Autism spectrum disorder: does neuroimaging support the DSM-5 proposal for a symptom dyad? A systematic review of functional magnetic resonance imaging and diffusion tensor imaging studies

An Umbrella Review of the Fusion of fMRI and AI in Autism

The role of functional magnetic resonance imaging (fMRI) is assuming an increasingly central role in autism diagnosis. The integration of Artificial Intelligence (AI) into the realm of applications further contributes to its development. This study's objective is to analyze emerging themes in this domain through an umbrella review, encompassing systematic reviews. The research methodology was based on a structured process for conducting a literature narrative review, using an umbrella review in PubMed and Scopus. Rigorous criteria, a standard checklist, and a qualification process were meticulously applied. The findings include 20 systematic reviews that underscore key themes in autism research, particularly emphasizing the significance of technological integration, including the pivotal roles of fMRI and AI. This study also highlights the enigmatic role of oxytocin. While acknowledging the immense potential in this field, the outcome does not evade acknowledging the significant challenges and limitations. Intriguingly, there is a growing emphasis on research and innovation in AI, whereas aspects related to the integration of healthcare processes, such as regulation, acceptance, informed consent, and data security, receive comparatively less attention. Additionally, the integration of these findings into Personalized Medicine (PM) represents a promising yet relatively unexplored area within autism research. This study concludes by encouraging scholars to focus on the critical themes of health domain integration, vital for the routine implementation of these applications.

Diversity and Classification of Genetic Variations in Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a neurodevelopmental condition with symptoms that affect the whole personality and all aspects of life. Although there is a high degree of heterogeneity in both its etiology and its characteristic behavioral patterns, the disorder is well-captured along the autistic triad. Currently, ASD status can be confirmed following an assessment of behavioral features, but there is a growing emphasis on conceptualizing autism as a spectrum, which allows for establishing a diagnosis based on the level of support need, free of discrete categories. Since ASD has a high genetic predominance, the number of genetic variations identified in the background of the condition is increasing exponentially as genetic testing methods are rapidly evolving. However, due to the huge amount of data to be analyzed, grouping the different DNA variations is still challenging. Therefore, in the present review, a multidimensional classification scheme was developed to accommodate most of the currently known genetic variants associated with autism. Genetic variations have been grouped according to six criteria (extent, time of onset, information content, frequency, number of genes involved, inheritance pattern), which are themselves not discrete categories, but form a coherent continuum in line with the autism spectrum approach.

Classification of autism based on short-term spontaneous hemodynamic fluctuations using an adaptive graph neural network

BACKGROUND

Short-term spontaneous hemodynamic fluctuations were collected by the functional near-infrared spectroscopy (fNIRS) system to classify children with autism spectrum disorder (ASD) and typical development (TD), and to explore abnormalities in the left inferior frontal gyrus in ASD.

METHODS

Using the fNIRS data of 25 children with ASD and 22 children with TD, a graph neural network combined with the temporal convolution module and the graph convolution module was used, to extract the spatio-temporal features of the data and achieve accurate classification of ASD.

RESULTS

The graph neural network was used to obtain a good classification result in the left inferior frontal gyrus, with an accuracy of 97.1%, precision of 95.1%, and specificity of 93.4%. It was found that the 5th channel (which is located in BA 10) and the 8th channel (which is located in BA 47) in the left inferior frontal gyrus were closely correlated with ASD.

COMPARISON WITH PREVIOUSLY USED METHOD(S)

Compared with the previous deep learning model using the same input, the accuracy of our model has increased by up to 13%, and the correlation between channels in the left inferior frontal gyrus area with the best classification effect was explored through the graph neural network.

CONCLUSION

The adaptive graph neural network (AGNN) model may be able to mine more valuable information to distinguish ASD from TD and in addition, the left inferior frontal gyrus may have greater investigative value.

Role of cortical excitatory/inhibitory imbalance in autism spectrum disorders from a symptom severity trajectories framework: a study protocol

BACKGROUND

There is considerable evidence reporting an excitatory/inhibitory (E/I) cortical imbalance in autism spectrum disorders (ASD). However, previous findings on the direction of this imbalance and its relationship to ASD symptomatology are heterogeneous. Some factors contributing to these mixed results might be the methodological differences between studies assessing the E/I ratio and the intrinsic variability within the autistic spectrum. Studying the evolution of ASD symptoms and the factors that modulate it might help to explain and reduce this variability. Here we present a study protocol to explore the longitudinal role of E/I imbalance in ASD symptoms, combining different approaches to measure the E/I ratio and using the trajectories of symptom severity as a framework.

