Abnormal brain activity in social reward learning in children with autism spectrum disorder: an fMRI study

Mapping brain functional and structural abnormities in autism spectrum disorder: moving toward precision treatment

Autism spectrum disorder (ASD) is a formidable challenge for psychiatry and neuroscience because of its high prevalence, lifelong nature, complexity, and substantial heterogeneity. A major goal of neuroimaging studies of ASD is to understand the neurobiological underpinnings of this disorder from multi-dimensional and multi-level perspectives, by investigating how brain anatomy, function, and connectivity are altered in ASD, and how they vary across the population. However, ongoing debate exists within those studies, and neuroimaging findings in ASD are often contradictory. Over the past decade, we have dedicated to delineate a comprehensive and consistent mapping of the abnormal structure and function of the autistic brain, and this review synthesizes the findings across our studies reaching a consensus that the "social brain" are the most affected regions in the autistic brain at different levels and modalities. We suggest that the social brain network can serve as a plausible biomarker and potential target for effective intervention in individuals with ASD.

Mapping the Heterogeneous Brain Structural Phenotype of Autism Spectrum Disorder Using the Normative Model

BACKGROUND

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder characterized by substantial clinical and biological heterogeneity. Quantitative and individualized metrics for delineating the heterogeneity of brain structure in ASD are still lacking. Likewise, the extent to which brain structural metrics of ASD deviate from typical development (TD) and whether deviations can be used for parsing brain structural phenotypes of ASD is unclear.

METHODS

T1-weighted magnetic resonance imaging data from the Autism Brain Imaging Data Exchange (ABIDE) II (n_TD = 564) were used to generate a normative model to map brain structure deviations of ABIDE I subjects (n_TD = 560, n_ASD = 496). Voxel-based morphometry was used to compute gray matter volume. Non-negative matrix factorization was employed to decompose the gray matter matrix into 6 factors and weights. These weights were used for normative modeling to estimate the factor deviations. Then, clustering analysis was used to identify ASD subtypes.

RESULTS

Compared with TD, ASD showed increased weights and deviations in 5 factors. Three subtypes with distinct neuroanatomical deviation patterns were identified. ASD subtype 1 and subtype 3 showed positive deviations, whereas ASD subtype 2 showed negative deviations. Distinct clinical manifestations in social communication deficits were identified among the three subtypes.

CONCLUSIONS

Our findings suggest that individuals with ASD have heterogeneous deviation patterns in brain structure. The results highlight the need to test for subtypes in neuroimaging studies of ASD. This study also presents a framework for understanding neuroanatomical heterogeneity in this increasingly prevalent neurodevelopmental disorder.

Absence of covert face valuation in Autism

Autism is a neurodevelopmental condition defined on clinical criteria related to diminished social reciprocity and stereotyped behavior. An influential view explains autism as a social motivation disorder characterized by less attention paid to the social environment and less pleasure experienced with social rewards. However, experimental attempts to validate this theory, by testing the impact of social reward on behavioral choice and brain activity, has yielded mixed results, possibly due to variations in how explicit instructions were about task goals. Here, we specified the putative motivation deficit as an absence of spontaneous valuation in the social domain, unexplained by inattention and correctible by explicit instruction. Since such deficit cannot be assessed with behavioral measures, we used functional neuroimaging (fMRI) to readout covert subjective values, assigned to social and nonsocial stimuli (faces and objects), either explicitly asked to participants (during a likeability judgment task) or not (during age or size estimation tasks). Value-related neural activity observed for objects, or for faces under explicit instructions, was very similar in autistic and control participants, with an activation peak in the ventromedial prefrontal cortex (vmPFC), known as a key node of the brain valuation system. The only difference observed in autistic participants was an absence of the spontaneous valuation normally triggered by faces, even when they were attended for age estimation. Our findings, therefore, suggest that in autism, social stimuli might fail to trigger the automatic activation of the brain valuation system.

