Shared and Specific Neural Correlates of Attention Deficit Hyperactivity Disorder and Autism Spectrum Disorder: A Meta-Analysis of 243 Task-Based Functional MRI Studies

OBJECTIVE

To investigate shared and specific neural correlates of cognitive functions in attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD), the authors performed a comprehensive meta-analysis and considered a balanced set of neuropsychological tasks across the two disorders.

METHODS

A broad set of electronic databases was searched up to December 4, 2022, for task-based functional MRI studies investigating differences between individuals with ADHD or ASD and typically developing control subjects. Spatial coordinates of brain loci differing significantly between case and control subjects were extracted. To avoid potential diagnosis-driven selection bias of cognitive tasks, the tasks were grouped according to the Research Domain Criteria framework, and stratified sampling was used to match cognitive component profiles. Activation likelihood estimation was used for the meta-analysis.

RESULTS

After screening 20,756 potentially relevant references, a meta-analysis of 243 studies was performed, which included 3,084 participants with ADHD (676 females), 2,654 participants with ASD (292 females), and 6,795 control subjects (1,909 females). ASD and ADHD showed shared greater activations in the lingual and rectal gyri and shared lower activations in regions including the middle frontal gyrus, the parahippocampal gyrus, and the insula. By contrast, there were ASD-specific greater and lower activations in regions including the left middle temporal gyrus and the left middle frontal gyrus, respectively, and ADHD-specific greater and lower activations in the amygdala and the global pallidus, respectively.

CONCLUSIONS

Although ASD and ADHD showed both shared and disorder-specific standardized neural activations, disorder-specific activations were more prominent than shared ones. Functional brain differences between ADHD and ASD are more likely to reflect diagnosis-related pathophysiology than bias from the selection of specific neuropsychological tasks.

Meta-analysis of structural integrity of white matter and functional connectivity in developmental stuttering

Developmental stuttering is a speech disfluency disorder characterized by repetitions, prolongations, and blocks of speech. While a number of neuroimaging studies have identified alterations in localized brain activation during speaking in persons with stuttering (PWS), it is unclear whether neuroimaging evidence converges on alterations in structural integrity of white matter and functional connectivity (FC) among multiple regions involved in supporting fluent speech. In the present study, we conducted coordinate-based meta-analyses according to the PRISMA guidelines for available publications that studied fractional anisotropy (FA) using tract-based spatial statistics (TBSS) for structural integrity and the seed-based voxel-wise FC analyses. The search retrieved 11 publications for the TBSS FA studies, 29 seed-based FC datasets from 6 publications for the resting-state, and 29 datasets from 6 publications for the task-based studies. The meta-analysis of TBSS FA revealed that PWS exhibited FA reductions in the middle and posterior segments of the left superior longitudinal fasciculus. Furthermore, the analysis of resting-state FC demonstrated that PWS had reduced FC in the right supplementary motor area and inferior parietal cortex, whereas an increase in FC was observed in the left cerebellum crus I. Conversely, we observed increased FC for task-based FC in regions implicated in speech production or sequential movements, including the anterior cingulate cortex, posterior insula, and bilateral cerebellum crus I in PWS. Functional network characterization of the altered FCs revealed that the sets of reduced resting-state and increased task-based FCs were largely distinct, but the somatomotor and striatum/thalamus networks were foci of alterations in both conditions. These observations indicate that developmental stuttering is characterized by structural and functional alterations in multiple brain networks that support speech fluency or sequential motor processes, including cortico-cortical and subcortical connections.

Subcortical volumetric alterations in four major psychiatric disorders: a mega-analysis study of 5604 subjects and a volumetric data-driven approach for classification

Differential diagnosis is sometimes difficult in practical psychiatric settings, in terms of using the current diagnostic system based on presenting symptoms and signs. The creation of a novel diagnostic system using objective biomarkers is expected to take place. Neuroimaging studies and others reported that subcortical brain structures are the hubs for various psycho-behavioral functions, while there are so far no neuroimaging data-driven clinical criteria overcoming limitations of the current diagnostic system, which would reflect cognitive/social functioning. Prior to the main analysis, we conducted a large-scale multisite study of subcortical volumetric and lateralization alterations in schizophrenia, bipolar disorder, major depressive disorder, and autism spectrum disorder using T1-weighted images of 5604 subjects (3078 controls and 2526 patients). We demonstrated larger lateral ventricles volume in schizophrenia, bipolar disorder, and major depressive disorder, smaller hippocampus volume in schizophrenia and bipolar disorder, and schizophrenia-specific smaller amygdala, thalamus, and accumbens volumes and larger caudate, putamen, and pallidum volumes. In addition, we observed a leftward alteration of lateralization for pallidum volume specifically in schizophrenia. Moreover, as our main objective, we clustered the 5,604 subjects based on subcortical volumes, and explored whether data-driven clustering results can explain cognitive/social functioning in the subcohorts. We showed a four-biotype classification, namely extremely (Brain Biotype [BB] 1) and moderately smaller limbic regions (BB2), larger basal ganglia (BB3), and normal volumes (BB4), being associated with cognitive/social functioning. Specifically, BB1 and BB2-3 were associated with severe and mild cognitive/social impairment, respectively, while BB4 was characterized by normal cognitive/social functioning. Our results may lead to the future creation of novel biological data-driven psychiatric diagnostic criteria, which may be expected to be useful for prediction or therapeutic selection.

Cerebral cortical structural alteration patterns across four major psychiatric disorders in 5549 individuals

According to the operational diagnostic criteria, psychiatric disorders such as schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and autism spectrum disorder (ASD) are classified based on symptoms. While its cluster of symptoms defines each of these psychiatric disorders, there is also an overlap in symptoms between the disorders. We hypothesized that there are also similarities and differences in cortical structural neuroimaging features among these psychiatric disorders. T1-weighted magnetic resonance imaging scans were performed for 5,549 subjects recruited from 14 sites. Effect sizes were determined using a linear regression model within each protocol, and these effect sizes were meta-analyzed. The similarity of the differences in cortical thickness and surface area of each disorder group was calculated using cosine similarity, which was calculated from the effect sizes of each cortical regions. The thinnest cortex was found in SZ, followed by BD and MDD. The cosine similarity values between disorders were 0.943 for SZ and BD, 0.959 for SZ and MDD, and 0.943 for BD and MDD, which indicated that a common pattern of cortical thickness alterations was found among SZ, BD, and MDD. Additionally, a generally smaller cortical surface area was found in SZ and MDD than in BD, and the effect was larger in SZ. The cosine similarity values between disorders were 0.945 for SZ and MDD, 0.867 for SZ and ASD, and 0.811 for MDD and ASD, which indicated a common pattern of cortical surface area alterations among SZ, MDD, and ASD. Patterns of alterations in cortical thickness and surface area were revealed in the four major psychiatric disorders. To our knowledge, this is the first report of a cross-disorder analysis conducted on four major psychiatric disorders. Cross-disorder brain imaging research can help to advance our understanding of the pathogenesis of psychiatric disorders and common symptoms.

