Also consistent between the two studies,

Participant 1 and 2 had lower accuracy scores compared with Participant 3 and 4.

As the task became more complex, a longer average latency to respond was also evidenced

by all four participants. In considering the average latency to respond on trials that were

ultimately correct and incorrect, there was variability. On the two-stimulus location trials,

Participant 1 and 2 made the only errors, though it should be noted that Participant 1 made only a

single error. On that single incorrect trial, Participant 1 had a shorter latency to respond

compared with the average for correct trials. Alternatively, Participant 2 had a longer average

latency to respond on incorrect trials compared with correct trials on both two- and four-stimulus






trials. Participants 1, 3, and 4, on the other hand, had a longer average latency to respond on

correct trials compared with incorrect.

Observing responses

Delay. In general, the data on observing responses made during the delay in Experiment

2 are consistent with the results of Experiment 1. In the presence of a blank screen, and therefore

the absence of further stimulation, participants all demonstrated a tendency to fixate back to the

locations where the stimuli were initially presented, rather than holding their eyes still, or

looking at other areas of the screen. On the two-stimulus location trials, all participants had a

substantially higher average number of fixations to locations where the stimuli had been initially

presented compared with the areas that had been blank. The average number of fixations to

locations where samples were presented was higher in the location trials compared with the

identity trials from Experiment 1 for Participants 1, 2, and 4. Participant 4 had a higher average

number of observations on the two-stimulus trials in Experiment 1 compared with Experiment 2.

Also, the difference in the average number of observations to regions with samples, compared to

blank regions, was much greater for Participants 1, 2, and 3 than for the comparable two-

stimulus trials from Experiment 1. Participant 4, on the other hand, had a very similar level of

difference in the average number of fixations to regions where sample had been presented and

regions that were blank across Experiments 1 and 2. On the four-stimulus trials, Participants 1

and 2 had a lower average frequency of observations to the four regions of the screen, all of

which presented stimuli on the sample screen. Participant 2 had a similar average duration of

observations to regions that displayed stimuli, where Participant 1 also had a lower average

duration of fixations. This is in contrast to Participants 3 and 4 who both had a higher average

number and duration of fixation on the four-stimulus trials. It should be noted, however, that the

average frequency of observations made by Participant 4 on the four-stimulus trials is roughly







equal to the average frequency of fixations to locations that did and did not display stimuli on the

two-stimulus trials. The higher average frequency of fixations seen in the four-stimulus trials

may, therefore, be somewhat artificial for Participant 4.

Comparison. The data from Experiment 2 on the observing responses during the

comparison are also consistent with the results from Experiment 1. There was a far lower

average number and duration of fixations made during the comparison compared with the delay.

On both the two-stimulus and four-stimulus trials, all of the participants had a higher average

frequency of fixations to the locations where the samples were initially presented on the location

trials compared with the identity trials from Experiment 1. Participants 2, 3, and 4 also had a

greater discrepancy in average frequency between locations that did and did not display an initial

sample in the two-stimulus trials in Experiment 2. At both levels of complexity, Participants 1

and 2 had a lower average frequency and duration of observations during the comparison

compared with Participants 3 and 4, along with lower accuracy.

As with Experiment 1 the role of fixations made during the delay and comparison cannot

be determined from these data. Similar future manipulations may provide greater clarity on the

assistive versus coincidental role of eye movements during a DMTS task. The similarity in

results between Experiments 1 and 2 may call into question the distinction between systems for

spatial versus object memory posited by Baddeley and colleagues (Baddeley, 1986; Postle et al.,

2006). While the average number of observations was higher in most instances in the location

DMTS task compared with the identity task, there were also fewer trials. Further replication with

more trials would allow for an even more direct comparison between the two types of tasks.

General Discussion

Taken together, Experiments 1 and 2 provide some initial suggestions regarding the utility

of using eye gaze as a dependent variable to begin to examine the otherwise covert phenomenon







of visual memory. The data from both studies indicate that, even when there is no additional

stimulation to be gained by doing so, individuals tend to allocate eye movements to screen

locations where sample stimuli were initially presented. While the data from these two studies

are indicative of the occurrence of this tendency, no firm conclusions can be drawn about the

specific role, or relative importance, of eye movements in either an identity or location-based

DMTS task. However, the procedures and the measures open avenues for future research

examining behavior analytic accounts of the complex human behavior of remembering.