The functional neural architecture of dysfunctional reward processing in autism

Functional imaging studies have found differential neural activation patterns during reward-paradigms in patients with autism spectrum disorder (ASD) compared to neurotypical controls. However, publications report conflicting results on the directionality and location of these aberrant activations. We here quantitatively summarized relevant fMRI papers in the field using the anatomical likelihood estimation (ALE) algorithm. Patients with ASD consistently showed hypoactivations in the striatum across studies, mainly in the right putamen and accumbens. These regions are functionally involved in the processing of rewards and are enrolled in extensive neural networks involving limbic, cortical, thalamic and mesencephalic regions. The striatal hypo-activations found in our ALE meta-analysis, which pooled over contrasts derived from the included studies on reward-processing in ASD, highlight the role of the striatum as a key neural correlate of impaired reward processing in autism. These changes were present for studies using social and non-social stimuli alike. The involvement of these regions in extensive networks associated with the processing of both positive and negative emotion alike might hint at broader impairments of emotion processing in the disorder.

Gray matter abnormalities follow non-random patterns of co-alteration in autism: Meta-connectomic evidence

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by atypical brain anatomy and connectivity. Graph-theoretical methods have mainly been applied to detect altered patterns of white matter tracts and functional brain activation in individuals with ASD. The network topology of gray matter (GM) abnormalities in ASD remains relatively unexplored.

METHODS

An innovative meta-connectomic analysis on voxel-based morphometry data (45 experiments, 1,786 subjects with ASD) was performed in order to investigate whether GM variations can develop in a distinct pattern of co-alteration across the brain. This pattern was then compared with normative profiles of structural and genetic co-expression maps. Graph measures of centrality and clustering were also applied to identify brain areas with the highest topological hierarchy and core sub-graph components within the co-alteration network observed in ASD.

RESULTS

Individuals with ASD exhibit a distinctive and topologically defined pattern of GM co-alteration that moderately follows the structural connectivity constraints. This was not observed with respect to the pattern of genetic co-expression. Hub regions of the co-alteration network were mainly left-lateralized, encompassing the precuneus, ventral anterior cingulate, and middle occipital gyrus. Regions of the default mode network appear to be central in the topology of co-alterations.

CONCLUSION

These findings shed new light on the pathobiology of ASD, suggesting a network-level dysfunction among spatially distributed GM regions. At the same time, this study supports pathoconnectomics as an insightful approach to better understand neuropsychiatric disorders.

A simultaneous [11C]raclopride positron emission tomography and functional magnetic resonance imaging investigation of striatal dopamine binding in autism

The social motivation hypothesis of autism posits that autism spectrum disorder (ASD) is characterized by impaired motivation to seek out social experience early in life that interferes with the development of social functioning. This framework suggests that impaired mesolimbic dopamine function underlies compromised responses to social rewards in ASD. Although this hypothesis is supported by functional magnetic resonance imaging (fMRI) studies, no molecular imaging study has evaluated striatal dopamine functioning in response to rewards in ASD. Here, we examined striatal functioning during monetary incentive processing in ASD and controls using simultaneous positron emission tomography (PET) and fMRI. Using a bolus + infusion protocol with the D2/D3 dopamine receptor antagonist [¹¹C]raclopride, voxel-wise binding potential (BP_ND) was compared between groups (controls = 12, ASD = 10) in the striatum. Striatal clusters showing significant between-group BP_ND differences were used as seeds in whole-brain fMRI general functional connectivity analyses. Relative to controls, the ASD group demonstrated decreased phasic dopamine release to incentives in the bilateral putamen and left caudate, as well as increased functional connectivity between a PET-derived right putamen seed and the precuneus and insula. Within the ASD group, decreased phasic dopamine release in the putamen was related to poorer theory-of-mind skills. Our findings that ASD is characterized by impaired striatal phasic dopamine release to incentives provide support for the social motivation hypothesis of autism. PET-fMRI may be a suitable tool to evaluate novel ASD therapeutics targeting the striatal dopamine system.

A Systematic Review of the Positive Valence System in Autism Spectrum Disorder

This review synthesized current literature of behavioral and cognitive studies targeting reward processing in autism spectrum disorder (ASD). The National Institute of Mental Health's Research Domain Criteria (RDoC) Positive Valence System (PVS) domain was used as an overarching framework. The objectives were to determine which component operations of reward processing may be atypical in ASD and consequently postulate a heuristic model of reward processing in ASD that could be evaluated with future research. 34 studies were identified from the Embase, PubMed, PsycINFO, and Web of Science databases and included in the review using guidelines from the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (also known as PRISMA guidelines). The extant literature suggested potential relationships between social symptoms of ASD and PVS sub-constructs of reward anticipation, probabilistic and reinforcement learning, reward prediction error, reward (probability), delay, and effort as well as between restricted and repetitive behaviors and interests (RRBIs) and PVS-sub constructs of initial response to reward, reward anticipation, reward (probability), delay, and effort. However, these findings are limited by a sparse and mixed literature for some sub-constructs. We put forward a developmentally informed heuristic model that posits how these component reward processes may be implicated in early ASD behaviors as well as later emerging and more intransigent symptoms. Future research is needed to comprehensively evaluate the proposed model.

