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Division of Information Management Engineering User Interface 21 The Modular Organization of the Mind How Can the Human Mind Occur in the Physical Universe? Ch 2. UI Lab . 백 백 백

Division of Information Management Engineering User Interface Laboratory 21 The Modular Organization of the Mind How Can the Human Mind Occur in the Physical

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Page 1: Division of Information Management Engineering User Interface Laboratory 21 The Modular Organization of the Mind How Can the Human Mind Occur in the Physical

Division of Information Management Engineering

User Interface Labora-

tory

21

The Modular Organization of the Mind

How Can the Human Mind Occur

in the Physical Universe?

Ch 2.

UI Lab . 백 지 승

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Function and Structure

Modular Architecture

Driving: Modules in ActionDual Tasking: Modular Parallelism and SerialityMapping Modules Onto the Brain

Overall Conclusions Appendix 2.1: Predicting the BOLD Response

Contents

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Humans and other creatures live in a complex world where multiple simultaneous demands are placed on them

adequateMultiple resource

• Perceptual capable of detecting important information coming via multiple sensory media

• Motor capable of taking appropriate actions and perform it simultaneously

• Central capable of coordinating actions and thoughts to achieve the needs

Function and Structure

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Structural Constraints of the Brain

• What is really interesting is not the mere fact of limitations on the brain’s ability, but the nature of these limitations

• The visual system illustrates the power and limitations of neural information processing - The visual input is being processed in the brain from our entire visual field - Every time we move our foveae to a new location, we are choosing to dedi-cate our most powerful processing resources to what we deem most important

illustrates the push to have related information processing close together - the visual areas is specialized to process a different sort of information about the visual signal - cells that process similar areas of the visual field are placed close together

Function and Structure

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• Parts of the brain are given over to performing related computa-tions

so that it is easier for the necessary neurons to interact

• At a larger scale, different cortical areas that do similar process-ing are often

adjacent

• There is also a clear clumping of areas in the cortex

• Neural computation is localized goes against a longstanding tra-dition to

regard information about a particular function as spread out over the entire brain ⇒ Damage to a specific area results in a specific deficit, but similar information processing is occurring elsewhere and can serve for certain tasks

Function and Structure

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Coordination: The Basal Ganglia

• While different regions of the brain they have to coordinate at least occa-sionally to

achieve a functional system ← tracks of brain fibers connect multiple cortical regions

⇒ basal ganglia

• The basal ganglia are a connected set of subcortical structuresStriatum(caudate+putamen) – perform a pattern-recognition function

• Three key features in the characterization of the basal ganglia loop1. Allows information from disparate regions of the brain to converge

in making a decision2. Requires a great compression of information from what is happen-

ing in these individual regions3. Processing that involves the multisynaptic is necessarily much

slower than processing that can occur in a single brain region

Function and Structure

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ACT-R’s Modules

• Each of modules is capable of massively parallel computation to achieve its objectives

– visual module (process visual field) & declarative module(searching data)• when it comes to communication among the modules → bottle neck ⇒

through buffer

Modular Architecture

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procedural

imaginal

goaldeclara-

tive

visual aural

manual vocal

cen-tral

percep-tual

mo-tor

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ACT-R’s Modules

• Communication among the modules is achieved via a procedural module

(associated with the basal ganglia)• The central procedural module teds to execute a single produc-

tion rule at a time⇒ it becomes the overall central bottleneck in information processing

Before progressing to examples that illustrate the module sys-tem,

it is useful to consider the relationship of this proposal to other ideas in cognitive science

Modular Architecture

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Fodor Modules

1. Domain specificity a module processes only a restricted set of stimuli

2. Mandatory operation when certain input arrived, the modules had to act, and how they acted could not be modified

3. Information encapsulation almost all information processing occurs within individual modules, although modules do offer a narrow band for trading information with other modules

4. Fast operation through information encapsulation, modular processes are the fastest cognitive processes

5. Shallow outputs the outputs of modules as “shallow”

6. Fixed neural architecture

Modular Architecture

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Modules and Capacity Limits

• The basic motivation for a modular structure is to get the best perfor-mance possible given the limitations of brain processing

