scholarly journals Resting state EEG in youth with ASD: age, sex, and relation to phenotype

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Emily Neuhaus ◽  
Sarah J. Lowry ◽  
Megha Santhosh ◽  
Anna Kresse ◽  
Laura A. Edwards ◽  
...  
Keyword(s):  
Individual Differences ◽  
Resting State ◽  
Repetitive Behavior ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Neural Activation ◽  
Alpha Power ◽  
Linear Regression Models ◽  
Biological Sex ◽  
Research Risks

Abstract Background Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy. Methods We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations. Results Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD. Conclusions Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.

scholarly journals Graph Ricci Curvatures Reveal Disease-related Changes in Autism Spectrum Disorder

2021 ◽  
Author(s):  
Pavithra Elumalai ◽  
Yasharth Yadav ◽  
Nitin Williams ◽  
Emil Saucan ◽  
Jürgen Jost ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Resting State ◽  
Neurodevelopmental Disorders ◽  
Data Exchange ◽  
Meta Analysis ◽  
Resting State Fmri ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
The Brain

Autism Spectrum Disorder (ASD) is a set of neurodevelopmental disorders that pose a significant global health burden. Measures from graph theory have been used to characterise ASD-related changes in resting-state fMRI functional connectivity networks (FCNs), but recently developed geometry-inspired measures have not been applied so far. In this study, we applied geometry-inspired graph Ricci curvatures to investigate ASD-related changes in resting-state fMRI FCNs. To do this, we applied Forman-Ricci and Ollivier-Ricci curvatures to compare networks of ASD and healthy controls (N = 1112) from the Autism Brain Imaging Data Exchange I (ABIDE-I) dataset. We performed these comparisons at the brain-wide level as well as at the level of individual brain regions, and further, determined the behavioral relevance of region-specific differences with Neurosynth meta-analysis decoding. We found brain-wide ASD-related differences for both Forman-Ricci and Ollivier-Ricci curvatures. For Forman-Ricci curvature, these differences were distributed across 83 of the 200 brain regions studied, and concentrated within the Default Mode, Somatomotor and Ventral Attention Network. Meta-analysis decoding identified the brain regions showing curvature differences as involved in social cognition, memory, language and movement. Notably, comparison with results from previous non-invasive stimulation (TMS/tDCS) experiments revealed that the set of brain regions showing curvature differences overlapped with the set of brain regions whose stimulation resulted in positive cognitive or behavioural outcomes in ASD patients. These results underscore the utility of geometry-inspired graph Ricci curvatures in characterising disease-related changes in ASD, and possibly, other neurodevelopmental disorders.

Individual Differences in Mental Imagery Modulate Effective Connectivity of Scene-Selective Regions During Resting State

2021 ◽  
Author(s):  
Maria Giulia Tullo ◽  
Hannes Almgren ◽  
Frederik Van de Steen ◽  
Valentina Sulpizio ◽  
Daniele Marinazzo ◽  
...  
Keyword(s):  
Individual Differences ◽  
Mental Imagery ◽  
Resting State ◽  
Effective Connectivity ◽  
Relevant Information ◽  
Brain Regions ◽  
Intrinsic Activity ◽  
Inhibitory Influence ◽  
Cortical Regions ◽  
Intrinsic Fluctuation

Abstract Successful navigation relies on the ability to identify, perceive, and correctly process the spatial structure of a scene. It is well known that visual mental imagery plays a crucial role in navigation. Indeed, cortical regions encoding navigationally relevant information are also active during mental imagery of navigational scenes. However, it remains unknown whether their intrinsic activity and connectivity reflect the individuals’ ability to imagine a scene. Here, we primarily investigated the intrinsic causal interactions among scene-selective brain regions such as Parahipoccampal Place Area (PPA), Retrosplenial Complex (RSC), and Occipital Place Area (OPA) using Dynamic Causal Modelling (DCM) for resting-state functional magnetic resonance (rs-fMRI) data. Second, we tested whether resting-state effective connectivity parameters among scene-selective regions could reflect individual differences in mental imagery in our sample, as assessed by the self-reported Vividness of Visual Imagery Questionnaire (VVIQ). We found an inhibitory influence of occipito-medial on temporal regions, and an excitatory influence of more anterior on more medial and posterior brain regions. Moreover, we found that a key role in imagery is played by the connection strength from OPA to PPA, especially in the left hemisphere, since the influence of the signal between these scene-selective regions positively correlated with good mental imagery ability. Our investigation contributes to the understanding of the complexity of the causal interaction among brain regions involved in navigation and provides new insight in understanding how an essential ability, such as mental imagery, can be explained by the intrinsic fluctuation of brain signal.