Resting and Functional Pupil Response Metrics Indicate Features of Reward Sensitivity and ASD in Children

The current study examined the relationship between quantitative measures of reward and punishment sensitivity, features of autism spectrum disorder (ASD), and resting and functional pupil response metrics across a clinically heterogeneous sample. Scores on a parent-report measure of punishment and reward sensitivity were correlated with ASD features. We also assessed whether pupil measurements could be used as a physiologic correlate of reward sensitivity and predictor of ASD diagnosis. In a logistic regression model, pupil dilation metrics, sex, and IQ, correctly classified 86.3% of participants as having an ASD diagnosis versus not. This research highlights individual differences of reward sensitivity associated with ASD features. Results support the use of pupil metrics and other patient-level variables as predictors of ASD diagnostic status.

Neural responsivity to social rewards in autistic female youth

Autism is hypothesized to be in part driven by a reduced sensitivity to the inherently rewarding nature of social stimuli. Previous neuroimaging studies have indicated that autistic males do indeed display reduced neural activity to social rewards, but it is unknown whether this finding extends to autistic females, particularly as behavioral evidence suggests that affected females may not exhibit the same reduction in social motivation as their male peers. We therefore used functional magnetic resonance imaging to examine social reward processing during an instrumental implicit learning task in 154 children and adolescents (ages 8-17): 39 autistic girls, 43 autistic boys, 33 typically developing girls, and 39 typically developing boys. We found that autistic girls displayed increased activity to socially rewarding stimuli, including greater activity in the nucleus accumbens relative to autistic boys, as well as greater activity in lateral frontal cortices and the anterior insula compared with typically developing girls. These results demonstrate for the first time that autistic girls do not exhibit the same reduction in activity within social reward systems as autistic boys. Instead, autistic girls display increased neural activation to such stimuli in areas related to reward processing and salience detection. Our findings indicate that a reduced sensitivity to social rewards, as assessed with a rewarded instrumental implicit learning task, does not generalize to affected female youth and highlight the importance of studying potential sex differences in autism to improve our understanding of the condition and its heterogeneity.

Neural Mechanisms of Social and Nonsocial Reward Prediction Errors in Adolescents with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is characterized by impaired predictive abilities; however, the neural mechanisms subsuming reward prediction errors in ASD are poorly understood. In the current study, we investigated neural responses during social and nonsocial reward prediction errors in 22 adolescents with ASD (ages 12-17) and 20 typically developing control adolescents (ages 12-18). Participants performed a reward prediction error task using both social (i.e., faces) and nonsocial (i.e., objects) rewards during a functional magnetic resonance imaging scan. Reward prediction errors were defined in two ways: (a) the signed prediction error, the difference between the experienced and expected reward; and (b) the thresholded unsigned prediction error, the difference between expected and unexpected outcomes regardless of magnitude. During social reward prediction errors, the ASD group demonstrated the following differences relative to the TD group: (a) signed prediction error: decreased activation in the right precentral gyrus and increased activation in the right frontal pole; and (b) thresholded unsigned prediction error: increased activation in the right anterior cingulate gyrus and bilateral precentral gyrus. Groups did not differ in brain activation during nonsocial reward prediction errors. Within the ASD group, exploratory analyses revealed that reaction times and social-communication impairments were related to precentral gyrus activation during social prediction errors. These findings elucidate the neural mechanisms of social reward prediction errors in ASD and suggest that ASD is characterized by greater neural atypicalities during social, relative to nonsocial, reward prediction errors in ASD. Autism Res 2020, 13: 715-728. © 2020 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: We used brain imaging to evaluate differences in brain activation in adolescents with autism while they performed tasks that involved learning about social and nonsocial information. We found no differences in brain responses during the nonsocial condition, but differences during the social condition of the learning task. This study provides evidence that autism may involve different patterns of brain activation when learning about social information.