METHODS

This observational two time-point prospective study assesses the E/I ratio and the evolution of the behavioural symptoms in a sample of at least 98 participants with ASD. Participants are enrolled at 12 to 72 months of age and followed from 18 to 48 months after. A comprehensive battery of tests is applied to evaluate ASD clinical symptoms. The E/I ratio is approached from electrophysiology, magnetic resonance, and genetics. We will calculate the individual change for the main ASD symptoms and, based on that, we will define the trajectories of symptom severity. Then, we will investigate the correlation between measures of excitation/inhibition balance and autistic symptomatology cross-sectionally, as well as the ability of these measurements to predict changes in symptoms over time.

DISCUSSION

This study presents a robust multisystemic approach to the E/I imbalance theory in autism and its relation to divergent symptom trajectories. That setting will allow us to relate and compare the neurobiological information coming from different sources and its impact on behavioural symptoms while accounting for the high variability in ASD. The findings derived from this study could contribute to the ASD biomarkers research and might provide valuable evidence for the development of more personalized treatments in ASD.

Altered intrinsic brain activity and connectivity in unaffected parents of individuals with autism spectrum disorder: a resting-state fMRI study

Objectives: Autism spectrum disorder (ASD) is a juvenile onset neurodevelopmental disorder with social impairment and stereotyped behavior as the main symptoms. Unaffected relatives may also exhibit similar ASD features due to genetic factors. Although previous studies have demonstrated atypical brain morphological features as well as task-state brain function abnormalities in unaffected parents with ASD children, it remains unclear the pattern of brain function in the resting state.

Methods: A total of 42 unaffected parents of ASD children (pASD) and 39 age-, sex-, and handedness-matched controls were enrolled. Multiple resting-state fMRI (rsfMRI) analyzing methods were applied, including amplitude of low-frequency fluctuation (ALFF), regional homogeneity (ReHo), degree centrality (DC), and functional connectivity (FC), to reveal the functional abnormalities of unaffected parents in ASD-related brain regions. Spearman Rho correlation analysis between imaging metric values and the severity of ASD traits were evaluated as well.

Results: ALFF, ReHo, and DC methods all revealed abnormal brain regions in the pASD group, such as the left medial orbitofrontal cortex (mOFC) and rectal gyrus (ROI-1), bilateral supplementary motor area (ROI-2), right caudate nucleus head and right amygdala/para-hippocampal gyrus (ROI-3). FC decreasing was observed between ROI-1 and right anterior cingulate cortex (ACC), ROI-2, and bilateral precuneus. FC enhancing was observed between ROI-3 and right anterior cerebellar lobe, left medial temporal gyrus, left superior temporal gyrus, left medial frontal gyrus, left precentral gyrus, right postcentral gyrus in pASD. In addition, ALFF values in ROI-1, DC values in ROI-3 were positively correlated with AQ scores in pASD (ρ₁ = 0.298, P₁ = 0.007; ρ₂ = 0.220, P₂ = 0.040), while FC values between ROI-1 and right ACC were negatively correlated with AQ scores (ρ₃ = −0.334, P₃ = 0.002).

Conclusion: rsfMRI metrics could be used as biomarkers to reveal the underlying neurobiological feature of ASD for unaffected parents.

Developmental differences in neural connectivity for semantic processing in youths with autism

BACKGROUND

Youths with autism spectrum disorder (ASD) rely more on lower-level visual processing as revealed by greater occipital activation, yet less effectively engage higher-level processing of modality-independent semantic knowledge as indicated by reduced frontal activation, compared to typically developing (TD) youths. However, little is known about age-dependent differences in neural connectivity during semantic processing in youths with ASD as compared to TD youths.

METHODS

Four groups were recruited: 31 ASD children (mean age = 10.5 years old), 33 TD children (mean age = 10.4), 30 ASD adolescents (mean age = 14.9), and 34 TD adolescents (mean age = 15.1). We explored their differences in neural connectivity by using functional magnetic resonance imaging (fMRI) with psychophysiological interaction (PPI) during semantic judgments.

RESULTS

In comparison with TD children, children with ASD showed greater activation in the left cuneus and weaker connectivity between the left cuneus and left middle temporal gyrus (MTG). In comparison with TD adolescents, adolescents with ASD showed less activation in the left inferior frontal gyrus (IFG) and weaker functional connectivity between the left IFG and left MTG.