White matter alterations in Attention-Deficit/Hyperactivity Disorder (ADHD): a systematic review of 129 diffusion imaging studies with meta-analysis

Aberrant anatomical brain connections in attention-deficit/hyperactivity disorder (ADHD) are reported inconsistently across diffusion weighted imaging (DWI) studies. Based on a pre-registered protocol (Prospero: CRD42021259192), we searched PubMed, Ovid, and Web of Knowledge until 26/03/2022 to conduct a systematic review of DWI studies. We performed a quality assessment based on imaging acquisition, preprocessing, and analysis. Using signed differential mapping, we meta-analyzed a subset of the retrieved studies amenable to quantitative evidence synthesis, i.e., tract-based spatial statistics (TBSS) studies, in individuals of any age and, separately, in children, adults, and high-quality datasets. Finally, we conducted meta-regressions to test the effect of age, sex, and medication-naïvety. We included 129 studies (6739 ADHD participants and 6476 controls), of which 25 TBSS studies provided peak coordinates for case-control differences in fractional anisotropy (FA)(32 datasets) and 18 in mean diffusivity (MD)(23 datasets). The systematic review highlighted white matter alterations (especially reduced FA) in projection, commissural and association pathways of individuals with ADHD, which were associated with symptom severity and cognitive deficits. The meta-analysis showed a consistent reduced FA in the splenium and body of the corpus callosum, extending to the cingulum. Lower FA was related to older age, and case-control differences did not survive in the pediatric meta-analysis. About 68% of studies were of low quality, mainly due to acquisitions with non-isotropic voxels or lack of motion correction; and the sensitivity analysis in high-quality datasets yielded no significant results. Findings suggest prominent alterations in posterior interhemispheric connections subserving cognitive and motor functions affected in ADHD, although these might be influenced by non-optimal acquisition parameters/preprocessing. Absence of findings in children may be related to the late development of callosal fibers, which may enhance case-control differences in adulthood. Clinicodemographic and methodological differences were major barriers to consistency and comparability among studies, and should be addressed in future investigations.

Increased glutamate and glutamine levels and their relationship to astrocytes and dopaminergic transmissions in the brains of adults with autism

Increased excitatory neuronal tones have been implicated in autism, but its mechanism remains elusive. The amplified glutamate signals may arise from enhanced glutamatergic circuits, which can be affected by astrocyte activation and suppressive signaling of dopamine neurotransmission. We tested this hypothesis using magnetic resonance spectroscopy and positron emission tomography scan with ¹¹C-SCH23390 for dopamine D1 receptors in the anterior cingulate cortex (ACC). We enrolled 18 male adults with high-functioning autism and 20 typically developed (TD) male subjects. The autism group showed elevated glutamate, glutamine, and myo-inositol (mI) levels compared with the TD group (p = 0.045, p = 0.044, p = 0.030, respectively) and a positive correlation between glutamine and mI levels in the ACC (r = 0.54, p = 0.020). In autism and TD groups, ACC D1 receptor radioligand binding was negatively correlated with ACC glutamine levels (r =  - 0.55, p = 0.022; r =  - 0.58, p = 0.008, respectively). The enhanced glutamate-glutamine metabolism might be due to astroglial activation and the consequent reinforcement of glutamine synthesis in autistic brains. Glutamine synthesis could underly the physiological inhibitory control of dopaminergic D1 receptor signals. Our findings suggest a high neuron excitation-inhibition ratio with astrocytic activation in the etiology of autism.

Neural correlates of perceptual switching and their association with empathy and alexithymia in individuals with and without autism spectrum disorder

Individuals with autism spectrum disorder (ASD) often show limited empathy (poor recognition of others' emotions) and high alexithymia (poor recognition of own emotions and external thinking), which can negatively impact their social functioning. Previous experimental studies suggest that alterations in cognitive flexibility play key roles in the development of these characteristics in ASD. However, the underlying neural mechanisms that link cognitive flexibility and empathy/alexithymia are still largely unknown. In this study, we examined the neural correlates of cognitive flexibility via functional magnetic resonance imaging during perceptual task-switching in typical development (TD) adults and adults with ASD. We also investigated associations between regional neural activity and psychometric empathy and alexithymia scores among these populations. In the TD group, stronger activation of the left middle frontal gyrus was associated with better perceptual switching and greater empathic concern. Among individuals with ASD, stronger activation of the left inferior frontal gyrus was associated with better perceptual switching, greater empathy, and lower alexithymia. These findings will contribute to develop a better understanding of social cognition, and could be informative for the development of new ASD therapies.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites and different developmental stages. Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults and Japanese adults. The neuromarker demonstrated significant generalization for children and adolescents. We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study

Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P < 0.05 , family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.

Distinctive alterations in the mesocorticolimbic circuits in various psychiatric disorders

AIM

Increasing evidence suggests that psychiatric disorders are linked to alterations in the mesocorticolimbic dopamine-related circuits. However, the common and disease-specific alterations remain to be examined in schizophrenia (SCZ), major depressive disorder (MDD), and autism spectrum disorder (ASD). Thus, this study aimed to examine common and disease-specific features related to mesocorticolimbic circuits.

METHODS

This study included 555 participants from four institutes with five scanners: 140 individuals with SCZ (45.0% female), 127 individuals with MDD (44.9%), 119 individuals with ASD (15.1%), and 169 healthy controls (HC) (34.9%). All participants underwent resting-state functional magnetic resonance imaging. A parametric empirical Bayes approach was adopted to compare estimated effective connectivity among groups. Intrinsic effective connectivity focusing on the mesocorticolimbic dopamine-related circuits including the ventral tegmental area (VTA), shell and core parts of the nucleus accumbens (NAc), and medial prefrontal cortex (mPFC) were examined using a dynamic causal modeling analysis across these psychiatric disorders.

RESULTS

The excitatory shell-to-core connectivity was greater in the all patients than in the HC group. The inhibitory shell-to-VTA and shell-to-mPFC connectivities were greater in the ASD group than in the HC, MDD, and SCZ groups. Furthermore, the VTA-to-core and VTA-to-shell connectivities were excitatory in the ASD group, while those connections were inhibitory in the HC, MDD, and SCZ groups.

CONCLUSION

Impaired signaling in the mesocorticolimbic dopamine-related circuits could be an underlying neuropathogenesis of various psychiatric disorders. These findings will improve the understanding of unique neural alternations of each disorder and will facilitate identification of effective therapeutic targets. This article is protected by copyright. All rights reserved.

Decision Flexibilities in Autism Spectrum Disorder: An fMRI Study of Moral Dilemmas

People make flexible decisions across a wide range of contexts to resolve social or moral conflicts. Individuals with autism spectrum disorder (ASD) frequently report difficulties in such behaviors, which hinders the flexibility in changing strategies during daily activities or adjustment of perspective during communication. However, the underlying mechanisms of this issue are insufficiently understood. This study aimed to investigate decision flexibility in ASD using a functional magnetic resonance imaging task that involved recognizing and resolving two types of moral dilemmas: cost–benefit analysis (CBA) and mitigating inevitable misconducts (MIM). The CBA session assessed the participants’ pitting of result-oriented outcomes against distressful harmful actions, whereas the MIM session assessed their pitting of the extenuation of a criminal sentence against a sympathetic situation of defendants suffering from violence or disease. The behavioral outcome in CBA-related flexibility was significantly lower in the ASD group compared to that of the typical development group. In the corresponding CBA contrast, activation in the left inferior frontal gyrus was lower in the ASD group. Meanwhile, in the MIM-related flexibility, there were no significant group differences in behavioral outcome or brain activity. Our findings add to our understanding of flexible decision-making in ASD.