Neural Mechanisms of Reward Prediction Error in Autism Spectrum Disorder

Few studies have explored neural mechanisms of reward learning in ASD despite evidence of behavioral impairments of predictive abilities in ASD. To investigate the neural correlates of reward prediction errors in ASD, 16 adults with ASD and 14 typically developing controls performed a prediction error task during fMRI scanning. Results revealed greater activation in the ASD group in the left paracingulate gyrus during signed prediction errors and the left insula and right frontal pole during thresholded unsigned prediction errors. Findings support atypical neural processing of reward prediction errors in ASD in frontostriatal regions critical for prediction coding and reward learning. Results provide a neural basis for impairments in reward learning that may contribute to traits common in ASD (e.g., intolerance of unpredictability).

A potential mechanistic role for neuroinflammation in reward processing impairments in autism spectrum disorder

Accumulating evidence suggests that autism spectrum disorder (ASD) may be conceptualized within a framework of reward processing impairments. The Social Motivation Theory of Autism posits that reduced motivation to interact with people and decreased pleasure derived from social interactions may derail typical social development and contribute to the emergence of core social communication deficits in ASD. Neuroinflammation may disrupt the development of mesolimbic dopaminergic systems that are critical for optimal functioning of social reward processing systems. This neuroinflammation-induced disturbance of mesolimbic dopaminergic functioning has been substantiated using maternal immune activation rodent models whose offspring show aberrant dopaminergic corticostriatal function, as well as behavioral characteristics of ASD model systems. Preclinical findings are in turn supported by clinical evidence of increased mesolimbic neuroinflammatory responses in individuals with ASD. This review summarizes evidence for reward processing deficits and neuroinflammatory impairments in ASD and examines how immune inflammatory dysregulation may impair the development of dopaminergic mesolimbic circuitry in ASD. Finally, future research directions examining neuroinflammatory effects on reward processing in ASD are proposed.

Evaluation of the Social Motivation Hypothesis of Autism: A Systematic Review and Meta-analysis

Importance

The social motivation hypothesis posits that individuals with autism spectrum disorder (ASD) find social stimuli less rewarding than do people with neurotypical activity. However, functional magnetic resonance imaging (fMRI) studies of reward processing have yielded mixed results.

Objectives

To examine whether individuals with ASD process rewarding stimuli differently than typically developing individuals (controls), whether differences are limited to social rewards, and whether contradictory findings in the literature might be due to sample characteristics.

Data Sources

Articles were identified in PubMed, Embase, and PsycINFO from database inception until June 1, 2017. Functional MRI data from these articles were provided by most authors.

Study Selection

Publications were included that provided brain activation contrasts between a sample with ASD and controls on a reward task, determined by multiple reviewer consensus.

Data Extraction and Synthesis

When fMRI data were not provided by authors, multiple reviewers extracted peak coordinates and effect sizes from articles to recreate statistical maps using seed-based d mapping software. Random-effects meta-analyses of responses to social, nonsocial, and restricted interest stimuli, as well as all of these domains together, were performed. Secondary analyses included meta-analyses of wanting and liking, meta-regression with age, and correlations with ASD severity. All procedures were conducted in accordance with Meta-analysis of Observational Studies in Epidemiology guidelines.

Main Outcomes and Measures

Brain activation differences between groups with ASD and typically developing controls while processing rewards. All analyses except the domain-general meta-analysis were planned before data collection.

Results

The meta-analysis included 13 studies (30 total fMRI contrasts) from 259 individuals with ASD and 246 controls. Autism spectrum disorder was associated with aberrant processing of both social and nonsocial rewards in striatal regions and increased activation in response to restricted interests (social reward, caudate cluster: d = -0.25 [95% CI, -0.41 to -0.08]; nonsocial reward, caudate and anterior cingulate cluster: d = -0.22 [95% CI, -0.42 to -0.02]; restricted interests, caudate and nucleus accumbens cluster: d = 0.42 [95% CI, 0.07 to 0.78]).

Conclusions and Relevance

Individuals with ASD show atypical processing of social and nonsocial rewards. Findings support a broader interpretation of the social motivation hypothesis of ASD whereby general atypical reward processing encompasses social reward, nonsocial reward, and perhaps restricted interests. This meta-analysis also suggests that prior mixed results could be driven by sample age differences, warranting further study of the developmental trajectory for reward processing in ASD.