CONCLUSIONS

Children with ASD may rely more on visual processes in the occipital cortex that are disconnected from modality-independent semantics in the temporal cortex. However, adolescents with ASD may less effectively engage frontal mechanisms involved in the top-down control of modality-independent semantic knowledge in the temporal cortex. Our findings provide evidence of developmental differences in the neural substrates of the alterations in semantic processing in youths with ASD compared to TD youths.

Critical aspects of neurodevelopment

Organisms have the unique ability to adapt to their environment by making use of external inputs. In the process, the brain is shaped by experiences that go hand-in-hand with optimisation of neural circuits. As such, there exists a time window for the development of different brain regions, each unique for a particular sensory modality, wherein the propensity of forming strong, irreversible connections are high, referred to as a critical period of development. Over the years, this domain of neurodevelopmental research has garnered considerable attention from many scientists, primarily because of the intensive activity-dependent nature of development. This review discusses the cellular, molecular, and neurophysiological bases of critical periods of different sensory modalities, and the disorders associated in cases the regulators of development are dysfunctional. Eventually, the neurobiological bases of the behavioural abnormalities related to developmental pathologies are discussed. A more in-depth insight into the development of the brain during the critical period of plasticity will eventually aid in developing potential therapeutics for several neurodevelopmental disorders that are categorised under critical period disorders.

Reduced tract integrity of the model for social communication is a neural substrate of social communication deficits in autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is a neurodevelopmental disorder with social communication deficits as one of the core symptoms. Recently, a five-level model for the social communication has been proposed in which white matter tracts corresponding to each level of the model are identified. Given that the model for social communication subserves social language functions, we hypothesized that the tract integrity of the model for social communication may be reduced in ASD, and the reduction may be related to social communication deficits.

METHODS

Sixty-two right-handed boys with ASD and 55 typically developing (TD) boys received clinical evaluations, intelligence tests, the Social Communication Questionnaire (SCQ), and MRI scans. Generalized fractional anisotropy (GFA) was measured by diffusion spectrum imaging to indicate the microstructural integrity of the tracts for each level of the social communication model. Group difference in the tract integrity and its relationship with the SCQ subscales of social communication and social interaction were investigated.

RESULTS

We found that the GFA values of the superior longitudinal fasciculus III (SLF III, level 1) and the frontal aslant tracts (FAT, level 2) were decreased in ASD compared to TD. Moreover, the GFA values of the SLF III and the FAT were associated with the social interaction subscale in ASD.

CONCLUSIONS

The tract integrity of the model for social communication is reduced in ASD, and the reduction is associated with impaired social interaction. Our results support that reduced tract integrity of the model for social communication might be a neural substrate of social communication deficits in ASD.

Uncovering the Social Deficits in the Autistic Brain. A Source-Based Morphometric Study

Autism is a neurodevelopmental disorder that mainly affects social interaction and communication. Evidence from behavioral and functional MRI studies supports the hypothesis that dysfunctional mechanisms involving social brain structures play a major role in autistic symptomatology. However, the investigation of anatomical abnormalities in the brain of people with autism has led to inconsistent results. We investigated whether specific brain regions, known to display functional abnormalities in autism, may exhibit mutual and peculiar patterns of covariance in their gray-matter concentrations. We analyzed structural MRI images of 32 young men affected by autistic disorder (AD) and 50 healthy controls. Controls were matched for sex, age, handedness. IQ scores were also monitored to avoid confounding. A multivariate Source-Based Morphometry (SBM) was applied for the first time on AD and controls to detect maximally independent networks of gray matter. Group comparison revealed a gray-matter source that showed differences in AD compared to controls. This network includes broad temporal regions involved in social cognition and high-level visual processing, but also motor and executive areas of the frontal lobe. Notably, we found that gray matter differences, as reflected by SBM, significantly correlated with social and behavioral deficits displayed by AD individuals and encoded via the Autism Diagnostic Observation Schedule scores. These findings provide support for current hypotheses about the neural basis of atypical social and mental states information processing in autism.

ASD Validity

ASD research is at an important crossroads. The ASD diagnosis is important for assigning a child to early behavioral intervention and explaining a child’s condition. But ASD research has not provided a diagnosis-specific medical treatment, or a consistent early predictor, or a unified life course. If the ASD diagnosis also lacks biological and construct validity, a shift away from studying ASD-defined samples would be warranted. Consequently, this paper reviews recent findings for the neurobiological validity of ASD, the construct validity of ASD diagnostic criteria, and the construct validity of ASD spectrum features. The findings reviewed indicate that the ASD diagnosis lacks biological and construct validity. The paper concludes with proposals for research going forward.