Intergroup bias in punishing behaviors of adults with autism spectrum disorder

Groups are essential elements of society, and humans, by nature, commonly manifest intergroup bias (i.e., behave more positively toward an ingroup member than toward an outgroup member). Despite the growing evidence of various types of altered decision-making in individuals with autism spectrum disorder (ASD), their behavior under the situation involving group membership remains largely unexplored. By modifying a third-party punishment paradigm, we investigated intergroup bias in individuals with ASD and typical development (TD). In our experiment, participants who were considered as the third party observed a dictator game wherein proposers could decide how to distribute a provided amount of money while receivers could only accept unconditionally. Participants were confronted with two different group situations: the proposer was an ingroup member and the recipient was an outgroup member (IN/OUT condition) or the proposer was an outgroup member and the recipient was an ingroup member (OUT/IN condition). Participants with TD punished proposers more severely when violating social norms in the OUT/IN condition than in IN/OUT condition, indicating that their decisions were influenced by the intergroup context. This intergroup bias was attenuated in individuals with ASD. Our findings deepen the understanding of altered decision-making and socioeconomic behaviors in individuals with ASD.

Dimensional distribution of cortical abnormality across antipsychotics treatment-resistant and responsive schizophrenia

•

Different etiology is assumed in treatment-resistant and responsive schizophrenia.

•

Patients with treatment-resistant schizophrenia were classified from controls.

•

Patients with non-treatment-resistant schizophrenia were classified from controls.

•

Two classifications reached area under the curve as high as 0.69 and 0.85.

•

Area under the curve remained as high as 0.69 when two classifiers were swapped.

Background

One-third of patients with schizophrenia are treatment-resistant to non-clozapine antipsychotics (TRS), while the rest respond (NTRS). Examining whether TRS and NTRS represent different pathophysiologies is an important step toward precision medicine.

Methods

Focusing on cortical thickness (CT), we analyzed international multi-site cross-sectional datasets of magnetic resonance imaging comprising 110 patients with schizophrenia (NTRS = 46, TRS = 64) and 52 healthy controls (HCs). We utilized a logistic regression with L1-norm regularization to find brain regions related to either NTRS or TRS. We conducted nested 10-fold cross-validation and computed the accuracy and area under the curve (AUC). Then, we applied the NTRS classifier to patients with TRS, and vice versa.

Results

Patients with NTRS and TRS were classified from HCs with 65% and 78% accuracies and with the AUC of 0.69 and 0.85 (p = 0.014 and < 0.001, corrected), respectively. The left planum temporale (PT) and left anterior insula/inferior frontal gyrus (IFG) contributed to both NTRS and TRS classifiers. The left supramarginal gyrus only contributed to NTRS and right superior temporal sulcus and right lateral orbitofrontal cortex only to the TRS. The NTRS classifiers successfully distinguished those with TRS from HCs with the AUC of 0.78 (p < 0.001), while the TRS classifiers classified those with NTRS from HCs with the AUC of 0.69 (p = 0.015).

Conclusion

Both NTRS and TRS could be distinguished from HCs on the basis of CT. The CT pathological basis of NTRS and TRS has commonalities, and TRS presents unique CT features.

Prediction of life satisfaction from resting-state functional connectome

BACKGROUND

Better life satisfaction (LS) is associated with better psychological and psychiatric outcomes. To the best of our knowledge, no studies have examined prediction models for LS.

METHODS

Using resting-state functional magnetic resonance imaging (R-fMRI) data from the Human Connectome Project (HCP) Young Adult S1200 dataset, we examined whether LS is predictable from intrinsic functional connectivity (iFC). All the HCP data were subdivided into either discovery (n = 100) or validation (n = 766) datasets. Using R-fMRI data in the discovery dataset, we computed a matrix of iFCs between brain regions. Ridge regression, in combination with principal component analysis and 10-fold cross-validation, was used to predict LS. Prediction performance was evaluated by comparing actual and predicted LS scores. The generalizability of the prediction model obtained from the discovery dataset was evaluated by applying this model to the validation dataset.

RESULTS

The model was able to successfully predict LS in the discovery dataset (r = 0.381, p < .001). The model was also able to successfully predict the degree of LS (r = 0.137, 5000-repetition permutation test p = .006) in the validation dataset, suggesting that our model is generalizable to the prediction of LS in young adults. iFCs stemming from visual, ventral attention, or limbic networks to other networks (such as the dorsal attention network and default mode network) were likely to contribute positively toward predicted LS scores. iFCs within ventral attention and limbic networks also positively contributed to predicting LS. On the other hand, iFCs stemming from the visual and cerebellar networks to other networks were likely to contribute negatively to the predicted LS scores.

CONCLUSION

The present findings suggest that LS is predictable from the iFCs. These results are an important step toward identifying the neural basis of life satisfaction.

A multi-site, multi-disorder resting-state magnetic resonance image database

Machine learning classifiers for psychiatric disorders using resting-state functional magnetic resonance imaging (rs-fMRI) have recently attracted attention as a method for directly examining relationships between neural circuits and psychiatric disorders. To develop accurate and generalizable classifiers, we compiled a large-scale, multi-site, multi-disorder neuroimaging database. The database comprises resting-state fMRI and structural images of the brain from 993 patients and 1,421 healthy individuals, as well as demographic information such as age, sex, and clinical rating scales. To harmonize the multi-site data, nine healthy participants (“traveling subjects”) visited the sites from which the above datasets were obtained and underwent neuroimaging with 12 scanners. All participants consented to having their data shared and analyzed at multiple medical and research institutions participating in the project, and 706 patients and 1,122 healthy individuals consented to having their data disclosed. Finally, we have published four datasets: 1) the SRPBS Multi-disorder Connectivity Dataset 2), the SRPBS Multi-disorder MRI Dataset (restricted), 3) the SRPBS Multi-disorder MRI Dataset (unrestricted), and 4) the SRPBS Traveling Subject MRI Dataset.

Measurement(s)	mental or behavioural disorder • brain measurement • Demographic Data
Technology Type(s)	functional magnetic resonance imaging • magnetic resonance imaging • Resting State Functional Connectivity Magnetic Resonance Imaging
Factor Type(s)	age • sex • site • disorder
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.14716329

Brain activations while processing degraded speech in adults with autism spectrum disorder

Individuals with autism spectrum disorder (ASD) are found to have difficulties in understanding speech in adverse conditions. In this study, we used noise-vocoded speech (VS) to investigate neural processing of degraded speech in individuals with ASD. We ran fMRI experiments in the ASD group and a typically developed control (TDC) group while they listened to clear speech (CS), VS, and spectrally rotated VS (SRVS), and they were requested to pay attention to the heard sentence and answer whether it was intelligible or not. The VS used in this experiment was spectrally degraded but still intelligible, but the SRVS was unintelligible. We recruited 21 right-handed adult males with ASD and 24 age-matched and right-handed male TDC participants for this experiment. Compared with the TDC group, we observed reduced functional connectivity (FC) between the left dorsal premotor cortex and left temporoparietal junction in the ASD group for the effect of task difficulty in speech processing, computed as VS-(CS + SRVS)/2. Furthermore, the observed reduced FC was negatively correlated with their Autism-Spectrum Quotient scores. This observation supports our hypothesis that the disrupted dorsal stream for attentive process of degraded speech in individuals with ASD might be related to their difficulty in understanding speech in adverse conditions.