scholarly journals Identification of a β-Arrestin 2 Mutation Related to Autism by Whole-Exome Sequencing

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Yunfei Tang ◽  
Yamei Liu ◽  
Lei Tong ◽  
Shini Feng ◽  
Dongshu Du ◽  
...  
Keyword(s):  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Developmental Stages ◽  
De Novo ◽  
Repetitive Behavior ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Potential Contribution ◽  
De Novo Mutations ◽  
Whole Exome

Autism spectrum disorder (ASD) is a complex neurological disease characterized by impaired social communication and interaction skills, rigid behavior, decreased interest, and repetitive activities. The disease has a high degree of genetic heterogeneity, and the genetic cause of ASD in many autistic individuals is currently unclear. In this study, we report a patient with ASD whose clinical features included social interaction disorder, communication disorder, and repetitive behavior. We examined the patient’s genetic variation using whole-exome sequencing technology and found new de novo mutations. After analysis and evaluation, ARRB2 was identified as a candidate gene. To study the potential contribution of the ARRB2 gene to the human brain development and function, we first evaluated the expression profile of this gene in different brain regions and developmental stages. Then, we used weighted gene coexpression network analysis to analyze the associations between ARRB2 and ASD risk genes. Additionally, the spatial conformation and stability of the ARRB2 wild type and mutant proteins were examined by simulations. Then, we further established a mouse model of ASD. The results showed abnormal ARRB2 expression in the mouse ASD model. Our study showed that ARRB2 may be a risk gene for ASD, but the contribution of de novo ARRB2 mutations to ASD is unclear. This information will provide references for the etiology of ASD and aid in the mechanism-based drug development and treatment.

scholarly journals Sex-dependent and sex-independent brain resting-state functional connectivity in children with autism spectrum disorder

2016 ◽  
Author(s):  
Xin Di ◽  
Bharat B Biswal
Keyword(s):  
Autism Spectrum Disorder ◽  
Functional Connectivity ◽  
Resting State ◽  
Data Exchange ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Imaging Data ◽  
Resting State Functional Connectivity ◽  
Main Effects

Background: Males are more likely to suffer from autism spectrum disorder (ASD) than females. As to whether females with ASD have similar brain alterations remain an open question. The current study aimed to examine sex-dependent as well as sex-independent alterations in resting-state functional connectivity in individuals with ASD compared with typically developing (TD) individuals. Method: Resting-state functional MRI data were acquired from the Autism Brain Imaging Data Exchange (ABIDE). Subjects between 6 to 20 years of age were included for analysis. After matching the intelligence quotient between groups for each dataset, and removing subjects due to excessive head motion, the resulting effective sample contained 28 females with ASD, 49 TD females, 129 males with ASD, and 141 TD males, with a two (diagnosis) by two (sex) design. Functional connectivity among 153 regions of interest (ROIs) comprising the whole brain was computed. Two by two analysis of variance was used to identify connectivity that showed diagnosis by sex interaction or main effects of diagnosis. Results: The main effects of diagnosis were found mainly between visual cortex and other brain regions, indicating sex-independent connectivity alterations. We also observed two connections whose connectivity showed diagnosis by sex interaction between the precuneus and medial cerebellum as well as the precunes and dorsal frontal cortex. While males with ASD showed higher connectivity in these connections compared with TD males, females with ASD had lower connectivity than their counterparts. Conclusions: Both sex-dependent and sex-independent functional connectivity alterations are present in ASD.

scholarly journals Inter-individual differences in pain anticipation and pain perception in migraine: Neural correlates of migraine frequency and cortisol-to-dehydroepiandrosterone sulfate (DHEA-S) ratio

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0261570
Author(s):  
Gyöngyi Kökönyei ◽  
Attila Galambos ◽  
Natália Kocsel ◽  
Edina Szabó ◽  
Andrea Edit Édes ◽  
...  
Keyword(s):  
Individual Differences ◽  
Allostatic Load ◽  
Pain Perception ◽  
Dehydroepiandrosterone Sulfate ◽  
Brain Regions ◽  
Episodic Migraine ◽  
Neural Activation ◽  
Migraine Frequency ◽  
Two Phases ◽  
The Brain

