Biology subjects

Simon Baron-Cohen

Publications and source records attributed to Simon Baron-Cohen.

4 recordsLinked to original sources

bioRxiv2016

Oxytocin enhances intrinsic corticostriatal functional connectivity in women

BackgroundOxytocin may influence various human behaviors and the connectivity across subcortical and cortical networks. Previous oxytocin studies are male-biased and often constrained by task-based inferences. Here we investigate the impact of oxytocin on resting state connectivity between subcortical and cortical networks women.\n\nMethodsWe collected resting state fMRI data on 26 typically-developing women following intranasal oxytocin administration using a double-blind placebo-controlled crossover design. Independent components analysis (ICA) was applied to examine connectivity between networks. An independent analysis of oxytocin receptor (OXTR) gene expression in human subcortical and cortical areas was carried out to determine plausibility of direct oxytocin effects on OXTR.\n\nResultsIn women, OXTR was highly expressed in striatal and other subcortical regions, but showed modest expression in cortical areas. Oxytocin increased connectivity between corticostriatal circuitry typically involved in reward, emotion, social-communication, language, and pain processing. This effect was 1.39 standard deviations above the null effect of no difference between oxytocin and placebo. This oxytocin-related effect on corticostriatal connectivity covaried with autistic traits, such that oxytocin-related increase in connectivity was stronger in individuals with higher autistic traits.\n\nDiscussionOxytocin strengthens corticostriatal connectivity in women, particularly with cortical networks that are involved in social-communicative, motivational, and affective processes. This effect may be important for future work on neurological and psychiatric conditions (e.g., autism, chronic pain), particularly through highlighting how oxytocin may operate differently for subsets of individuals.\n\nSignificance statementThis is the first study to examine how oxytocin affects corticostriatal connectivity in humans, and specifically in women. This is important given oxytocin could impact neural circuitry differently in males and females. Here, we show that oxytocin increases connectivity between corticostriatal circuitry involved in a number of social-communicative, motivational, and affective processes that are implicated in certain neuropsychiatric conditions (e.g., autism). This effect is bolstered by independent evidence that oxytocin receptor gene expression is high in striatal regions and modest in cortical areas. These results may have potential implications for personalized treatment, as oxytocin-related effects on connectivity may vary substantially between individuals.

Neuroscience↗

bioRxiv2016

Genome-wide analyses of empathy and systemizing: heritability and correlates with sex, education, and psychiatric risk

Empathy is the ability to recognize and respond to the emotional states of other individuals. It is an important psychological process that facilitates navigating social interactions and maintaining relationships, which are important for wellbeing. Several psychological studies have identified difficulties in both self-report and performance-based measures of empathy in a range of psychiatric conditions. To date, no study has systematically investigated the genetic architecture of empathy using genome-wide association studies (GWAS). Here we report the results of the largest GWAS of empathy to date using a well-validated self-report measure of empathy, the Empathy Quotient (EQ), in 46,861 research participants from 23andMe, Inc. We identify 11 suggestive loci (P < 1x10-6), though none were significant at P < 2.5x10-8 after correcting for multiple testing. The most significant SNP was identified in the non-stratified analysis (rs4882760; P = 4.29x10-8), and is an intronic SNP in TMEM132C. The EQ had a modest but significant narrow-sense heritability (0.11{+/-}0.014; P = 1.7x10-14). As predicted, based on earlier work, we confirmed a significant female-advantage on the EQ (P < 2x10-16 Cohens d = 0.65). We identified similar SNP heritability and high genetic correlation between the sexes. Also, as predicted, we identified a significant negative genetic correlation between autism and the EQ (rg = -0.27{+/-}0.07, P = 1.63x10-4). We also identified a significant positive genetic correlation between the EQ and risk for schizophrenia (rg = 0.19{+/-}0.04; P= 1.36x10-5), risk for anorexia nervosa (rg = 0.32{+/-}0.09; P = 6x10-4), and extraversion (rg = 0.45{+/-}0.08; 5.7x10-8). This is the first GWAS of self-reported empathy. The results suggest that the genetic variations associated with empathy also play a role in psychiatric conditions and psychological traits.

Genomics↗

bioRxiv2015

Unsupervised data-driven stratification of mentalizing heterogeneity in autism

Individuals affected by autism spectrum conditions (ASC) are considerably heterogeneous. Novel approaches are needed to parse this heterogeneity to enhance precision in clinical and translational research. Applying a clustering approach taken from genomics and systems biology on two large independent cognitive datasets of adults with and without ASC (n=715; n=251), we find replicable evidence for 5 discrete ASC subgroups that are highly differentiated in item-level performance on an explicit mentalizing task tapping ability to read complex emotion and mental states from the eye region of the face (Reading the Mind in the Eyes Test; RMET). Three subgroups comprising 42-65% of ASC adults show evidence for large impairments (Cohens d = -1.03 to -11.21), while other subgroups are effectively unimpaired. These findings delineate robust natural subdivisions within the ASC population that may allow for more individualized inferences and accelerate research towards precision medicine goals.

Animal Behavior and Cognition↗

bioRxiv2015

Improving effect size estimation and statistical power with multi-echo fMRI and its impact on understanding the neural systems supporting mentalizing

Functional magnetic resonance imaging (fMRI) research is routinely criticized for being statistically underpowered due to characteristically small sample sizes and much larger sample sizes are being increasingly recommended. Additionally, various sources of artifact inherent in fMRI data can have detrimental impact on effect size estimates and statistical power. Here we show how specific removal of non-BOLD artifacts can improve effect size estimation and statistical power in task-fMRI contexts, with particular application to the social-cognitive domain of mentalizing/theory of mind. Non-BOLD variability identification and removal is achieved in a biophysical and statistically principled manner by combining multi-echo fMRI acquisition and independent components analysis (ME-ICA). Group-level effect size estimates on two different mentalizing tasks were enhanced by ME-ICA at a median rate of 24% in regions canonically associated with mentalizing, while much more substantial boosts (40-149%) were observed in non-canonical cerebellar areas. This effect size boosting is primarily a consequence of reduction of non-BOLD noise at the subject-level, which then translates into consequent reductions in between-subject variance at the group-level. Power simulations demonstrate that enhanced effect size enables highly-powered studies at traditional sample sizes. Cerebellar effects observed after applying ME-ICA may be unobservable with conventional imaging at traditional sample sizes. Thus, ME-ICA allows for principled design-agnostic non-BOLD artifact removal that can substantially improve effect size estimates and statistical power in task-fMRI contexts. ME-ICA could help issues regarding statistical power and non-BOLD noise and enable potential for novel discovery of aspects of brain organization that are currently under-appreciated and not well understood.

Neuroscience↗