Neural correlates of shared sensory symptoms in autism and attention-deficit/hyperactivity disorder

Symptoms of autism spectrum disorder and attention-deficit/hyperactivity disorder often co-occur. Among these, sensory impairment, which is a core diagnostic feature of autism spectrum disorder, is often observed in children with attention-deficit/hyperactivity disorder. However, the underlying mechanisms of symptoms that are shared across disorders remain unknown. To examine the neural correlates of sensory symptoms that are associated with autism spectrum disorder and attention-deficit/hyperactivity disorder, we analysed resting-state functional MRI data obtained from 113 people with either autism spectrum disorder or attention-deficit/hyperactivity disorder (n = 78 autism spectrum disorder, mean age = 29.5; n = 35 attention-deficit/hyperactivity disorder, mean age = 31.2) and 96 neurotypical controls (mean age = 30.6, range: 20–55 years) using a cross-sectional study design. First, we used a multi-dimensional approach to examine intrinsic brain functional connectivity related to sensory symptoms in four domains (i.e. low registration, sensation seeking, sensory sensitivity and sensation avoidance), after controlling for age, handedness and head motion. Then, we used a partial least squares correlation to examine the link between sensory symptoms related to intrinsic brain functional connectivity and neurodevelopmental symptoms measured using the Autism Spectrum Quotient and Conners’ Adult Attention-Deficit/Hyperactivity Disorder Rating Scale, regardless of diagnosis. To test whether observed associations were specific to sensory symptoms related to intrinsic brain functional connectivity, we conducted a control analysis using a bootstrap framework. The results indicated that transdiagnostic yet distinct intrinsic brain functional connectivity neural bases varied according to the domain of the examined sensory symptom. Partial least squares correlation analysis revealed two latent components (latent component 1: q < 0.001 and latent component 2: q < 0.001). For latent component 1, a set of intrinsic brain functional connectivity was predominantly associated with neurodevelopmental symptom-related composite score (r = 0.64, P < 0.001), which was significantly correlated with Conners’ Adult Attention-Deficit/Hyperactivity Disorder Rating Scale total T scores (r = −0.99, q < 0.001). For latent component 2, another set of intrinsic brain functional connectivity was positively associated with neurodevelopmental symptom-related composite score (r = 0.58, P < 0.001), which was eventually positively associated with Autism Spectrum Quotient total scores (r = 0.92, q < 0.001). The bootstrap analysis showed that the relationship between intrinsic brain functional connectivity and neurodevelopmental symptoms was relative to sensory symptom-related intrinsic brain functional connectivity (latent component 1: P = 0.003 and latent component 2: P < 0.001). The current results suggest that sensory symptoms in individuals with autism spectrum disorder and those with attention-deficit/hyperactivity disorder have shared neural correlates. The neural correlates of the sensory symptoms were associated with the severity of both autism spectrum disorder and attention-deficit/hyperactivity disorder symptoms, regardless of diagnosis.

Common Brain Networks Between Major Depressive-Disorder Diagnosis and Symptoms of Depression That Are Validated for Independent Cohorts

Large-scale neuroimaging data acquired and shared by multiple institutions are essential to advance neuroscientific understanding of pathophysiological mechanisms in psychiatric disorders, such as major depressive disorder (MDD). About 75% of studies that have applied machine learning technique to neuroimaging have been based on diagnoses by clinicians. However, an increasing number of studies have highlighted the difficulty in finding a clear association between existing clinical diagnostic categories and neurobiological abnormalities. Here, using resting-state functional magnetic resonance imaging, we determined and validated resting-state functional connectivity related to depression symptoms that were thought to be directly related to neurobiological abnormalities. We then compared the resting-state functional connectivity related to depression symptoms with that related to depression diagnosis that we recently identified. In particular, for the discovery dataset with 477 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a brain network prediction model of depression symptoms (Beck Depression Inventory-II [BDI] score). The prediction model significantly predicted BDI score for an independent validation dataset with 439 participants from 4 different imaging sites. Finally, we found 3 common functional connections between those related to depression symptoms and those related to MDD diagnosis. These findings contribute to a deeper understanding of the neural circuitry of depressive symptoms in MDD, a hetero-symptomatic population, revealing the neural basis of MDD.

Systematic Review and Meta-analysis: Resting-State Functional Magnetic Resonance Imaging Studies of Attention-Deficit/Hyperactivity Disorder

OBJECTIVE

To conduct a meta-analysis of resting-state functional magnetic resonance imaging (R-fMRI) studies in children and adolescents with attention-deficit/hyperactivity disorder (ADHD) and in adults with ADHD to assess spatial convergence of findings from available studies.

METHOD

Based on a preregistered protocol in PROSPERO (CRD42019119553), a large set of databases were searched up to April 9, 2019, with no language or article type restrictions. Study authors were systematically contacted for additional unpublished information/data. Resting-state functional magnetic resonance imaging studies using seed-based connectivity (SBC) or any other method (non-SBC) reporting whole-brain results of group comparisons between participants with ADHD and typically developing controls were eligible. Voxelwise meta-analysis via activation likelihood estimation with cluster-level familywise error (voxel-level: p < .001; cluster-level: p < .05) was used.

RESULTS

Thirty studies (18 SBC and 12 non-SBC), comprising 1,978 participants (1,094 with ADHD; 884 controls) were retained. The meta-analysis focused on SBC studies found no significant spatial convergence of ADHD-related hyperconnectivity or hypoconnectivity across studies. This nonsignificant finding remained after integrating 12 non-SBC studies into the main analysis and in sensitivity analyses limited to studies including only children or only non-medication-naïve patients.

CONCLUSION

The lack of significant spatial convergence may be accounted for by heterogeneity in study participants, experimental procedures, and analytic flexibility as well as in ADHD pathophysiology. Alongside other neuroimaging meta-analyses in other psychiatric conditions, the present results should inform the conduct and publication of future neuroimaging studies of psychiatric disorders.

Generalizable brain network markers of major depressive disorder across multiple imaging sites

Many studies have highlighted the difficulty inherent to the clinical application of fundamental neuroscience knowledge based on machine learning techniques. It is difficult to generalize machine learning brain markers to the data acquired from independent imaging sites, mainly due to large site differences in functional magnetic resonance imaging. We address the difficulty of finding a generalizable marker of major depressive disorder (MDD) that would distinguish patients from healthy controls based on resting-state functional connectivity patterns. For the discovery dataset with 713 participants from 4 imaging sites, we removed site differences using our recently developed harmonization method and developed a machine learning MDD classifier. The classifier achieved an approximately 70% generalization accuracy for an independent validation dataset with 521 participants from 5 different imaging sites. The successful generalization to a perfectly independent dataset acquired from multiple imaging sites is novel and ensures scientific reproducibility and clinical applicability.

Impact of past experiences on decision-making in autism spectrum disorder

People are often influenced by past costs in their current decision-making, thus succumbing to a well-known bias recognized as the sunk cost effect. A recent study showed that the sunk cost effect is attenuated in individuals with autism spectrum disorder (ASD). However, the study only addressed one situation of utilization decision by focusing on the choice between similar attractive alternatives with different levels of sunk costs. Thus, it remains unclear how individuals with ASD behave under sunk costs in different types of decision situations, particularly progress decisions, in which the decision-maker allocates additional resources to an initially chosen alternative. The sunk cost effect in progress decisions was estimated using an economic task designed to assess the effect of the past investments on current decision-making. Twenty-four individuals with ASD and 21 age-, sex-, smoking status-, education-, and intelligence quotient-level-matched typical development (TD) subjects were evaluated. The TD participants were more willing to make the second incremental investment if a previous investment was made, indicating that their decisions were influenced by sunk costs. However, unlike the TD group, the rates of investments were not significantly increased after prior investments in the ASD group. The results agree with the previous evidence of a reduced sensitivity to context stimuli in individuals with ASD and help us obtain a broader picture of the impact of sunk costs on their decision-making. Our findings will contribute to a better understanding of ASD and may be useful in addressing practical implications of their socioeconomic behavior.