• Parallel processes are not capacity limited and serial processes are→ approximately the way it works out in ACT-R computations within a module can progress in parallel, can avoid capacity limitations• The hardest limitations occur in the communication between modules• Serial limitation arises from the necessity for all modules to communi-

cate through the production system • The major point of disagreement with EPIC is whether the central produc-

tion system also has a central bottleneck limitation The functional reasons in ACT-R – avoids the problem of multiple rules

making contradictory demands on the same time

Modular Architecture

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Before getting into examples that involve detailed experimental analyses of the behavior of specific modules, it is important to start with an example that illus-trates the functionality of the overall architecture

Driving requires a driver to do many things at once - The most critical task is controlling the vehicle

(lateral control, longitudinal control)

Dario Salvucci has developed a driving model in ACT-R that incorporates the two subtasks of control and monitoring Control - input: keeping track of near/ far points

output: lateral/ longitudinal control parameters calls upon the visual module, the procedural module, the manual module,

an implicit pedal module

Monitoring – selects which lane to encode and whether to encode information in front or behind

calls upon the visual module, the procedural module, and the declarative mod-ule

Driving: Modules in Action

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• Use distribution of eye movements to track shift between the two tasks• Assumes that the eyes follow shifts of attention in order to achieve higher resolu-

tion• The overall correspondence between eye movements predicted by Salvucci’s model

and the data is quite impressive - though eye movements are slow, stochastic and do not provide total tracking

the match between human and model proportion of gazes to different parts of the visual array

Driving: Modules in Action

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Driving: Modules in Action

• The switch between control regions and monitoring regions Control gazes: forward gazes to the same lane Monitoring gazes: all other gazes

• The probability of switching from monitoring to controlling/ from control to monitoring

as a function of time performing that activity

(a) (b)

The difference is a consequence of the need to switch back to control after 0.5 sec The length of time spent on control depends on road conditions and the stability of the

vehicle

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Compares the time to key each digit in a 10 digit numbers when not driving versus when driving

The effect of dialing a cell phone number on two measures of safe driving, lat-eral deviation and speed deviation

Driving: Modules in Action

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There are two types of parallelism, two types of seriality associated with all of the ACT-R modules

Within-Module Parallelism massively parallel computation is happening

Within-Module Seriality the need for communication and coordination poses serial bottlenecks within each module

Between-Module Parallelism computation in one module can proceed in parallel with computation in another module

Between-Module Seriality in many cases one module must wait on another

Dual Tasking: Modular Parallelism and Seriality

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Dual Tasking: Modular Parallelism and Seriality

• The time to perform the aural-vocal task and the time to per-form the visual-manual task• the model reproduces the overall speed increase and the re-duction in the dual-task cost from about 50ms to about 10ms• produces a somewhat larger dual cost in the aural-vocal task and a smaller dual-task cost in the visual-manual task

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Dual Tasking: Modular Parallelism and Seriality

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Localizing Eight Modules1. Visual module2. Aural module3. Manual module4. Vocal module5. Imaginal module6. Declarative module7. Goal module8. Procedural module

Two points need to be made to qualify any simple conclusion of a one-to-one

mapping of function onto structure1. The brain tends to distribute similar but distinguishable processes to differ-

ent regions2. There is no necessary reason why these brain regions should perform only a

single architectural function

Mapping Modules Onto the Brain

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The Experiment

The effects of the four factors(input modality, output modality, transformation, substitution) on the eight regions associated with the modules

Mapping Modules Onto the Brain

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Predicting the BOLD Response

Observed (dotted lines connecting points) BOLD responses and predictions (solid lines) for the eight predefined regions

Mapping Modules Onto the Brain

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How the human mind occur in the physical universe?⇒ the mind partitions itself into specific information-processing func-tions → achieved in relatively localized brain regions where the pro-cessing can be done effectively

The general answer of a modular partition seems the only way to achieve the multipurpose functionality that human need to meet the demands of their world given the structures of their brains

Overall Conclusions

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Function and Structure

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Function and Structure

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Modular Architecture

procedural

Imagi-nal-ac-

tion

goal

retrieval

visualaural

manual vocal

goal

declara-tive

imaginal

imaginal

aural

Aural-lo-cation

vocal

visual

Visual-location

manual

ENVIRONMENT

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