Is He Being Bad? Social and Language Brain Networks during Social Judgment in Children with Autism

Abstract

Individuals with autism often violate social rules and have lower accuracy in identifying and explaining inappropriate social behavior. Twelve children with autism (AD) and thirteen children with typical development (TD) participated in this fMRI study of the neurofunctional basis of social judgment. Participants indicated in which of two pictures a boy was being bad (Social condition) or which of two pictures was outdoors (Physical condition). In the within-group Social–Physical comparison, TD children used components of mentalizing and language networks [bilateral inferior frontal gyrus (IFG), bilateral medial prefrontal cortex (mPFC), and bilateral posterior superior temporal sulcus (pSTS)], whereas AD children used a network that was primarily right IFG and bilateral pSTS, suggesting reduced use of social and language networks during this social judgment task. A direct group comparison on the Social–Physical contrast showed that the TD group had greater mPFC, bilateral IFG, and left superior temporal pole activity than the AD group. No regions were more active in the AD group than in the group with TD in this comparison. Both groups successfully performed the task, which required minimal language. The groups also performed similarly on eyetracking measures, indicating that the activation results probably reflect the use of a more basic strategy by the autism group rather than performance disparities. Even though language was unnecessary, the children with TD recruited language areas during the social task, suggesting automatic encoding of their knowledge into language; however, this was not the case for the children with autism. These findings support behavioral research indicating that, whereas children with autism may recognize socially inappropriate behavior, they have difficulty using spoken language to explain why it is inappropriate. The fMRI results indicate that AD children may not automatically use language to encode their social understanding, making expression and generalization of this knowledge more difficult.

Divergent roles of autistic and alexithymic traits in utilitarian moral judgments in adults with autism

“…For example, instead of retrieving semantic representations (for personal dilemma 45 , it can be "ME HURT YOU = WRONG"), they can rely on visual imagery of the same rule, which has indeed been shown to support non-utilitarian moral judgments in healthy individuals 121 . Prior studies support this line of reasoning, e.g., a previous neuroimaging study 122 showed that typically developing children automatically encode their social knowledge into language while assessing behaviour of others in paradigms with minimum verbal requirements, but no such pattern is found in autistic children. Anecdotal reports from autistic individuals also note that they primarily rely on non-verbal thoughts 123 (as one autistic noted 122 : "I think in pictures.…”

The clinical utility of social information processing theory in assessing and treating offenders with autism spectrum disorder

“…Thus, a simpler methodology is required, which would demand a lower level of language abilities and have less of a cognitive load, while still being a valid and reliable assessment of moral reasoning in ASD (Shulman et al, 2012). Carter et al (2012) compared children with autism (ASD) and children with typical development (TD) on the neurofunctional basis of social judgment in a fMRI study. Participants indicated in which of two pictures a boy was being bad (Social condition) or which of two pictures was outdoors (Physical condition).…”

Hypo- and hyper-connectivity in default mode network related to social impairment in tweens with autism spectrum disorder

“…We chose to decompose data into 20 components, because this is a common degree of clustering/splitting when applying ICA to rs-fMRI data (Smith et al, 2009). Selection of the components was based on their relation with social communication, resulting in the DMN (Li et al, 2014), the salience network (Toyomaki, & Murohashi, 2013), the auditory network (Russo, 2008) and the language network (Carter et al, 2012). When several components represented the same networks, the component with the highest correlation coefficient with the template was selected for further analysis.…”

“…Temporally correlated signal variations of different brain regions are thought to correspond to distinct functional resting-state networks (Beckmann, DeLuca, Devlin, & Smith, 2005). For few resting-state networks, a relation with social communication has been already demonstrated, among which the auditory network (Russo, 2008), the language network (Carter, Williams, Minshew, & Lehman, 2012), the salience network (Toyomaki & Murohashi, 2013) and the default mode network (DMN) (Li, Mai & Liu, 2014;Mars et al, 2012). Since most evidence is found on the role of the DMN in social communication, this network will be our main focus.…”