White matter alterations in autism spectrum disorder and attention-deficit/hyperactivity disorder in relation to sensory profile

Background

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) have high rates of co-occurrence and share atypical behavioral characteristics, including sensory symptoms. The present diffusion tensor imaging (DTI) study was conducted to examine whether and how white matter alterations are observed in adult populations with developmental disorders (DD) and to determine how brain–sensory relationships are either shared between or distinct to ASD and ADHD.

Methods

We collected DTI data from adult population with DD (a primary diagnosis of ASD: n = 105, ADHD: n = 55) as well as age- and sex-matched typically developing (TD) participants (n = 58). Voxel-wise fractional anisotropy (FA), mean diffusivity, axial diffusivity, and radial diffusivity (RD) were analyzed using tract-based spatial statistics. The severities of sensory symptoms were assessed using the Adolescent/Adult Sensory Profile (AASP).

Results

Categorical analyses identified voxel clusters showing significant effects of DD on FA and RD in the posterior portion of the corpus callosum and its extension in the right hemisphere. Furthermore, regression analyses using the AASP scores revealed that slopes in relationships of FA or RD with the degree of sensory symptoms were parallel between the two DDs in large parts of the affected corpus callosum regions. A small but significant cluster did exist showing difference in association between an AASP subscale score and RD across ASD and ADHD.

Limitations

Wide age range of the participants may be oversimplified.

Conclusions

These results indicate that white matter alteration and their relationships to sensory symptoms are largely shared between ASD and ADHD, with localized abnormalities showing significant between-diagnosis differences within DD.

Binding of Dopamine D1 Receptor and Noradrenaline Transporter in Individuals with Autism Spectrum Disorder: A PET Study

Although previous studies have suggested the involvement of dopamine (DA) and noradrenaline (NA) neurotransmissions in the autism spectrum disorder (ASD) pathophysiology, few studies have examined these neurotransmissions in individuals with ASD in vivo. Here, we investigated DA D1 receptor (D1R) and noradrenaline transporter (NAT) binding in adults with ASD (n = 18) and neurotypical controls (n = 20) by utilizing two different PET radioligands, [11C]SCH23390 and (S,S)-[18F]FMeNER-D2, respectively. We found no significant group differences in DA D1R (striatum, anterior cingulate cortex, and temporal cortex) or NAT (thalamus and pons) binding. However, in the ASD group, there were significant negative correlations between DA D1R binding (striatum, anterior cingulate cortex and temporal cortex) and the “attention to detail” subscale score of the Autism Spectrum Quotient. Further, there was a significant positive correlation between DA D1R binding (temporal cortex) and emotion perception ability assessed by the neurocognitive battery. Associations of NAT binding with empathic abilities and executive function were found in controls, but were absent in the ASD group. Although a lack of significant group differences in binding might be partly due to the heterogeneity of ASD, our results indicate that central DA and NA function might play certain roles in the clinical characteristics of ASD.

Functional connectomes linking child-parent relationships with psychological problems in adolescence

The child-parent relationship is a significant factor in an adolescent's well-being and functional outcomes. Epidemiological evidence indicates that relationships with the father and mother are differentially associated with specific psychobehavioral problems that manifest differentially between boys and girls. Neuroimaging is expected to bridge the gap in understanding such a complicated mapping between the child-parent relationships and adolescents' problems. However, possible differences in the effects of child-father and child-mother relationships on sexual dimorphism in children's brains and psychobehavioral problems have not been examined yet. This study used a dataset of 10- to 13-year-old children (N ​= ​93) to reveal the triad of associations among child-parent relationship, brain, and psychobehavioral problems by separately estimating the respective effects of child-father and child-mother relationships on boys and girls. We first fitted general linear models to identify the effects of paternal and maternal relationships in largely different sets of children's resting-state functional connectivity, which we term paternal and maternal functional brain connectomes (FBCs). We then performed connectome-based predictive modeling (CPM) to predict children's externalizing and internalizing problems from these parental FBCs. The models significantly predicted a range of girls' internalizing problems, whereas the prediction of boys' aggression was also significant using a more liberal uncorrected threshold. A series of control analyses confirmed that CPMs using FBCs associated with peer relationship or family socioeconomic status failed to make significant predictions of psychobehavioral problems. Lastly, a causal discovery method identified causal paths from daughter-mother relationship to maternal FBC, and then to daughter's internalizing problems. These observations indicate sex-dependent mechanisms linking child-parent relationship, brain, and psychobehavioral problems in the development of early adolescence.

Transdiagnostic subtyping of males with developmental disorders using cortical characteristics

•

Overlapping diagnosis and within-diagnosis heterogeneity was often reported in ASD.

•

ASD and ADHD were subtyped regardless of diagnosis using cortical characteristics.

•

The analysis revealed the number of subtypes as two.

•

The boundary of the subtypes did not match the diagnostic boundary.

•

The membership of subtypes was robust against the choice of an atlas.

Background

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are biologically heterogeneous and often co-occur. As within-diagnosis heterogeneity and overlapping diagnoses are challenging for researchers and clinicians, identifying biologically homogenous subgroups, independent of diagnosis, is an urgent need.

Methods

MRI data from 148 adult males with developmental disorders (99 primary ASD, mean age = 31.7 ± 8.0, 49 primary ADHD; mean age = 31.7 ± 9.6) and 105 neurotypical controls (NTC; mean age = 30.6 ± 6.8) were analyzed. We extracted mean cortical thickness (CT) and surface area (SA) values using a functional atlas. Then, we conducted HeterogeneitY through DiscRiminant Analysis (HYDRA) to transdiagnostically cluster and classify individuals. Differences in diagnostic likelihood and clinical symptoms between subtypes were tested. Sensitivity analyses tested the stability of the number of subtypes and their membership by excluding 13 participants diagnosed with both ASD and ADHD and by using a different atlas.

Results

In relation to both CT and SA, HYDRA identified two subtypes. The likelihood of ASD or ADHD was not significantly different from the chance of belonging to any of these two subtypes. Clinical characteristics did not differ between subtypes in either CT or SA based analyses. The high consistency in membership was replicated when utilizing a different atlas or excluding people with dual diagnoses in CT (dice coefficients > 0.94) and in SA (>0.88).

Conclusion

Although the brain-derived subtypes do not match diagnostic groups, individuals with developmental disorders were successfully and stably subtyped using either CT or SA.

Role of the right temporoparietal junction in intergroup bias in trust decisions

Intergroup bias, which is the tendency to behave more positively toward an in-group member than toward an out-group member, is pervasive in real life. In particular, intergroup bias in trust decisions substantially influences multiple areas of life and thus better understanding of this tendency can provide significant insights into human social behavior. Although previous functional magnetic resonance imaging studies showed the involvement of the right temporoparietal junction (TPJ) in intergroup trust bias, a causal relationship between the two has rarely been explored. By combining repetitive transcranial magnetic stimulation and a newly developed trust game task, we investigated the causal role of the right TPJ in intergroup bias in trust decisions. In the trust game task, the counterpart's group membership (in-group or out-group) and reciprocity were manipulated. We applied either neuronavigated inhibitory continuous theta burst stimulation (cTBS) or sham stimulation over the right TPJ before performing the trust game task in healthy volunteers. After the sham stimulation, the participants' degrees of investments with in-group members were significantly higher than those with out-group members. However, after cTBS to the right TPJ, this difference was not observed. The current results extend previous findings by showing that the causal roles of the right TPJ can be observed in intergroup bias in trust decisions. Our findings add to our understanding of the mechanisms of human social behavior.