Utility of Eye Tracking in a DMTS Task

Utility of DMTS task. This study extends previous cognitive research on visual working

memory by utilizing a DMTS task with difficult to name stimuli. While the use of a DMTS task

incorporating nonsense stimuli is common in behavior analytic research, particularly related to

stimulus control, few examples were found in the cognitive literature that utilized a similar

research paradigm. The studies by Postle and colleagues (Postle, et al., 2006; Postle, et al., 2005)

provided the closest comparison in their use of difficult to name stimuli in a delayed recognition

task. The studies by Postle and colleagues utilized shapes that had been shown to have a low

level of prior association. In the object recognition tasks, the authors required a yes/no decision

as to whether a comparison object matched the initial sample after a delay. In contrast to the

current study Postle and colleagues (Postle, et al., 2006; Postle, et al., 2005) presented only one

stimulus as a sample, and the primary dependent variable they measured was accuracy following

different distraction tasks. The distraction tasks were designed to test the presence of different

visual memory sub-systems by selectively interrupting either object or spatial visual working

memory. This was accomplished by introducing either a verbal task to disrupt object recall, or a

movement task to disrupt spatial recall, along with a free eye movement control condition. Eye

movements were tracked in order to ensure the integrity of the movement disruption task, rather


specify


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than as a dependent variable in its own right (Postle et al., 2006). Also, in contrast to the current

study, Postle and colleagues (2005) changed the nature and complexity of the verbal distraction

task, rather than altering the complexity of the recall task itself, in order to control for the greater

difficulty of the verbal task.

The use of difficult to name stimuli, with which participants have a minimal prior history,

may offer some advantages over the use of other stimulus types, such as numbers (Godijn &

Theeuwes, 2012) or animals (Laeng, et al., 2014). One advantage is that it may reduce a source

of variability across trials, and across participants, allowing for comparisons to be made. When

participants have a prior history with the stimuli being used, performance on the task may be

variable based on that prior history, rather than being under the control of the task itself. Another

advantage to using difficult to name stimuli may be in minimizing the opportunity to utilize

verbal strategies when examining nonverbal remembering. The purpose of the current study was

to begin to examine observable behaviors that may occur in conjunction with covert behaviors

involved with remembering. By minimizing the opportunity to use verbal strategies, including

tacting the initial sample, and then echoing the tacts as a rehearsal strategy, it may be possible to

gain insight into how similar performances happen in our everyday experience.

The use of the DMTS task itself may also offer some advantages over other experimental

manipulations that were found in the literature. For example, the study by Tremblay and

colleagues (2006) utilized eye movements as a dependent variable that they correlated with

correct recollection of the order of presentation of a set of seven dots. However, the dots

remained on the screen throughout the delay. The authors found that recall for dot pairs that were

rehearsed, as indicated by eye movements, was somewhat better than for unrehearsed pairs

(Tremblay et al., 2006). What cannot be determined is what the performance might have been if

there was no further stimulation to be gained by looking at the screen. As with minimizing verbal


The authors


behavior associated with remembering visually presented information, examining behavior in the

absence of stimuli may provide a better analog to some everyday experiences where we respond

regarding something that is no longer present. The structure of the present DMTS task would

allow for future studies to evaluate differences in performance when stimuli are left up during

the delay, as in the study by Tremblay and colleagues (2006), compared to when the delay

interval is blank. Also, the length of the delay can be easily manipulated to evaluate any

differences between shorter, longer, and even unpredictable delay lengths.

The current study replicated research conducted by Dube and colleagues (2006) by

demonstrating an ability to increase the complexity of a DMTS task by increasing the number of

samples initially presented. Dube and colleagues found that increasing the number of samples led

to a corresponding decrease in accuracy in both Experiment 1 and Experiment 2. An additional

measure that may indicate an increase in task complexity was an increase in latency to respond to

the comparison as the number of initial samples increased, which was demonstrated by three of

the four participants in the current study. The increase in latency may be a more sensitive

measure than accuracy for this type of DMTS task, as it may be less vulnerable to a ceiling

effect. In the current study, increasing the level of complexity allowed for the comparison of eye

gaze measures in increasingly difficult tasks. Another comparison afforded by the current DMTS

task was in the allocation of eye movements to areas of the screen where stimuli had been

initially presented compared with areas that were blank on the one-stimulus and two-stimulus

trials. This type of demonstration was not found in any of the reviewed literature on visual

memory. Future studies could manipulate the complexity level further by including a greater

number of initial samples, or placing the samples in less predictable locations.

Utility of eye tracking measures. The current study also extends the research conducted

by Dube, and colleagues (2006) by providing further demonstration of the utility of eye gaze


omit


measures as a dependent variable. In the current study, the dependent variables provided by the

eye tracking equipment included the number and duration of fixations. Future studies could

incorporate other measures, including the pattern of fixations. Much of the research on visual

memory has come out of the domain of cognitive psychology. With few exceptions (Bochynska

& Laeng, 2015; Laeng et al., 2014; Tremblay et al., 2006), the use of eye gaze measures has been

restricted to ensuring the integrity of the independent variable (Godijn & Theeuwes, 2012; Postle

et al., 2006; Postle et al., 2005). In constructing their tasks the authors (Godijn & Theeuwes,

2012; Postle et al., 2006; Postle et al., 2005) started with a hypothesis regarding the nature of

visual working memory, and then sought to validate that hypothesis by providing interfering

tasks and demonstrating a disruption in accuracy. With this framework, the use of eye gaze

measures as a dependent variable is unnecessary. Alternatively, behavior analytic research takes

an inductive, approach to questions about all forms of behavior, including complex processes,

such as remembering. This approach necessitates the use of direct measures of the behavior of

interest, rather than correlates that are hypothesized to demonstrate inner structures and

processes. Thus, in order to develop hypotheses about the role of eye movements in a delayed

recall task, it is necessary to measure the eye movements themselves.