Previous studies targeting inter-individual differences in pain processing in migraine mainly focused on the perception of pain. Our main aim was to disentangle pain anticipation and perception using a classical fear conditioning task, and investigate how migraine frequency and pre-scan cortisol-to-dehydroepiandrosterone sulfate (DHEA-S) ratio as an index of neurobiological stress response would relate to neural activation in these two phases. Functional Magnetic Resonance Imaging (fMRI) data of 23 participants (18 females; mean age: 27.61± 5.36) with episodic migraine without aura were analysed. We found that migraine frequency was significantly associated with pain anticipation in brain regions comprising the midcingulate and caudate, whereas pre-scan cortisol-to DHEA-S ratio was related to pain perception in the pre-supplementary motor area (pre-SMA). Both results suggest exaggerated preparatory responses to pain or more general to stressors, which may contribute to the allostatic load caused by stressors and migraine attacks on the brain.

scholarly journals Early patterns of functional brain development associated with autism spectrum disorder in tuberous sclerosis complex

2019 ◽  
Author(s):  
Abigail Dickinson ◽  
Kandice J. Varcin ◽  
Mustafa Sahin ◽  
Charles A. Nelson ◽  
Shafali S. Jeste
Keyword(s):  
Brain Development ◽  
Tuberous Sclerosis ◽  
Tuberous Sclerosis Complex ◽  
Genetic Disorder ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Alpha Phase ◽  
Cognitive Outcomes ◽  
Alpha Power ◽  
Network Function

Lay AbstractAround half of infants with tuberous sclerosis complex (TSC) develop autism. Here, using EEG, we find that there is a reduction in communication between brain regions during infancy in TSC, and that the infants who show the largest reductions are those who later develop autism. Being able to identify infants who show early signs of disrupted brain development may improve the timing of early prediction and interventions in TSC, and also help us to understand how early brain changes lead to autism.AbstractTuberous sclerosis complex (TSC) is a rare genetic disorder that confers a high risk for autism spectrum disorders (ASD), with behavioral predictors of ASD emerging early in life. Deviations in structural and functional neuronal connectivity are highly implicated in both TSC and ASD.For the first time, we explore whether electroencephalographic (EEG) measures of network function precede or predict the emergence of ASD in TSC. We determine whether altered brain function (1) is present in infancy in TSC, (2) differentiates infants with TSC based on ASD diagnostic status, and (3) is associated with later cognitive function.We studied 35 infants with TSC (N=35), and a group of typically developing infants (n=20) at 12 and 24 months of age. Infants with TSC were later subdivided into ASD and non-ASD groups based on clinical evaluation. We measured features of spontaneous alpha oscillations (6-12Hz) that are closely associated with neural network development: alpha power, alpha phase coherence (APC) and peak alpha frequency (PAF).Infants with TSC demonstrated reduced interhemispheric APC compared to controls at 12 months of age, and these differences were found to be most pronounced at 24 months in the infants who later developed ASD. Across all infants, PAF at 24 months was associated with verbal and non-verbal cognition at 36 months.Associations between early network function and later neurodevelopmental and cognitive outcomes highlight the potential utility of early scalable EEG markers to identify infants with TSC requiring additional targeted intervention initiated very early in life.

scholarly journals Longitudinal Changes in Cortical Thickness in Adolescents with Autism Spectrum Disorder and Their Association with Restricted and Repetitive Behaviors

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 2024
Author(s):  
Valentina Bieneck ◽  
Anke Bletsch ◽  
Caroline Mann ◽  
Tim Schäfer ◽  
Hanna Seelemeyer ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Individual Differences ◽  
Cortical Thickness ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Developmental Trajectory ◽  
Repetitive Behaviors ◽  
Spectrum Disorder ◽  
Childhood And Adolescence ◽  
Autism Symptoms

The neuroanatomy of autism spectrum disorder (ASD) shows highly heterogeneous developmental trajectories across individuals. Mapping atypical brain development onto clinical phenotypes, and establishing their molecular underpinnings, is therefore crucial for patient stratification and subtyping. In this longitudinal study we examined intra- and inter-individual differences in the developmental trajectory of cortical thickness (CT) in childhood and adolescence, and their genomic underpinnings, in 33 individuals with ASD and 37 typically developing controls (aged 11–18 years). Moreover, we aimed to link regional atypical CT development to intra-individual variations in restricted and repetitive behavior (RRB) over a two-year time period. Individuals with ASD showed significantly reduced cortical thinning in several of the brain regions functionally related to wider autism symptoms and traits (e.g., fronto-temporal and cingulate cortices). The spatial patterns of the neuroanatomical differences in CT were enriched for genes known to be associated with ASD at a genetic and transcriptomic level. Further, intra-individual differences in CT correlated with within-subject variability in the severity of RRBs. Our findings represent an important step towards characterizing the neuroanatomical underpinnings of ASD across development based upon measures of CT. Moreover, our findings provide important novel insights into the link between microscopic and macroscopic pathology in ASD, as well as their relationship with different clinical ASD phenotypes.