Estimating repetitive spatiotemporal patterns from many subjects' resting-state fMRIs

Recently, we proposed a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data (SpatioTemporal Pattern estimation, STeP) (Takeda et al., 2016). From such resting-state data as functional MRI (fMRI), STeP can estimate several spatiotemporal patterns and their onsets even if they are overlapping. Nowadays, a growing number of resting-state data are publicly available from such databases as the Autism Brain Imaging Data Exchange (ABIDE), which promote a better understanding of resting-state brain activities. In this study, we extend STeP to make it applicable to such big databases, thus proposing the method we call BigSTeP. From many subjects' resting-state data, BigSTeP estimates spatiotemporal patterns that are common across subjects (common spatiotemporal patterns) as well as the corresponding spatiotemporal patterns in each subject (subject-specific spatiotemporal patterns). After verifying the performance of BigSTeP by simulation tests, we applied it to over 1,000 subjects' resting-state fMRIs (rsfMRIs) obtained from ABIDE I. This revealed two common spatiotemporal patterns and the corresponding subject-specific spatiotemporal patterns. The common spatiotemporal patterns included spatial patterns resembling the default mode (DMN), sensorimotor, auditory, and visual networks, suggesting that these networks are time-locked with each other. We compared the subject-specific spatiotemporal patterns between autism spectrum disorder (ASD) and typically developed (TD) groups. As a result, significant differences were concentrated at a specific time in a pattern, when the DMN exhibited large positive activity. This suggests that the differences are context-dependent, that is, the differences in fMRI activities between ASDs and TDs do not always occur during the resting state but tend to occur when the DMN exhibits large positive activity. All of these results demonstrate the usefulness of BigSTeP in extracting inspiring hypotheses from big databases in a data-driven way.

Cortical surface architecture endophenotype and correlates of clinical diagnosis of autism spectrum disorder

AIM

Prior structural magnetic resonance imaging studies demonstrated atypical gray matter characteristics in siblings of individuals with autism spectrum disorder (ASD). However, they did not clarify which aspect of gray matter is related to the endophenotype (i.e., genetic vulnerability) of ASD. Further, because they did not enroll siblings of typically developing (TD) people, they may have underestimated the difference between individuals with ASD and their unaffected siblings. The current study aimed to address these gaps.

METHODS

We recruited 30 pairs of adult male siblings (15 pairs with an ASD endophenotype and 15 pairs without) and focused on four gray matter parameters: cortical volume and three surface-based parameters (cortical thickness, fractal dimension, and sulcal depth [SD]). First, we sought to identify a pattern of an ASD endophenotype, comparing the four parameters. Then, we compared individuals with ASD and their unaffected siblings in the cortical parameters to identify neural correlates for the clinical diagnosis accounting for the difference between TD siblings.

RESULTS

A sparse logistic regression with a leave-one-pair-out cross-validation showed the SD as having the highest accuracy for the identification of an ASD endophenotype (73.3%) compared with the other three parameters. A bootstrapping analysis accounting for the difference in the SD between TD siblings showed a significantly large difference between individuals with ASD and their unaffected siblings in six out of 68 regions of interest.

CONCLUSION

This proof-of-concept study suggests that an ASD endophenotype emerges in the SD and that neural bases for ASD diagnosis can be discerned from the endophenotype when accounting for the difference between TD siblings.

Harmonization of resting-state functional MRI data across multiple imaging sites via the separation of site differences into sampling bias and measurement bias

When collecting large amounts of neuroimaging data associated with psychiatric disorders, images must be acquired from multiple sites because of the limited capacity of a single site. However, site differences represent a barrier when acquiring multisite neuroimaging data. We utilized a traveling-subject dataset in conjunction with a multisite, multidisorder dataset to demonstrate that site differences are composed of biological sampling bias and engineering measurement bias. The effects on resting-state functional MRI connectivity based on pairwise correlations because of both bias types were greater than or equal to psychiatric disorder differences. Furthermore, our findings indicated that each site can sample only from a subpopulation of participants. This result suggests that it is essential to collect large amounts of neuroimaging data from as many sites as possible to appropriately estimate the distribution of the grand population. Finally, we developed a novel harmonization method that removed only the measurement bias by using a traveling-subject dataset and achieved the reduction of the measurement bias by 29% and improvement of the signal-to-noise ratios by 40%. Our results provide fundamental knowledge regarding site effects, which is important for future research using multisite, multidisorder resting-state functional MRI data.

Sunk Cost Effect in Individuals with Autism Spectrum Disorder

The sunk cost effect, an interesting and well-known decision bias, is pervasive in real life and has been studied in various disciplines. In this study, we modified a task exemplifying the sunk cost effect and used it to evaluate this behavior in individuals with autism spectrum disorder (ASD). The control group exhibited a typical sunk cost effect in our task. We found that the sunk cost effect was lower in the ASD group than in the control group. The results agree with previous evidence of reduced sensitivity to context stimuli in individuals with ASD and extend this finding to the context of the sunk cost effect. Our findings are useful in addressing the practical implications on their socioeconomic behavior.

White matter endophenotypes and correlates for the clinical diagnosis of autism spectrum disorder

Since prior diffusion tensor imaging (DTI) studies reported no significant differences in white matter organizations between individuals with autism spectrum disorder (ASD) and their unaffected siblings, the neural correlates for developing a clinical diagnosis among people with endophenotypes remain undetermined. We obtained DTI data from a total of 60 participants consisting of 30 people with endophenotypes and 30 people without. We first followed a conventional approach by comparing individuals with ASD and their unaffected siblings. Using region-of-interest approach, we then performed bootstrapping to examine whether the differences in white matter organizations between individuals with ASD and their unaffected siblings were substantially large, considering the distribution of differences between typically developing (TD) siblings. Conventional approaches revealed no significant differences in white matter organizations between individuals with ASD and their unaffected siblings. Bootstrapping revealed a significantly large difference in axial diffusivity in the left stria terminalis between individuals with ASD and their unaffected siblings after accounting for the distribution of differences in axial diffusivity among TD siblings (99.998 percentile). The results remained significant after controlling for multiple comparisons with Bonferroni method. We assumed that one aspect of this tract was associated with the development of a clinical diagnosis.

Need for closure and cognitive flexibility in individuals with autism spectrum disorder: A preliminary study

The need for closure (NFC), a desire for a firm answer and less ambiguity, has a key role in cognitive flexibility in typical development (TD) populations. This study investigated this motivational construct and its relation to cognitive inflexibility in autism spectrum disorder (ASD). Compared with individuals with TD, those with ASD reported higher levels in preference for predictability and closed-mindedness and lower levels in decisiveness. These NFC facets were significantly associated with cognitive flexibility in ASD as well as TD groups. The study findings provide further insights into the motivational underpinnings of flexible behavior in ASD.

Inflexible daily behaviour is associated with the ability to control an automatic reaction in autism spectrum disorder

Inflexible behaviours in people with autism spectrum disorder (ASD) broadly obstruct social communication. Meanwhile, flexibility implicates cognitive control to resolve socially conflicting situations; however, it remains unclear how people with ASD behave in the face of these conflicts in this respect. We used the ultimatum game (UG) and the implicit-association test (IAT) to examine goal-directed/economic flexibility, both of which involve conflict and cognitive control. In addition, we used the Detail and Flexibility Questionnaire (DFlex) to measure inflexible everyday behaviour with diminished cognitive control and attention shifting. We observed the decreased flexibility in participants with ASD (DFlex and IAT); further, their IAT scores positively correlated with DFlex. However, in the UG, contrary to our prediction, participants with ASD accepted unfair offers more frequently than TD. These results suggest that assessing the automatic/attention processing level with the IAT could be a useful approach to study behavioural flexibility among ASD compared with the UG, which might comprise multiple response strategies besides economic rationality. Overall, the severity of inflexible daily behaviours in people with ASD may be associated with a reduced flexible attitude at an automatic level, altered attention processing and decreased cognitive control.