Using eye tracking equipment, it was possible to measure sensitively a behavior that would

otherwise not be available as a dependent variable, and as the technology continues to improve,

the measurement will likely also become more sensitive. This may allow researchers to extend

the conceptual analysis of complex human behavior by demonstrating aspects of complex,

mostly covert, behavior chains that are consistent with the experimentally derived principles of

behavior (Palmer, 2010). While the current study does not allow for a determination to be made

about the role of eye movements, it does demonstrate that such questions may be amendable to

the experimental methods of behavior analysis. As a behavior, eye movement is a free operant,





and an individual’s eye gaze behaviors may happen mostly without the interference of rule-

governed behavior. However, it is also a behavior that may be brought under the control of rules,

for instance by requiring that the eyes be held still (Godijn & Theeuwes, 2012), or that they

move in either a random way (Postle et al., 2005), or in a specified way (Postle et al., 2006).

Future studies should alternate the use of free and restricted eye movement conditions in a single

subject research design to gain greater insight on how the use of eye movements might relate

functionally to the behaviors involved in remembering. The functional roles for eye gaze could

include acting as a rehearsal mechanism, consistent with the notion of covert seeing, as was

suggested by Skinner (1953). The same behaviors that occurred as part of seeing are conditioned

to occur at a covert level under circumstances where doing so leads to reinforcement in the form

of improved accuracy to the comparison. Alternatively, it may be that eye movements are

coincidental with whatever covert behaviors are occurring, but that their presence neither assists

nor detracts from the ultimate performance on the DMTS task. For instance, it may be that there

is simply a tendency to repeat behaviors that have recently been reinforced, with the reinforcer in

this case being opportunity to observe the initial samples. The eye movements may then persist

in the absence of further reinforcement, at least until the comparison stimulus is presented. One

way of evaluating this hypothesis may be to look at the pattern of eye movements as the delay

progresses. If eye movements during the delay are the result of reinforcement during the initial

sample, then perhaps the rate at which this behavior occurs might change in an orderly way as

the delay progresses. And finally, it may be that eye gaze fixations during a DMTS task serve

different functions for different individuals, or in different situations.

Evaluation of Eye Gaze in the DMTS Task

Delay. In both Experiments 1 and 2, all participants fixated back to the areas of the

screen where samples had initially been presented during the delay. This is despite the fact that



should




during the delay there was no further stimulation to be gained by looking back to these regions.

On the one-stimulus and two-stimulus identity trials, and on the two-stimulus location trials, it is

possible to compare the number and duration of fixations to locations where samples had initially

been presented compared with the regions that had been blank. On these trials, all participants

made more observations, for a longer total average duration, to the regions where the sample(s)

had been located compared with the number of fixations to the regions that had been blank. A

further comparison can be made in considering the pattern as the complexity increased. Across

Experiments 1 and 2, with few exceptions, the number of fixations increased as the number of

stimuli increased, and the highest average number of fixations occurred during the delay on the

four-stimulus trials. A final comparison, made with caution, is between participants. Two of the

participants consistently had a higher level of accuracy, and two had a lower level of accuracy.

Overall, a higher average frequency and average total duration of observations was displayed by

the high accuracy responders compared with the low accuracy responders.

In contrast to these data trends, however, in both Experiment 1 and Experiment 2, correct

trials were not associated with the highest average frequency or duration of fixations during the

delay compared with incorrect trials. So simply looking back to regions where stimuli were

presented during the delay did not lead in an automatic way to be a greater likelihood of being

correct on any given trial.

Comparison. The data on fixations during the comparison slide demonstrated greater

variability both within and across participants in their tendency to fixate back to regions where

stimuli were initially presented. Comparing the results of Experiment 1 and Experiment 2, there

were a higher number of fixations during the comparison when the task was to indicate the initial

location of a match as opposed to the identity of a match. As with the data from the delay, the

increase in complexity was also associated with an increase in the mean frequency and duration


of fixations in most instances, though to a much smaller degree. There was also a greater average

number of fixations demonstrated by the high accuracy responders compared with the low

accuracy responders, though again to a much smaller degree. As with the data from the delay

interval, there was variability on whether a higher frequency of observations during the

comparison was associated with correct or incorrect trials.

Behavioral Explanations

The results of this study do not either rule in or rule out any particular cognitive theory of

visual working memory, or even the presence of a visual working memory system in general.

The purpose of the study was to utilize direct measures of behavior that occurred during a task

that involved responding to a stimulus in its absence, and possible explanations for the data will

largely be restricted to accounts that are consistent with empirically validated principles of

behavior. The principle of determinism applied to behavior indicates that behavior happens for a

reason. Behaviors occur in the presence of discriminative stimuli that indicate the availability of

a reinforcer that is currently motivating, and continue to occur in similar circumstances because

of a history of reinforcement. There are several possible explanations for these data that are

consistent with the principles of behavior, based primarily on differing sources of reinforcement

as well as discriminative stimuli.