Epilepsy and Autism

Epilepsy and autistic spectrum disorder frequently coexist in the same individual. Electroencephalogram (EEG) epileptiform activity is also present at a substantially higher rate in children with autism than normally developing children. As with epilepsy, there are a multitude of genetic and environmental factors that can result in autistic spectrum disorder. There is growing consensus from both animal and clinical studies that autism is a disorder of aberrant connectivity. As measured with functional magnetic resonance imaging (MRI) and EEG, the brain in autistic spectrum disorder may be under- or overconnected or have a mixture of over- and underconnectivity. In the case of comorbid epilepsy and autism, an imbalance of the excitatory/inhibitory (E/I) ratio in selected regions of the brain may drive overconnectivity. Understanding the mechanism by which altered connectivity in individuals with comorbid epilepsy and autistic spectrum disorder results in the behaviors specific to the autistic spectrum disorder remains a challenge.

Atypical sympathetic arousal in children with autism spectrum disorder and its association with anxiety symptomatology

Background

Autism spectrum disorder (ASD) has been associated with autonomic atypicalities, although the nature of these differences remains largely unknown. Moreover, existing literature suggests large variability in autonomic function in ASD, motivating the need to examine the existence of subgroups that exhibit more homogeneous autonomic features.

Methods

Electrodermal activity (EDA), a non-invasive physiological indicator of autonomic activity, was measured in typically developing children (n = 33) and those with ASD (n = 38) as participants performed tasks that elicit anxiety, attention, response inhibition, and social cognition processes. The ASD group was divided into low- (n = 18) and high-anxiety (n = 20) participants, and the groups were compared to mean EDA level and electrodermal reactions frequency (EDR).

Results

The ASD group had a significantly blunted mean EDA response to the anxiety tasks (p < 0.004). The EDR response to all tasks, except response inhibition, was also blunted in the ASD group (p < 0.04). For this group, EDR frequency during the anxiety and social cognition tasks was negatively correlated with behavioral scores in the domains that were probed by each task (p < 0.002). The high-anxiety ASD group showed significantly decreased mean EDA compared to both the low-anxiety ASD group (p = 0.02) and the typically developing control group (p = 0.04). The high-anxiety ASD group also had significantly more severe symptoms than the low-anxiety ASD group on domains related to anxiety, attention, rule breaking, aggression, obsessions and compulsions, and depression.

Conclusions

Our results suggest atypical autonomic function in children with ASD, specifically with respect to sympathetic activity. Moreover, anxiety symptomatology defined subgroups with distinct physiological and behavioral profiles. Overall, the results add to the body of literature supporting autonomic dysfunction in ASD and highlight the role of anxiety and autonomic features in explaining the variability in the autism spectrum.

State-Dependent Differences in Functional Connectivity in Young Children With Autism Spectrum Disorder

Background

While there is increasing evidence of altered brain connectivity in autism, the degree and direction of these alterations in connectivity and their uniqueness to autism has not been established. The aim of the present study was to compare connectivity in children with autism to that of typically developing controls and children with developmental delay without autism.

Methods

We assessed EEG spectral power, coherence, phase lag, Pearson and partial correlations, and epileptiform activity during the awake, slow wave sleep, and REM sleep states in 137 children aged 2 to 6 years with autism (n = 87), developmental delay without autism (n = 21), or typical development (n = 29).

Findings

We found that brain connectivity, as measured by coherence, phase lag, and Pearson and partial correlations distinguished children with autism from both neurotypical and developmentally delayed children. In general, children with autism had increased coherence which was most prominent during slow wave sleep.

Interpretation

Functional connectivity is distinctly different in children with autism compared to samples with typical development and developmental delay without autism. Differences in connectivity in autism are state and region related. In this study, children with autism were characterized by a dynamically evolving pattern of altered connectivity.

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We used EEG to examine the connectivity in young children in awake, rapid eye movement, and slow wave sleep (SWS) states.

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Differences in coherence between the autism group and the other groups were maximal during SWS.

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Sleep may be the most sensitive time to measure differences in neuro-development before they are observable in behavior.