scholarly journals Overt social interaction and resting state in young adult males with autism: core and contextual neural features

2018 ◽  
Author(s):  
Kyle Jasmin ◽  
Stephen J. Gotts ◽  
Y. Xu ◽  
S. Liu ◽  
Cameron Riddell ◽  
...  
Keyword(s):  
Intellectual Disability ◽  
Resting State ◽  
Temporal Correlation ◽  
Brain Regions ◽  
Autism Spectrum ◽  
Adult Males ◽  
Language Abilities ◽  
Social Demand ◽  
Face To Face ◽  
Social Processing

AbstractConversation is an important and ubiquitous social behavior. Individuals with Autism Spectrum Disorder (autism) without intellectual disability often have normal structural language abilities but deficits in social aspects of communication like pragmatics, prosody, and eye contact. Previous studies of resting state activity suggest that intrinsic connections among neural circuits involved with social processing are disrupted in autism, but to date no neuroimaging study has examined neural activity during the most commonplace yet challenging social task: spontaneous conversation. Here we used functional MRI to scan autistic males (N=19) without intellectual disability and age- and IQ-matched typically developing controls (N=20) while they engaged in a total of 193 face-to-face interactions. Participants completed two kinds of tasks: Conversation, which had high social demand, and Repetition, which had low social demand. Autistic individuals showed abnormally increased task-driven inter-regional temporal correlation relative to controls, especially among social processing regions and during high social demand. Furthermore, these increased correlations were associated with parent ratings of participants’ social impairments. These results were then compared with previously-acquired resting-state data (56 Autism, 62 Control participants). While some inter-regional correlation levels varied by task or rest context, others were strikingly similar across both task and rest, namely increased correlation among the thalamus, dorsal and ventral striatum, somatomotor, temporal and prefrontal cortex in the autistic individuals, relative to the control groups. These results suggest a basic distinction. Autistic cortico-cortical interactions vary by context, tending to increase relative to controls during Task and decrease during Rest. In contrast, striato- and thalamocortical relationships with socially engaged brain regions are increased in both Task and Rest, and may be core to the condition of autism.

scholarly journals Shared Characteristics of Intrinsic Connectivity Networks Underlying Interoceptive Awareness and Empathy

2020 ◽  
Vol 14 ◽  
Author(s):  
Teodora Stoica ◽  
Brendan Depue
Keyword(s):  
Resting State ◽  
Brain Regions ◽  
Cognitive Empathy ◽  
Autism Spectrum ◽  
Interoceptive Awareness ◽  
Affective Empathy ◽  
Resting State Functional Connectivity ◽  
Increased Sensitivity ◽  
Intrinsic Connectivity Networks ◽  
The Right

Awareness of internal bodily sensations (interoceptive awareness; IA) and its connection to complex socioemotional abilities like empathy has been postulated, yet the functional neural circuitry they share remains poorly understood. The present fMRI study employs independent component analysis (ICA) to investigate which empathy facet (Cognitive or Affective) shares resting-state functional connectivity (rsFC) and/or BOLD variability (rsBOLD) with IA. Healthy participants viewed an abstract nonsocial movie demonstrated to evoke strong rsFC in brain networks resembling rest (InScapes), and resultant rsFC and rsBOLD data were correlated with self-reported empathy and IA questionnaires. We demonstrate a bidirectional behavioral and neurobiological relationship between empathy and IA, depending on the type of empathy interrogated: Affective empathy and IA share both rsFC and rsBOLD, while Cognitive empathy and IA only share rsBOLD. Specifically, increased rsFC in the right inferior frontal operculum (rIFO) of a larger attention network was associated with increased vicarious experience but decreased awareness of inner body sensations. Furthermore, increased rsBOLD between brain regions of an interoceptive network was related to increased sensitivity to internal sensations along with decreased Affective empathy. Finally, increased rsBOLD between brain regions subserving a mentalizing network related to not only an improved ability to take someone’s perspective, but also a better sense of mind-body interconnectedness. Overall, these findings suggest that the awareness of one’s own internal body changes (IA) is related to the socioemotional ability of feeling and understanding another’s emotional state (empathy) and critically, that this relationship is reflected in the brain’s resting state neuroarchitecture. Methodologically, this work highlights the importance of utilizing rsBOLD as a complementary window alongside rsFC to better understand neurological phenomena. Our results may be beneficial in aiding diagnosis in clinical populations such as autism spectrum disorder (ASD), where participants may be unable to complete tasks or questionnaires due to the severity of their symptoms.

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