Covert seeing. The eye movements may function to assist the individual in responding to a

stimulus that is no longer present as a rehearsal strategy. This would be consistent with a

behavioral interpretation of visual remembering that proposes the possibility of covertly re-

seeing the stimuli, in a manner similar to the covert repetition of verbal stimuli. As opposed to

the cognitive theory of a visuo-spatial sketchpad (Baddeley, 1986), this interpretation does not

require a hypothetical construct that is responsible for the strategy. Instead, seeing is considered

to be a behavior, and as a behavior it may occur to a small enough degree to be considered


covert, if engaging in the behavior is reinforced. In this case, the reinforcement would be the

ability to respond to the comparison. There is not, in this behavioral interpretation, a version of

the stimulus that is being viewed and manipulated, but rather, a tendency to engage in similar

behaviors covertly that would lead to reinforcement if done overtly while in the presence of the

stimuli, based on prior learning history

Transitive conditioned motivating operation. A related explanation is that the data may

be consistent with what would be expected if the participants engaged in a behavior chain that

led them to respond to the comparison after the delay. The presentation of the initial sample sets

the occasion for the behavior of remembering that then makes supplemental stimuli

reinforcing. As part of problem solving, individuals may then look for supplemental stimuli,

even in their absence of the stimuli. In this case, the regions of the screen where stimuli were

initially presented may be considered to be a transitive conditioned motivating operation (CMO-

T), where their value as a reinforcer for the behavior of looking is momentarily increased as part

of a behavior chain that terminates with a response to the comparison (Michael, 1993). This does

not necessarily imply that the behaviors are required to reach the terminal response in the chain,

though it also doesn’t rule that out either. That the regions may function as CMO-Ts, and

allocating eye movements to the regions is momentarily more likely because of their place in the

chain, would be consistent with the hypothesis of covert seeing described above, but may also

stand alone as its own behavioral explanation for the data. In this case, the movements may have

been conditioned as part of the larger chain without being necessary to the chain. A disruption in

the chain, by restricting eye movements in some way, may then result in a longer latency to

respond, but not necessarily a disruption in response accuracy.

Behavioral repetition. A final alternative explanation offered here may be that in viewing

the initial sample screen, more stimuli require more eye movements, and it is that tendency that


is being repeated, to a smaller extent, during the delay. Eye movements and fixations are

behaviors associated with initially observing the stimuli, and may be reinforced by the

opportunity to observe the sample(s). Behaviors that have been recently reinforced have a

tendency to be repeated. During the delay, it may that the behaviors are simply being repeated

due to their reinforcement history, and due to a more general tendency to engage in some sort of

behavior during a delay. As was suggested earlier in this manuscript one possibility for

evaluating this explanation may be to look at eye movement patterns as the delay progresses.

Further research utilizing eye tracking equipment during a DMTS task is necessary to further

define the role of eye movements during the delay.

Future research

Given that the purpose of the current research was to examine visual remembering by

utilizing eye gaze measures as a dependent variable in a DMTS task, one of the primary

outcomes of the current study is the identification of questions for future research. There are

several possibilities for an extension of the current research to address both limitations of the

current study, and to further explore some of the questions raised. As an initial suggestion, future

studies should look to utilize research designs that allow for functional relations to be drawn.

Many of the suggestions made below may be amendable to the use of some variation of a

reversal or multielement design.

The nature of the DMTS task allows for several manipulations to refine our understanding

of when and how eye gaze behaviors occur during a DMTS task. For instance, the delay interval

could be lengthened to assess what impact that would have on the same eye measures. It may be

that the use of eye gaze fixations increases as the delay increases in order to maintain the

response. A longer delay may also better allow for a closer examination of how eye gaze

behaviors change as the interval progresses. Additionally, in the real world, we often cannot


is the identification of questions…


predict how long of an interval there will be between the observation of stimulus and the need to

respond based on that observation. Future studies could examine eye gaze patterns when the

length of the delay is unpredictable.

The current study attempted to control for verbal behavior by utilizing Mandarin language

characters. Mandarin characters were selected due to their relative complexity. The goal of using

complex stimuli was that it would make them difficult to name, thereby reducing the ability to

use verbal strategies during the DMTS task. However, the participants may still have behaved

verbally by assigning labels to parts, or the whole, of each character, and then engaged in covert

verbal rehearsal instead of, or along with, visual strategies. Because of the individual nature of

learning histories, it may not be possible to fully control for the use of the verbal behavior, that

may or may not occur, in this task. Studies from the cognitive domain have utilized different

interfering tasks during the delay in order to confound the use of verbal behavior that may or

may not be emitted during the delay (Postle, et al., 2005; Postle, et al., 2006). In these studies,

the effect of the distraction task was measured indirectly by looking at accuracy, rather than

considering the impact directly on eye movements. A further confound inherent in this

methodology is that the distraction task may simply mask the stimulus control that allows an

individual to respond to a visual stimulus after a delay, rather than interfering with a specific

covert response. An alternative way of evaluating the question may be to compare difficult to

name stimuli with easy to name stimuli and consider any differences in the participant’s use of

eye gaze. The easy to name stimuli could include common objects or written words. Or, in order

to minimize prior learning history, labels could be developed and taught for a subset of the

characters. Then, using either a reversal design between difficult and easy to name stimuli, or a

multielement design between the two stimulus categories, the impact on eye gaze measures could

be evaluated.