Shared mechanisms underlie normal healthy sleep and normal brain development. Therefore, we suspect that differences in the way that the brain is behaving during sleep have the potential to tell us about what might be developing incorrectly in people with neurodevelopmental disorders. In addition, sleep evaluations of children allow us to filter out waking distractions, so that we are truly measuring the brain working offline. For instance, the differences in the way the brain was connected that we observed between our three study groups were by far the most notable during slow wave sleep. This finding highlights the importance of taking the state of the brain into account when commenting on the ‘connectedness’ of the brain as a potential biomarker for neurodevelopmental disorders. Future attempts to classify developmental disorders by using differences in connectivity must take into account brain state, whether awake or asleep as well as developmental stage.

Abnormal Brain Dynamics Underlie Speech Production in Children with Autism Spectrum Disorder

A large proportion of children with autism spectrum disorder (ASD) have speech and/or language difficulties. While a number of structural and functional neuroimaging methods have been used to explore the brain differences in ASD with regards to speech and language comprehension and production, the neurobiology of basic speech function in ASD has not been examined. Magnetoencephalography (MEG) is a neuroimaging modality with high spatial and temporal resolution that can be applied to the examination of brain dynamics underlying speech as it can capture the fast responses fundamental to this function. We acquired MEG from 21 children with high‐functioning autism (mean age: 11.43 years) and 21 age‐ and sex‐matched controls as they performed a simple oromotor task, a phoneme production task and a phonemic sequencing task. Results showed significant differences in activation magnitude and peak latencies in primary motor cortex (Brodmann Area 4), motor planning areas (BA 6), temporal sequencing and sensorimotor integration areas (BA 22/13) and executive control areas (BA 9). Our findings of significant functional brain differences between these two groups on these simple oromotor and phonemic tasks suggest that these deficits may be foundational and could underlie the language deficits seen in ASD. Autism Res2016, 9: 249–261. © 2015 International Society for Autism Research, Wiley Periodicals, Inc.

Interaction effect between handedness and CNTNAP2 polymorphism (rs7794745 genotype) on voice-specific frontotemporal activity in healthy individuals: an fMRI study

Recent neuroimaging studies have demonstrated that Contactin-associated protein-like2 (CNTNAP2) polymorphisms affect left-hemispheric function of language processing in healthy individuals, but no study has investigated the influence of these polymorphisms on right-hemispheric function involved in human voice perception. Further, although recent reports suggest that determination of handedness is influenced by genetic effect, the interaction effect between handedness and CNTNAP2 polymorphisms for brain activity in human voice perception and language processing has not been revealed. We aimed to investigate the interaction effect of handedness and CNTNAP2 polymorphisms in respect to brain function for human voice perception and language processing in healthy individuals. Brain function of 108 healthy volunteers (74 right-handed and 34 non-right-handed) was examined while they were passively listening to reverse sentences (rSEN), identifiable non-vocal sounds (SND), and sentences (SEN). Full factorial design analysis was calculated by using three factors: (1) rs7794745 (A/A or A/T), (2) rs2710102 [G/G or A carrier (A/G and A/A)], and (3) voice-specific response (rSEN or SND). The main effect of rs7794745 (A/A or A/T) was significantly revealed at the right middle frontal gyrus (MFG) and bilateral superior temporal gyrus (STG). This result suggests that rs7794745 genotype affects voice-specific brain function. Furthermore, interaction effect was significantly observed among MFG-STG activations by human voice perception, rs7794745 (A/A or A/T), and handedness. These results suggest that CNTNAP2 polymorphisms could be one of the important factors in the neural development related to vocal communication and language processing in both right-handed and non-right-handed healthy individuals.

Constrained spherical deconvolution-based tractography and tract-based spatial statistics show abnormal microstructural organization in Asperger syndrome

BACKGROUND

The aim of this study was to investigate potential differences in neural structure in individuals with Asperger syndrome (AS), high-functioning individuals with autism spectrum disorder (ASD). The main symptoms of AS are severe impairments in social interactions and restricted or repetitive patterns of behaviors, interests or activities.

METHODS

Diffusion weighted magnetic resonance imaging data were acquired for 14 adult males with AS and 19 age, sex and IQ-matched controls. Voxelwise group differences in fractional anisotropy (FA) were studied with tract-based spatial statistics (TBSS). Based on the results of TBSS, a tract-level comparison was performed with constrained spherical deconvolution (CSD)-based tractography, which is able to detect complex (for example, crossing) fiber configurations. In addition, to investigate the relationship between the microstructural changes and the severity of symptoms, we looked for correlations between FA and the Autism Spectrum Quotient (AQ), Empathy Quotient and Systemizing Quotient.

