Functional Connectivity in an fMRI Working Memory Task in High-functioning Autism

(Koshino et al., 2005)

Computational Modeling of Intelli-gence

11.05.27.(Fri)Summarized by Joon Shik Kim

Abstract

• fMRI results suggested that the normal controls might use verbal codes to perform a n-back task, while the adults with autism might use visual codes.

• The autism group also had more activation than the control group in the posterior regions includ-ing inferior temporal and occipital regions.

• The temporal profile of the activity in the pre-frontal regions was more correlated with the left parietal regions for the control group, whereas it was more correlated with the right parietal re-gions for the autism group.

Introduction

• N-back task is performed well by both high-functioning individuals with autism and controls (Williams et al.).

• Some studies have reported that individuals with autism show differences between verbal and visuospa-tial information processing in intelligence scales, such as WAIS, WISC, Block Design, and Object Assembly (Frith, 1989; Shah and Frith, 1983, 1993).

• People with autism tend to process low-level visual features (details) but may not be able to integrate fea-tures into global structures reflecting the hierarchical nature of the environmental stimuli; therefore, it is dif-ficult for them to find the central meaning of the envi-ronmental stimuli (Hill and Frith, 2003).

Methods (1/4)

• 14 high-functioning individuals with autism (13 males and 1 female) and 14 healthy normal control participants (13 males and 1 female).

• Age was matched. Autism group mean: 25.7 yr and control group mean: 29.8 yr

• Experimental paradigm: n-back task with three experimental conditions: 0-back, 1-back, and 2-back.

Methods (2/4)

Methods (3/4)

• Functional connectivity: a correlation or synchronization between the time courses of activation of two regions.

• Fisher transformation:–

– z is approximately normally distributed with standard error , where N is the sample size

1 1ln2 1

rz

r

, where r is a Pearson’ correlation coef-ficient.

1

3N

Methods (4/4)

• Exploratory factor analysis (principal component factor analysis) was per-formed (McLaughlin et al., 1992; Pe-terson et al., 1999)

• Our logic behind the factor analysis was that each factor would represent a large-scale network among brain regions corresponding to some func-tions (Musulam, 1990, 1998).

Results (1/4)

• The performance between the con-trol and autism groups was very simi-lar to each other and resulted in no significant group difference in both response time (RT) and error rate.

• Sum of signal percentage change

Results (2/4)

• t maps that were transformed to a standardized space and averaged across participants for the 2-back condition compared to the resting baseline.

Autism group showed much less activation than the control group in the left hemisphere.

Results (3/4)

Factor analysis result

Results (4/4)

Connectivity

Discussion (1/3)

• Control group might have used the verbal strategy in which they en-coded each stimulus letter verbally to facilitate memory.

• Control group showed more activa-tion in the left inferior parietal re-gions because they used phonologi-cal codes to encode the stimulus let-ter.

Discussion (2/3)

• Autism group might have used a more nonverbal, visual-graphical approach in which they coded the shapes of the alphabet letters without naming them.

• The autism group showed more acti-vation in the posterior regions, includ-ing the left inferior temporal, left temporal, right temporal, and left in-ferior extrastriate.

Discussion (3/3)

• This pattern might be related to the information processing style of the autism participants, suggesting that they relied on analysis of lower level visual features.