Behaved verbally by assigning


Another avenue for future research could present a single stimulus, and record the scan

path, along with any other salient patterns, as the individual initially observes the stimulus.

Correspondence between the initial observation patterns and the eye gaze patterns towards a

matched or unmatched comparison could then be evaluated. It could be that similar viewing

patterns are associated with correctly identifying a match, or that a divergence in viewing

patterns results in incorrectly identifying a match as unmatched. This result could lend support to

the covert seeing hypothesis, that the same behaviors that led to successful initial observation are

repeated in order to respond correctly after the delay.

Research on visual memory could be extended in future research using the DMTS

paradigm, by interrupting the participant’s eye movements during the delay. The participant

could be required to hold their eyes fixated on a point presented on the delay screen. This

manipulation could be presented in a reversal design with conditions where the participant can

move their eyes freely. The use of forced movements could also be used instead of forced

fixation, similar to what was demonstrated in th third experimental question in the collection of

studies presented by Postle, and colleagues (2006). Correlations between accuracy and the free

or restricted use of eye movements may add support to the hypothesis that eye movements play

an assistive role in visual memory tasks.

In order to explore the hypothesis that eye movements during the delay are due to repetition

of recently reinforced behavior, rather than being functionally related to accurate responding on

the DMTS task, an additional screen with task irrelevant stimuli, such as simple dots, could be

presented immediately after the sample screen, before the delay, in screen locations that are

randomly assigned. Eye movements could then be evaluated for whether fixations occurs more

frequently, or for a longer duration, toward the locations most recently observed, or towards the


locations where the relevant samples had been presented. This information could be correlated

with accuracy similar to the current study.

Not surprisingly, there were differences in accuracy across participants on the DMTS task,

particularly as it became more complex. The differences in accuracy were also associated with

differences in eye gaze fixations, particularly during the delay. An extension of the research

conducted by Dube, and colleagues (2005) could include providing some supplemental

stimulation for low accuracy responders during the delay to prompt their eye movement patterns

to more closely match the patterns displayed by the high accuracy responders. Following

training, the continued use of similar eye gaze patterns in the absence of prompting could be

evaluated, along with its impact on accuracy. Another avenue for changing the performance of

the participants, particularly those with lower accuracy scores, could be to provide feedback on

correct responding, and perhaps to provide additional reinforcement contingent on correct

responding.

Should further research continue to suggest an assistive role for eye movements during the

delay, and while viewing the comparison, this may provide insight on teaching strategies for

individuals who struggle to respond to visually presented material after a delay. For instance,

individuals with a developmental delay or dementia may be able to be taught to utilize shifts in

eye gaze to actively maintain the behavior of looking until the opportunity to respond.

Limitations

There are several limitations to the current study. A primary limitation is the lack of a

strong functional relation demonstrated by the results. This is in part due to the structure of the

current study, which can be addressed in future research, and in part it is due to the nature of the

problem. There may always be a point at which the overt becomes the covert, and is no longer

accessible to measurement. However, this should not discourage future research into complex


human behavior such as remembering, as additional evidence will add to our ability to make

interpretations regarding covert behavior based on empirically derived information, rather than

relying on speculation. The current study does not rule out cognitive explanations for

remembering in favor of a behavioral explanation. Nor does it rule out or in any particular theory

of visual memory.

With regards to improving the functional relations demonstrated in future studies, single-

subject research designs, such as reversal and multielement designs, could be utilized to measure

the impact of the chosen independent variable on eye gaze and accuracy in a DMTS task. The

current study replicated the design of Dube, and colleagues (2006), and the purpose of the two

studies were very similar, which was to demonstrate the utility of the eye tracking equipment and

eye gaze measures to begin to examine an otherwise largely covert phenomenon. The internal

validity of the study could be strengthened by conducting systematic replications, using a

research design that allows for greater confidence in the results, as well as considering more

rigorous single-subject designs when examining future research questions. For example,

conditions that allow for, and restrict the use of, eye movements during the delay could be placed

into a reversal design, as could varying delay lengths, or comparing easy and difficult to name

stimuli. Alternatively, these same variables could be compared using a multielement design.

A related limitation of the current study is the small number of trials and participants,

limiting the ability to use the tools of statistics to achieve greater confidence in the results. The

use of single-subject research is one of the hallmarks of behavior analysis, and may continue to

be the most appropriate, given that the function of eye movements during the delay may differ

among participants. However, by including a greater number of trials to allow for the use of

statistics we may gain further insight into the nature of the role of eye movements in a DMTS

task, as well as greater confidence in the robustness of the results.