RESULTS

TBSS revealed widely distributed local increases in FA bilaterally in individuals with AS, most prominent in the temporal part of the superior longitudinal fasciculus, corticospinal tract, splenium of corpus callosum, anterior thalamic radiation, inferior fronto-occipital fasciculus (IFO), posterior thalamic radiation, uncinate fasciculus and inferior longitudinal fasciculus (ILF). CSD-based tractography also showed increases in the FA in multiple tracts. However, only the difference in the left ILF was significant after a Bonferroni correction. These results were not explained by the complexity of microstructural organization, measured using the planar diffusion coefficient. In addition, we found a correlation between AQ and FA in the right IFO in the whole group.

CONCLUSIONS

Our results suggest that there are local and tract-level abnormalities in white matter (WM) microstructure in our homogenous and carefully characterized group of adults with AS, most prominent in the left ILF.

Why autism must be taken apart

Although accumulated evidence has demonstrated that autism is found with many varied brain dysfunctions, researchers have tried to find a single brain dysfunction that would provide neurobiological validity for autism. However, unitary models of autism brain dysfunction have not adequately addressed conflicting evidence, and efforts to find a single unifying brain dysfunction have led the field away from research to explore individual variation and micro-subgroups. Autism must be taken apart in order to find neurobiological treatment targets. Three research changes are needed. The belief that there is a single defining autism spectrum disorder brain dysfunction must be relinquished. The noise caused by the thorny brain-symptom inference problem must be reduced. Researchers must explore individual variation in brain measures within autism.

Inflectional morphology in high-functioning autism: Evidence for speeded grammatical processing

Autism is characterized by language and communication deficits. We investigated grammatical and lexical processes in high-functioning autism by contrasting the production of regular and irregular past-tense forms. Boys with autism and typically-developing control boys did not differ in accuracy or error rates. However, boys with autism were significantly faster than controls at producing rule-governed past-tenses (slip-slipped, plim-plimmed, bring-bringed), though not lexically-dependent past-tenses (bring-brought, squeeze-squeezed, splim-splam). This pattern mirrors previous findings from Tourette syndrome attributed to abnormalities of frontal/basal-ganglia circuits that underlie grammar. We suggest a similar abnormality underlying language in autism. Importantly, even when children with autism show apparently normal language (e.g., in accuracy or with diagnostic instruments), processes and/or brain structures subserving language may be atypical in the disorder.

The neurobiology of autism spectrum disorders

Data is progressively and robustly accumulating regarding the biological basis of autism. Autism spectrum disorders (ASD) are currently considered a group of neurodevelopmental disorders with onset very early in life and a complex, heterogeneous, multifactorial aetiology. A comprehensive search of the last five years of the Medline database was conducted in order to summarize recent evidence on the neurobiological bases of autism. The main findings on genetic influence, neuropathology, neurostructure and brain networks are summarized. In addition, findings from peripheral samples of subjects with autism and animal models, which show immune, oxidative, mitochondrial dysregulations, are reported. Then, other biomarkers from very different systems associated with autism are reported. Finally, an attempt is made to try and integrate the available evidence, which points to a oligogenetic, multifactorial aetiology that converges in an aberrant micro-organization of the cortex, with abnormal functioning of the synapses and abnormalities in very general physiological pathways (such as inflammatory, immune and redox systems).

Increased coherence of white matter fiber tract organization in adults with Asperger syndrome: a diffusion tensor imaging study

To investigate whether there are global white matter (WM) differences between autistic and healthy adults, we performed diffusion tensor imaging (DTI) in 14 male adults with Asperger syndrome (AS) and 19 gender-, age-, and intelligence quotient-matched controls. We focused on individuals with high-functioning autism spectrum disorder (ASD), AS, to decrease heterogeneity caused by large variation in the cognitive profile. Previous DTI studies of ASD have mainly focused on finding local changes in fractional anisotropy (FA) and mean diffusivity (MD), two indexes used to characterize microstructural properties of WM. Although the local or voxel-based approaches may be able to provide detailed information in terms of location of the observed differences, such results are known to be highly sensitive to partial volume effects, registration errors, or placement of the regions of interest. Therefore, we performed global histogram analyses of (a) whole-brain tractography results and (b) skeletonized WM masks. In addition to the FA and MD, the planar diffusion coefficient (CP) was computed as it can provide more specific information of the complexity of the neural structure. Our main finding indicated that adults with AS had higher mean FA values than controls. A less complex neural structure in adults with AS could have explained the results, but no significant difference in CP was found. Our results suggest that there are global abnormalities in the WM tissue of adults with AS.