Linked functional network abnormalities during intrinsic and extrinsic activity in schizophrenia as revealed by a data-fusion approach

Abnormalities in functional brain networks in schizophrenia have been studied by examining intrinsic and extrinsic brain activity under various experimental paradigms. However, the identified patterns of abnormal functional connectivity (FC) vary depending on the adopted paradigms. Thus, it is unclear whether and how these patterns are inter-related. In order to assess relationships between abnormal patterns of FC during intrinsic activity and those during extrinsic activity, we adopted a data-fusion approach and applied partial least square (PLS) analyses to FC datasets from 25 patients with chronic schizophrenia and 25 age- and sex-matched normal controls. For the input to the PLS analyses, we generated a pair of FC maps during the resting state (REST) and the auditory deviance response (ADR) from each participant using the common seed region in the left middle temporal gyrus, which is a focus of activity associated with auditory verbal hallucinations (AVHs). PLS correlation (PLS-C) analysis revealed that patients with schizophrenia have significantly lower loadings of a component containing positive FCs in default-mode network regions during REST and a component containing positive FCs in the auditory and attention-related networks during ADR. Specifically, loadings of the REST component were significantly correlated with the severities of positive symptoms and AVH in patients with schizophrenia. The co-occurrence of such altered FC patterns during REST and ADR was replicated using PLS regression, wherein FC patterns during REST are modeled to predict patterns during ADR. These findings provide an integrative understanding of altered FCs during intrinsic and extrinsic activity underlying core schizophrenia symptoms.

•

A new fMRI analysis method for data fusion was applied to schizophrenia fMRI data.

•

Multiple patterns of abnormal functional connectivity were linked in schizophrenia.

•

Abnormal networks included the auditory language and saliency networks and DMN.

•

The identified patterns of connectivity abnormalities were correlated with symptoms.

The effect of visual cues on performance in the ultimatum game in individuals with autism spectrum disorder

The Ultimatum Game (UG) allows for the assessment of altruistic behavior as well as the perception of fairness. We examined the effects of visual social cues (gaze of others), factors associated with autism, and trust on UG performance in typical adults (TAs) and individuals with autism spectrum disorder (ASD). We hypothesized that individuals with ASD would be less affected by visual social cues than TAs. We recruited 30 TAs and 30 individuals with ASD. Participants completed 30 trials of the UG, during which the visual background was altered to include either stylized eyespots, flowers, or a neutral background. Reaction times and money distributed in each condition were recorded. Reaction times did not vary among background conditions in either group, although individuals with ASD responded more slowly overall. TAs distributed less money in the neutral background and flowers conditions than in the eyespots condition, while no significant differences in the amount of money distributed were observed among background conditions for individuals with ASD, who also distributed more money overall than TAs. Such findings may be due to decreased susceptibility to social cues among individuals with ASD.

Attitudes toward risk and ambiguity in patients with autism spectrum disorder

Although the ability to make optimal decisions under uncertainty is an integral part of everyday life, individuals with autism spectrum disorder (ASD) frequently report that they experience difficulties with this skill. In behavioral economics, researchers distinguish two types of uncertainty to understand decision-making in this setting: risk (known probabilities) and ambiguity (unknown probabilities). However, it remains unclear how individuals with ASD behave under risk and ambiguity, despite growing evidence of their altered decision-making under uncertainty. We therefore extended previous research by studying the attitudes of those with ASD toward risk and ambiguity in both positive and negative contexts (i.e., gain and loss). In gain contexts, no significant difference was observed between the groups in risk attitudes, but ambiguity aversion was attenuated in ASD. In loss contexts, ambiguity attitudes did not significantly differ between the groups, but the ASD participants were less risk-seeking compared with the controls. In addition, insensitivity to the context change under risk and ambiguity in ASD was both significantly associated with poor social skills. These results improve our understanding of altered decision-making under uncertainty by disentangling the attitudes toward risk and ambiguity in ASD individuals. Applying behavioral economic tools may provide insights into the mechanisms underlying behavioral disturbances in ASD.

Cognitive profiles of adults with high-functioning autism spectrum disorder and those with attention-deficit/hyperactivity disorder based on the WAIS-III

The cognitive profile differences between adult patients with autism spectrum disorder (ASD) and those with attention-deficit/hyperactivity disorder (ADHD) are not well characterized. We examined the cognitive profiles of adults having either ASD (n=120) or ADHD (n=76) with no intellectual disabilities (IQ≥70) using the Wechsler Intelligence Scale III (WAIS-III). Verbal Intelligence (VIQ) - Performance Intelligence (PIQ) difference discrepancies were detected between the two groups. Information subtest scores of the Verbal Comprehension index and Arithmetic and Digit Span subtests of the Freedom from Distractibility index were significantly higher in ASD than in ADHD, while the Picture Completion subtest was significantly lower in ASD. To our knowledge, this is the first study to evaluate the difference in the cognitive profiles of adults with ASD and those with ADHD based on the WAIS III with a large number of participants.

Aberrant Spatial and Temporal Prefrontal Activation Patterns in Medication-Naïve Adults with ADHD

Previous near-infrared spectroscopy (NIRS) studies using a verbal fluency task (VFT) have consistently reported that adults with attention-deficit hyperactivity disorder (ADHD) showed significantly smaller oxygenated-hemoglobin [oxy-Hb] activations in the prefrontal cortex (PFC) compared to those in healthy controls (HC). Despite this consistent evidence of brain dysfunction in ADHD, ADHD is currently diagnosed based only on subjective clinical and scoring measures, which are often unreliable. Hence, it is necessary to establish objective neuroimaging biomarkers for ADHD. While most NIRS studies have utilized averaged [oxy-Hb] values during the whole task period for group comparisons, we used a cluster-based non-parametric randomization test to compare the [oxy-Hb] time-course changes with a 0.1-s time resolution between drug-naïve adults with ADHD and HC, which may provide us with more details regarding abnormal prefrontal activation patterns in ADHD. A total of 101 participants, consisting of 63 drug-naïve adult individuals with ADHD and 38 HC, were included in this study. We identified that adults with ADHD showed significantly smaller [oxy-Hb] activations than those in HC at spatially and temporally connected clusters located in the bilateral PFC (more prominent on the left) and temporal brain region (more prominent on the left). We further found that aberrant [oxy-Hb] activation differs according to the time period during the task or according to brain location. Our findings indicate more detailed aberrant prefrontal and temporal activation patterns of ADHD compared with those in previous studies, possibly representing a biological marker for ADHD.

Altered functional organization within the insular cortex in adult males with high-functioning autism spectrum disorder: evidence from connectivity-based parcellation

Background

The insular cortex comprises multiple functionally differentiated sub-regions, each of which has different patterns of connectivity with other brain regions. Such diverse connectivity patterns are thought to underlie a wide range of insular functions, including cognitive, affective, and sensorimotor processing, many of which are abnormal in autism spectrum disorder (ASD). Although past neuroimaging studies of ASD have shown structural and functional abnormalities in the insula, possible alterations in the sub-regional organization of the insula and the functional characteristics of each sub-region have not been examined in the ASD brain.