An area for future research that has already been suggested is to evaluate performance in

the presence of easy and difficult to name stimuli in order to control for some of the impact of

verbal behavior. Participant verbal behavior during the task is another limitation of the current

study. That participants may have engaged in some covert verbal behavior while completing the

task is likely, given the learning history that most of us have in using this type of rehearsal

strategy. The tendency to engage in rehearsal behavior increases the challenge of determining the

functional role of eye movements that were measured during the DMTS task.

A final limitation of the current research is the relative sensitivity of the equipment. The

eye tracking equipment used in initial studies by Baddeley and colleagues (reported in Postle et

al., 2006) were described as being of low sensitivity. The fourth experiment reported in the

collection of studies was completed, in part, to utilize more sensitive measures. As is the case

with many other technologies, we should expect that the sensitivity of eye tracking equipment,

and the resulting measures, will become more sensitive over time. It is difficult to predict how

improved sensitivity will change our understanding of the use of eye gaze during a DMTS task;

however this should not prevent future research from seeking out improved equipment and the

data they generate.

Conclusion

In conclusion, the results of this study contribute to the literature on complex human

behavior, and provide some suggestions on how stimulus control might operate over a delay

interval. The results indicated that individuals tend to allocate eye gaze fixations to the locations

where samples were initially presented during the delay, and that the pattern of these fixations

increased in a somewhat orderly way as the number of initial samples increased. These findings

extend the research of Dube, and colleagues (2006) by utilizing eye tracking equipment in a

DMTS task, and examining eye gaze measures during the delay and comparison, rather than the



initial observation. Additionally, the present research presented a slightly different DMTS task,

which extended the cognitive literature on visual memory (Postle et al., 2006; Postle et al.,

2005), by requiring the participant to identify whether the comparison matched one of the

samples, as well as identifying the initial location of the comparison. While the results do not

provide definitive answers about the behavior of remembering, they do indicate that this research

paradigm may allow us to further a research agenda into complex, often covert, human behavior.

By doing so we may enhance our understanding of our own behavior, as well as allow us to

develop techniques to help those who may struggle to perform tasks that rely on responding to

visually presented material after a delay.

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Running head: EXAMINING EYE GAZE IN A DMTS TASK

80

Table 1

One-stimulus trial data

Participant 1 2 3 4

Overall accuracy (%) 87.5 100 100 100

Accuracy on matched trials (%) 100 100 100 100

Accuracy on unmatched trials (%) 66.7 100 100 100

Mean frequency of fixations during the delay

ROI that DID contain a sample 4.875 (5.793)

2.875 (2.800)

5.375 (4.534)

4.75 ( 2.712)

ROI that DID NOT contain a sample 1.125 (2.475)

2.25 (2.916)

1.125 ( 1.126)

0.625 ( 1.408)

Mean duration of fixations during the delay


0.244 (0.261)

0.434 ( 0.214)

0.496 ( 0.177)

ROI that DID NOT contain a sample 0.04 ( 0.088)

0.17 (0.263)

0.054 ( 0.053)

0.263 ( 0.486)

Mean frequency of fixations during the comparison

ROI that DID contain a sample 0.25 (0.463) 0 0.75

(1.035) 0


1.25 (0.354)

1.375 (1.847)

0.625 (1.06)

Mean duration of fixations during the comparison

ROI that DID contain a sample 0.02 (0.046) 0 0.058

(0.079) 0

ROI that DID NOT contain a sample 0.008 ( 0.025)

0.004 (0.011)

0.07 ( 0.108)

0.076 (0.131)


One-stimulus trial data

Participant

1 2 3 4 Overall accuracy (%) 87.5 100 100 100

Accuracy on matched trials (%) 100 100 100 100

Accuracy on unmatched trials (%) 67 100 100 100


ROI that DID contain a sample 4.875 (SD 5.793)

2.875 (SD 2.800)

5.375 (SD 4.534)

4.75 (SD 2.712)

ROI that DID NOT contain a sample 1.125 (SD 2.475)

2.25 (SD 2.916)

1.125 (SD 1.126)

0.625 (SD 1.408))



0.244 (SD 0.261)

0.434 (SD 0.214)

0.496 (SD 0.177)


0.17 (SD 0.263)

0.054 (SD 0.053)

0.263 (SD 0.486)


ROI that DID contain a sample 0.25 (SD 0.463) 0 0.75

(SD 1.035) 0


1.25 (SD 0.354)

1.375 (SD 1.847)

0.625 (SD 1.06)


ROI that DID contain a sample 0.02 (SD 0.046) 0 0.058

(SD 0.079) 0


0.004 (SD 0.011)

0.07 (SD 0.108)

0.076 (SD 0.131)

Note: The accuracy on identifying a

matched or unmatched comparison, and mean frequency and mean duration of observing responses to ROI (ROI) on one-stimulus

trials. Standard deviation from the mean is presented in brackets.