Concordance of white matter and gray matter abnormalities in autism spectrum disorders: a voxel-based meta-analysis study

There are at least two fundamental unanswered questions in the literature on autism spectrum disorders (ASD): Are abnormalities in white (WM) and gray matter (GM) consistent with one another? Are WM morphometric alterations consistent with alterations in the GM of regions connected by these abnormal WM bundles and vice versa? The aim of this work is to bridge this gap. After selecting voxel-based morphometry and diffusion tensor imaging studies comparing autistic and normally developing groups of subjects, we conducted an activation likelihood estimation (ALE) meta-analysis to estimate consistent brain alterations in ASD. Multidimensional scaling was used to test the similarity of the results. The ALE results were then analyzed to identify the regions of concordance between GM and WM areas. We found statistically significant topological relationships between GM and WM abnormalities in ASD. The most numerous were negative concordances, found bilaterally but with a higher prevalence in the right hemisphere. Positive concordances were found in the left hemisphere. Discordances reflected the spatial distribution of negative concordances. Thus, a different hemispheric contribution emerged, possibly related to pathogenetic factors affecting the right hemisphere during early developmental stages. Besides, WM fiber tracts linking the brain structures involved in social cognition showed abnormalities, and most of them had a negative concordance with the connected GM regions. We interpreted the results in terms of altered brain networks and their role in the pervasive symptoms dramatically impairing communication and social skills in ASD patients.

Abnormalities in fronto-striatal connectivity within language networks relate to differences in grey-matter heterogeneity in Asperger syndrome

Asperger syndrome (AS) is an Autism Spectrum Disorder (ASD) characterised by qualitative impairment in the development of emotional and social skills with relative preservation of general intellectual abilities, including verbal language. People with AS may nevertheless show atypical language, including rate and frequency of speech production. We previously observed that abnormalities in grey matter homogeneity (measured with texture analysis of structural MR images) in AS individuals when compared with controls are also correlated with the volume of caudate nucleus. Here, we tested a prediction that these distributed abnormalities in grey matter compromise the functional integrity of brain networks supporting verbal communication skills. We therefore measured the functional connectivity between caudate nucleus and cortex during a functional neuroimaging study of language generation (verbal fluency), applying psycho-physiological interaction (PPI) methods to test specifically for differences attributable to grey matter heterogeneity in AS participants. Furthermore, we used dynamic causal modelling (DCM) to characterise the causal directionality of these differences in interregional connectivity during word production. Our results revealed a diagnosis-dependent influence of grey matter heterogeneity on the functional connectivity of the caudate nuclei with right insula/inferior frontal gyrus and anterior cingulate, respectively with the left superior frontal gyrus and right precuneus. Moreover, causal modelling of interactions between inferior frontal gyri, caudate and precuneus, revealed a reliance on bottom-up (stimulus-driven) connections in AS participants that contrasted with a dominance of top-down (cognitive control) connections from prefrontal cortex observed in control participants. These results provide detailed support for previously hypothesised central disconnectivity in ASD and specify discrete brain network targets for diagnosis and therapy in ASD.

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We used MRI techniques to assess the connectivity in language networks in AS.

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Grey-matter heterogeneity of MR images correlated with volume of caudate in AS.

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Hence, caudate nuclei were used as seed ROIs in connectivity analyses: PPI, DCM.

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Grey-matter heterogeneity differently tuned caudate connectivity in AS, controls.

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DCM of language circuitry featured bottom-up models in AS and top-down in controls.

PET and MR imaging: the odd couple or a match made in heaven?

PET and MR imaging are modalities routinely used for clinical and research applications. Integrated scanners capable of acquiring PET and MR imaging data in the same session, sequentially or simultaneously, have recently become available for human use. In this article, we describe some of the technical advances that allowed the development of human PET/MR scanners; briefly discuss methodologic challenges and opportunities provided by this novel technology; and present potential oncologic, cardiac, and neuropsychiatric applications. These examples range from studies that might immediately benefit from PET/MR to more advanced applications on which future development might have an even broader impact.