The Diagnosis of Autism Spectrum Disorder Based on the Random Neural Network Cluster

As the autism spectrum disorder (ASD) is highly heritable, pervasive and prevalent, the clinical diagnosis of ASD is vital. In the existing literature, a single neural network (NN) is generally used to classify ASD patients from typical controls (TC) based on functional MRI data and the accuracy is not very high. Thus, the new method named as the random NN cluster, which consists of multiple NNs was proposed to classify ASD patients and TC in this article. Fifty ASD patients and 42 TC were selected from autism brain imaging data exchange (ABIDE) database. First, five different NNs were applied to build five types of random NN clusters. Second, the accuracies of the five types of random NN clusters were compared to select the highest one. The random Elman NN cluster had the highest accuracy, thus Elman NN was selected as the best base classifier. Then, we used the significant features between ASD patients and TC to find out abnormal brain regions which include the supplementary motor area, the median cingulate and paracingulate gyri, the fusiform gyrus (FG) and the insula (INS). The proposed method provides a new perspective to improve classification performance and it is meaningful for the diagnosis of ASD.

Both Hypo-Connectivity and Hyper-Connectivity of the Insular Subregions Associated With Severity in Children With Autism Spectrum Disorders

Some studies identified hypo-connectivity, while others showed hyper-connectivity of the insula in the autism spectrum disorders (ASD). These contradictory findings leave open the question of whether and to what extent functional connectivity of the insula is altered and how functional connectivity of the insula is associated with the severity of ASD. A newly emerging insular atlas that comprises multiple functionally differentiated subregions provides a new framework to interpret the functional significance of insular findings and uncover the mechanisms underlying the severity of ASD. Using the new insular atlas, the present study aimed to investigate the distinct functional connectivity of the insular subregions and their associations with ASD severity in a cohort of 49 children with ASD and 33 typically developing (TD) subjects. We found that compared with TD group, the ASD group showed different connectivity patterns in the left ventral agranular insula, right ventral dysgranular and granular insula, and dorsal dysgranular insula, characterized by significant hyper-connectivity and/or hypo-connectivity with special brain regions. Furthermore, both the hypo-connectivity and hyper-connectivity patterns of the insular subregions were significantly associated with the severity of ASD symptoms. Our research demonstrated distinct functional connectivity patterns of the insular subregions and emphasized the importance of the subdivisions within the insula to the potential impact of functional difference in children with ASD. Moreover, these results might help us to better understand the mechanisms underlying the symptoms in children with ASD and might elucidate potential biomarkers for clinical applications.

μ opioid receptor, social behaviour and autism spectrum disorder: reward matters

The endogenous opioid system is well known to relieve pain and underpin the rewarding properties of most drugs of abuse. Among opioid receptors, the μ receptor mediates most of the analgesic and rewarding properties of opioids. Based on striking similarities between social distress, physical pain and opiate withdrawal, μ receptors have been proposed to play a critical role in modulating social behaviour in humans and animals. This review summarizes experimental data demonstrating such role and proposes a novel model, the μ opioid receptor balance model, to account for the contribution of μ receptors to the subtle regulation of social behaviour. Interestingly, μ receptor null mice show behavioural deficits similar to those observed in patients with autism spectrum disorder (ASD), including severe impairment in social interactions. Therefore, after a brief summary of recent evidence for blunted (social) reward processes in subjects with ASD, we review here arguments for altered μ receptor function in this pathology. This article is part of a themed section on Emerging Areas of Opioid Pharmacology. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v175.14/issuetoc.

Characteristics of Brains in Autism Spectrum Disorder: Structure, Function and Connectivity across the Lifespan

Autism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by impaired social communication and restricted and repetitive behaviors (RRBs). Over the past decade, neuroimaging studies have provided considerable insights underlying neurobiological mechanisms of ASD. In this review, we introduce recent findings from brain imaging studies to characterize the brains of ASD across the human lifespan. Results of structural Magnetic Resonance Imaging (MRI) studies dealing with total brain volume, regional brain structure and cortical area are summarized. Using task-based functional MRI (fMRI), many studies have shown dysfunctional activation in critical areas of social communication and RRBs. We also describe several data to show abnormal connectivity in the ASD brains. Finally, we suggest the possible strategies to study ASD brains in the future.