Table 2


The table lines are missing – try copying the table made in another word document and pasting it as a JPEG (paste special option). This will allow you to adjust the table without losing the content/proportions.You also want the table to appear in Times New Roman font size 12. There is a way to add a page with a landscape orientation, which would allow you to fit the whole table in without reducing the font. It would still read in a normal orientation, except the page size would be adjusted so that it is wide and short just for this (and any other) page. If you are able to easily do this, I recommend doing it for Tables 1-4.


Two-stimulus trial data Participant

1 2 3 4 Overall accuracy (%) 87.5 79.2 95.8 100

Accuracy on matched trials (%) 83.3 75.0 91.7 100

Accuracy on unmatched trials (%) 91.7 83.3 100 100



6.292 (4.750)

9.583 (6.659)

14.667 (9.563)


1.208 (1.414)

2.625 (6.672)

7.125 (7.870)



0.273 ( 0.233)

0.673 (0.507)

1.143 (0.836)


0.053 (0.075)

0.093 (0.226)

0.570 (0.678)


ROI that DID contain a sample 0 1.292 (2.053)

0.375 (1.096)

1.083 (1.586)

ROI that DID NOT contain a sample 0 0.715 (0.994)

0.333 (0.761)

0.958 (1.489)


ROI that DID contain a sample 0 0.052 ( 0.101)

0.017 (0.050)

0.058 (0.085)

ROI that DID NOT contain a sample 0 0.026 ( 0.43)

0.015 (0.041)

0.068 (0.101)

Note: The accuracy on identifying a matched or unmatched comparison, and mean frequency and mean duration of observing

responses to ROI (ROI) on two-stimulus trials. Standard deviation from the mean is presented in brackets.


Table 3


Four-stimulus trial data Participant

1 2 3 4

Overall accuracy (%) 75 79.2 87.5 83.3

Accuracy on matched trials (%) 66.7 75 83.3 91.7

Accuracy on unmatched trials (%) 83.3 83.3 91.7 75



10.75 (6.453)

15.208 (8.341)

20.083 (6.743)


ROI that DID contain a sample 0.13 ( 0.166)

0.503 (0.330)

0.991 (0.693)

1.375 (0.556)



1.917 (2.225)

1.167 (2.120)

2.458 (2.553)



0.074 (0.086)

0.065 (0.130)

0.218 (0.268)

Note: The accuracy on identifying a matched or unmatched comparison, and mean frequency and mean duration of observing

responses to ROI (ROI) on four-stimulus trials. Standard deviation from the mean is presented in brackets.

Table 4


Note: Average latency to respond to the comparison in seconds. Standard deviation from the mean is presented in brackets.


86

Table 5

Participant 1 fixations during the delay by trial type and accuracy.

One stimulus Two stimuli Four stimuliMatched Unmatched Matched Unmatched Matched Unmatched

Correct trials 7 (0.212)

2(0.105)

3.5(0.149)

4.727(0.242)

2.444(0.092)

4.111(0.173)

Incorrect trials --- 0(0)

0.5(0.015)

3(0.1)

2.667(0.113)

3.333(0.13)

Participant 2 fixations during the delay by type and accuracy.


Correct trials 2.4(0.128)

3.667(0.227) 7.125

(0.31)

4.818(0.193)

7.333(0.323)

12.3(0.602)

Incorrect trials --- --- 11(0.547)

4(0.16)

6.333(0.28)

25(1.155)




6.667(0.49)

11.7(0.772)

7.846(0.563)

17.182(1.139)

13.273(0.844)

Incorrect trials --- --- 11*(1.03) --- 0*

(0)30*

(1.98)




3.667(0.423)

16.400(1.314)

13.429(1.02)

23(1.633)

16.222(1.054)

Incorrect trials --- --- --- --- --- 20(1.3)


In the previous tables, you have included the abbreviation for the standard deviation in the table. I like how it looks without the abbreviation (it looks much cleaner); however, either way is fine. You just need to make sure you make this consistent across tables.


Note: Mean frequency of observations by trial type. Total mean duration is shown in brackets.

Numbers with an (*) symbol represent a single trial. Dashed lines indicate that there are no trials

of that type. SD vaues are presented in Appendix C.

Table 6

Participant 1 fixations during the comparison by trial type and accuracy.


Correct trials .4(0.04)

0(0)

0(0)

0(0)

0.556(0.024)

0.222(0.011)

Incorrect trials --- 0(0)

0(0)

0(0)

0(0))

.667(0.027)



Correct trials 0(0)

0.333(0.01) 2.125

(0.102)

0.727(0.036)

2.222(0.08)

1(0.045)

Incorrect trials --- --- 1.667(0.038)

0.5(0.025)

2(0.067)

5(0.205)




1.33(0.077)

0.818(0.125)

0.083(0.003)

.455(0.034)

1.546(0.076)

Incorrect trials --- --- 0*(0) --- 1*

(0.03)5*

(0.33)



Correct trials 0(0)

0(0)

1(0.053)

1.167(0.063)

2.333(0.203)

2.11(0.208)

Incorrect trials --- --- --- --- --- 4(0.307)


mean


Note: Mean frequency of observations by trial type. Total mean duration is shown in brackets.