AMPAKINE enhancement of social interaction in the BTBR mouse model of autism

Autism is a neurodevelopmental disorder in which the first diagnostic symptom is unusual reciprocal social interactions. Approximately half of the children diagnosed with an autism spectrum disorder also have intellectual impairments. General cognitive abilities may be fundamental to many aspects of social cognition. Cognitive enhancers could conceivably be of significant benefit to children and adults with autism. AMPAKINE compounds are a novel class of pharmacological agents that act as positive modulators of AMPA receptors to enhance excitatory glutamatergic neurotransmission. This class of compounds was reported to improve learning and memory in several rodent and non-human primate tasks, and to normalize respiratory abnormalities in a mouse model of Rett syndrome. Here we evaluate the actions of AMPA compounds in adult male and female BTBR mice, a well characterized mouse model of autism. Acute treatment with CX1837 and CX1739 reversed the deficit in sociability in BTBR mice on the most sensitive parameter, time spent sniffing a novel mouse as compared to time spent sniffing a novel object. The less sensitive parameter, time in the chamber containing the novel mouse versus time in the chamber containing the novel object, was not rescued by CX1837 or CX1739 treatment. Preliminary data with CX546, in which β-cyclodextrin was the vehicle, revealed behavioral effects of the acute intraperitoneal and oral administration of vehicle alone. To circumvent the artifacts introduced by the vehicle administration, we employed a novel treatment regimen using pellets of peanut butter for drug delivery. Absence of vehicle treatment effects when CX1837 and CX1739 were given in the peanut butter pellets, to multiple cohorts of BTBR and B6 control mice, confirmed that the pharmacologically-induced improvements in sociability in BTBR were not confounded by the administration procedures. The highest dose of CX1837 improved the cognitive deficit in novel object recognition in BTBR. No drug effects were detected on the high levels of repetitive self-grooming in BTBR. In open field tests, CX1837 and CX1739 did not induce hyperactivity or sedation in either strain. It is interesting to speculate that the ability of CX1837 and CX1739 to restore aspects of sociability in BTBR mice could utilize synaptic mechanisms regulating social cognition, suggesting a potential pharmacological target for interventions to treat symptoms of autism. This article is part of a Special Issue entitled 'Cognitive Enhancers'.

A stable pattern of EEG spectral coherence distinguishes children with autism from neuro-typical controls - a large case control study

BACKGROUND

The autism rate has recently increased to 1 in 100 children. Genetic studies demonstrate poorly understood complexity. Environmental factors apparently also play a role. Magnetic resonance imaging (MRI) studies demonstrate increased brain sizes and altered connectivity. Electroencephalogram (EEG) coherence studies confirm connectivity changes. However, genetic-, MRI- and/or EEG-based diagnostic tests are not yet available. The varied study results likely reflect methodological and population differences, small samples and, for EEG, lack of attention to group-specific artifact.

METHODS

Of the 1,304 subjects who participated in this study, with ages ranging from 1 to 18 years old and assessed with comparable EEG studies, 463 children were diagnosed with autism spectrum disorder (ASD); 571 children were neuro-typical controls (C). After artifact management, principal components analysis (PCA) identified EEG spectral coherence factors with corresponding loading patterns. The 2- to 12-year-old subsample consisted of 430 ASD- and 554 C-group subjects (n = 984). Discriminant function analysis (DFA) determined the spectral coherence factors' discrimination success for the two groups. Loading patterns on the DFA-selected coherence factors described ASD-specific coherence differences when compared to controls.

RESULTS

Total sample PCA of coherence data identified 40 factors which explained 50.8% of the total population variance. For the 2- to 12-year-olds, the 40 factors showed highly significant group differences (P < 0.0001). Ten randomly generated split half replications demonstrated high-average classification success (C, 88.5%; ASD, 86.0%). Still higher success was obtained in the more restricted age sub-samples using the jackknifing technique: 2- to 4-year-olds (C, 90.6%; ASD, 98.1%); 4- to 6-year-olds (C, 90.9%; ASD 99.1%); and 6- to 12-year-olds (C, 98.7%; ASD, 93.9%). Coherence loadings demonstrated reduced short-distance and reduced, as well as increased, long-distance coherences for the ASD-groups, when compared to the controls. Average spectral loading per factor was wide (10.1 Hz).

CONCLUSIONS

Classification success suggests a stable coherence loading pattern that differentiates ASD- from C-group subjects. This might constitute an EEG coherence-based phenotype of childhood autism. The predominantly reduced short-distance coherences may indicate poor local network function. The increased long-distance coherences may represent compensatory processes or reduced neural pruning. The wide average spectral range of factor loadings may suggest over-damped neural networks.