Methods

Resting-state functional magnetic resonance imaging (rs-fMRI) data were acquired from 36 adult males with ASD and 38 matched typically developed (TD) controls. A data-driven clustering analysis was applied to rs-fMRI data of voxels in the left and right insula to automatically group voxels with similar intrinsic connectivity pattern into a cluster. After determining the optimal number of clusters based on information theoretic measures of variation of information and mutual information, functional parcellation patterns in both the left and the right insula were compared between the TD and ASD groups. Furthermore, functional profiles of each sub-region were meta-analytically decoded using Neurosynth and were compared between the groups.

Results

We observed notable alterations in the anterior sector of the left insula and the middle ventral sub-region of the right insula in the ASD brain. Meta-analytic decoding revealed that whereas the anterior sector of the left insula contained two functionally differentiated sub-regions for cognitive, sensorimotor, and emotional/affective functions in TD brain, only a single functional cluster for cognitive and sensorimotor functions was identified in the anterior sector in the ASD brain. In the right insula, the middle ventral sub-region, which is primarily specialized for sensory- and auditory-related functions, showed a significant volumetric increase in the ASD brain compared with the TD brain.

Conclusions

The results indicate an altered organization of sub-regions in specific parts of the left and right insula of the ASD brain. The alterations in the left and right insula may constitute neural substrates underlying abnormalities in emotional/affective and sensory functions in ASD.

Electronic supplementary material

The online version of this article (doi:10.1186/s13229-016-0106-8) contains supplementary material, which is available to authorized users.

Altered effects of perspective-taking on functional connectivity during self- and other-referential processing in adults with autism spectrum disorder

In interactive social situations, it is often crucial to be able to take another person's perspective when evaluating one's own or another person's specific trait; individuals with autism spectrum disorder (ASD) critically lack this social skill. To examine how perspective-dependent self- and other-evaluation processes modulate functional connectivity in ASD, we conducted a functional magnetic resonance imaging study in which 26 high-functioning adults with ASD and 24 typically developed (TD) controls were asked to decide whether an adjective describing a personality trait correctly described the participant himself/herself ("self") or the participant's mother ("other") by taking either the first (1P) or third person (3P) perspective. We observed that functional connectivity between the left sensorimotor cortex and the left middle cingulate cortex was enhanced in TD control individuals taking the 3P perspective, this enhancement was significantly reduced in ASD, and the degree of reduction was significantly correlated with the severity of autistic traits. Furthermore, the self-reference effect on functional connectivity between the left inferior frontal cortex and frontopolar cortices was significantly enhanced in TD control individuals taking the 3P perspective, whereas such effect was reversed in ASD. These findings indicate altered effects of perspective on the functional connectivity, which may underlie the deficits in social interaction and communication observed in individuals with ASD.

Linked alterations in gray and white matter morphology in adults with high-functioning autism spectrum disorder: a multimodal brain imaging study

Growing evidence suggests that a broad range of behavioral anomalies in people with autism spectrum disorder (ASD) can be linked with morphological and functional alterations in the brain. However, the neuroanatomical underpinnings of ASD have been investigated using either structural magnetic resonance imaging (MRI) or diffusion tensor imaging (DTI), and the relationships between abnormalities revealed by these two modalities remain unclear. This study applied a multimodal data-fusion method, known as linked independent component analysis (ICA), to a set of structural MRI and DTI data acquired from 46 adult males with ASD and 46 matched controls in order to elucidate associations between different aspects of atypical neuroanatomy of ASD. Linked ICA identified two composite components that showed significant between-group differences, one of which was significantly correlated with age. In the other component, participants with ASD showed decreased gray matter (GM) volumes in multiple regions, including the bilateral fusiform gyri, bilateral orbitofrontal cortices, and bilateral pre- and post-central gyri. These GM changes were linked with a pattern of decreased fractional anisotropy (FA) in several white matter tracts, such as the bilateral inferior longitudinal fasciculi, bilateral inferior fronto-occipital fasciculi, and bilateral corticospinal tracts. Furthermore, unimodal analysis for DTI data revealed significant reductions of FA along with increased mean diffusivity in those tracts for ASD, providing further evidence of disrupted anatomical connectivity. Taken together, our findings suggest that, in ASD, alterations in different aspects of brain morphology may co-occur in specific brain networks, providing a comprehensive view for understanding the neuroanatomy of this disorder.

•

Structural alterations of gray (GM) and white matter (WM) in ASD were investigated.

•

Linked independent component analysis was used for multimodal data analysis.

•

Alterations of GM and WM in ASD co-occurred in cognitive and affective networks.

•

Results reveal an integrative view of multiple aspects of structural changes in ASD.

Altered network topologies and hub organization in adults with autism: a resting-state fMRI study

Recent functional magnetic resonance imaging (fMRI) studies on autism spectrum condition (ASC) have identified dysfunctions in specific brain networks involved in social and non-social cognition that persist into adulthood. Although increasing numbers of fMRI studies have revealed atypical functional connectivity in the adult ASC brain, such functional alterations at the network level have not yet been fully characterized within the recently developed graph-theoretical framework. Here, we applied a graph-theoretical analysis to resting-state fMRI data acquired from 46 adults with ASC and 46 age- and gender-matched controls, to investigate the topological properties and organization of autistic brain network. Analyses of global metrics revealed that, relative to the controls, participants with ASC exhibited significant decreases in clustering coefficient and characteristic path length, indicating a shift towards randomized organization. Furthermore, analyses of local metrics revealed a significantly altered organization of the hub nodes in ASC, as shown by analyses of hub disruption indices using multiple local metrics and by a loss of "hubness" in several nodes (e.g., the bilateral superior temporal sulcus, right dorsolateral prefrontal cortex, and precuneus) that are critical for social and non-social cognitive functions. In particular, local metrics of the anterior cingulate cortex consistently showed significant negative correlations with the Autism-Spectrum Quotient score. Our results demonstrate altered patterns of global and local topological properties that may underlie impaired social and non-social cognition in ASC.

Altered orbitofrontal sulcogyral patterns in adult males with high-functioning autism spectrum disorders

Functions of the orbitofrontal cortex include diverse social, cognitive and affective processes, many of which are abnormal in autism spectrum disorders (ASDs). Recently, altered orbitofrontal sulcogyral patterns have been revealed in several psychiatric conditions, such as schizophrenia, indicating a possibility that altered orbitofrontal sulcogyral morphology reflects abnormal neurodevelopment. However, the presence of sulcal alterations in ASD remains unexplored. Using structural magnetic resonance imaging, subtypes of the 'H-shaped' sulcus (Type I, II and III, in order of frequency), posterior orbital sulcus (POS) and intermediate orbital sulcus were identified in each hemisphere of adult males with ASD (n = 51) and matched normal controls (n = 55) based on the study by Chiavaras and Petrides. ASD showed a significantly altered distribution of H-shaped sulcal subtypes in both hemispheres, with a significant increase of Type III. A significant alteration in the distribution of sulcal subtypes was also identified in the right hemisphere POS of ASD. Categorical regression analysis revealed that Type I and II expressions predicted a reduced total Autism-Spectrum Quotient score. Furthermore, Type I expression was associated with a reduced 'attention to detail' subscale score. The results demonstrate that altered sulcogyral morphology can be a marker for abnormal neurodevelopment leading to the increased risk of developing autism.