Numbers with a (*) symbol represent a single trial. Dashed lines indicate that there are no trials

of that type. SD values are presented in Appendix C.

Table 7

Two-stimulus trial data Participant

1 2 3 4

Overall accuracy (%) 91.7 83.3 100 100

Overall latency (s) 1.786 (SD 1.636)

1.987 (SD 1.074)

1.451 (SD 0.671)

2.433 (SD 0.767)

Correct (s) 1.382 (SD 0.892)

1.798 (SD 1.033)

1.451 (SD 0.671)

2.433 (SD 0.767)

Incorrect (s) 0.622 (NA)

2.928 (SD 0.970) --- ---



11.5 (SD 5.76)

19.75 (SD 9.056)

11.917 (SD 5.435)


1.5 (SD 1.784)

0.917 (SD 1.443)

4.833 (SD 6.117)



0.527 (SD 0.259)

1.718 (SD 0.844)

0.852 (SD 0.402)


0.061 (SD 0.072)

0.068 (SD 0.119)

0.282 (SD 0.459)



1.75 (SD 2.340)

2.5 (SD 2.431)

2.833 (SD 4.896)

ROI that DID NOT contain a sample 0 (SD 0)

0.073 (SD 0.101)

0.167 (SD 0.389)

0.75 (SD 1.422)



0.417 (SD 0.669)

0.208 (SD 0.173)

0.295 (SD 0.608)

ROI that DID NOT contain a sample 0 (SD 0)

0.013 (SD 0.022)

0.024 (SD 0.065)

0.037 (SD 0.069)

Note: Accuracy for identifying the location of the comparison as an initial sample on two-

stimulus trials. Overall latency, and latency for correct and incorrect trials, along with observing

response data during the delay and comparison are presented as a mean. Standard deviation from

the mean is presented in brackets.



Table 8

Participant

1 2 3 4

Overall accuracy (%) 66.7 83.3 91.7 91.7

Overall latency (s) 3.236 (SD 1.522)

2.454 (SD 1.102)

2.148 (SD 0.961)

4.641 (SD 1.717)

Correct (s) 3.501 (SD 1.488)

2.339 (SD 1.009)

2.179 (SD 1.001)

4.596 (SD 1.793)

Incorrect (s) 2.706 (SD 1.664)

3.028 (SD 1.254)

1.807 * (NA)

5.136 * (NA)



9.917 (SD 6.374)

22.333 (SD 8.424)

17.000 (SD 6.045)



0.525 (SD 0.302)

1.557 (SD 0.722)

1.297 (SD 0.359)



1.718 (SD 1.775)

1.571 (SD 2.023)

2.917 (SD 3.059)



0.062 (SD 0.076)

0.083 (SD 0.11)

0.272 (SD 0.507)

Note: Accuracy for identifying the location of the comparison as an initial sample on four-

stimulus trials. Overall latency, and latency for correct and incorrect trials, along with observing

response data during the delay and comparison presented as mean values. Standard deviation

from the mean is presented in brackets.



91

Table 9

Participant 1 Participant 2 Participant 3 Participant 4 Correct Incorrect Correct Incorrect Correct Incorrect Correct Incorrect

Delay

Two-stimuli 9.9 (0.454)

3 * (0.220)

11.6 (0.523)

11 (0.530)

11.917 (0.852) - 19.75

(1.718) -

Four-stimuli 6.75 (0.333)

6.25 (0.273)

8.9 (0.479)

15 (0.755)

15.818 (1.230)

30 * (2.030)

23.909 (1.660)

5 * (0.420)

Comparison

Two-stimuli 0.182 (0.009)

0 * (0)

1.909 (0.08)

0 (0)

2.833 (0.295) - 2.5

(0.195) -

Four-stimuli 0.25 (0.006)

0 (0)

1.455 (0.555)

4 (0.33)

3 (0.313)

2 * (0.13)

1.636 (0.091)

0 * (0)

Note: Mean frequency of observations by trial type. Total mean duration is shown in brackets. Numbers with an (*) symbol represent

a single trial. Dashed lines indicate that there are no trials of that type. SD values are presented in Appendix C.


mena


92

0

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10

15

20

25

30

35

40

Tota

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Inco

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t

Tota

l

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Inco

rrec

t

Tota

l

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rrec

t

Tota

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t

Participant 1 Participant 2 Participant 3 Participant 4

Perc

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Figure 1. Bar graph representing the percentage of matched trials in which the participant looked

at the regions of interest that presented the correct sample during the comparison slide.


Appendix B

Sample matched one-stimulus trials

湯


Sample unmatched one-stimulus trial

張


Sample matched two-stimulus trial

Sample unmatched two-stimulus trial


Sample matched four-stimulus trial


Sample unmatched four-stimulus trial


Sample two-stimulus location trial


Sample four-stimulus location trial


Documents

The Visuo-Spatial Sketchpad and Eye-Movements · Web viewincluded Mandarin characters, and participants were screened for prior knowledge of Chinese writing systems. The purpose of