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Antonioni A, Raho EM, Straudi S, Granieri E, Koch G, Fadiga L. The cerebellum and the Mirror Neuron System: A matter of inhibition? From neurophysiological evidence to neuromodulatory implications. A narrative review. Neurosci Biobehav Rev 2024; 164:105830. [PMID: 39069236 DOI: 10.1016/j.neubiorev.2024.105830] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2024] [Revised: 07/20/2024] [Accepted: 07/24/2024] [Indexed: 07/30/2024]
Abstract
Mirror neurons show activity during both the execution (AE) and observation of actions (AO). The Mirror Neuron System (MNS) could be involved during motor imagery (MI) as well. Extensive research suggests that the cerebellum is interconnected with the MNS and may be critically involved in its activities. We gathered evidence on the cerebellum's role in MNS functions, both theoretically and experimentally. Evidence shows that the cerebellum plays a major role during AO and MI and that its lesions impair MNS functions likely because, by modulating the activity of cortical inhibitory interneurons with mirror properties, the cerebellum may contribute to visuomotor matching, which is fundamental for shaping mirror properties. Indeed, the cerebellum may strengthen sensory-motor patterns that minimise the discrepancy between predicted and actual outcome, both during AE and AO. Furthermore, through its connections with the hippocampus, the cerebellum might be involved in internal simulations of motor programs during MI. Finally, as cerebellar neuromodulation might improve its impact on MNS activity, we explored its potential neurophysiological and neurorehabilitation implications.
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Affiliation(s)
- Annibale Antonioni
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara 44121, Italy; Department of Neuroscience, Ferrara University Hospital, Ferrara 44124, Italy; Doctoral Program in Translational Neurosciences and Neurotechnologies, University of Ferrara, Ferrara 44121, Italy.
| | - Emanuela Maria Raho
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara 44121, Italy
| | - Sofia Straudi
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara 44121, Italy; Department of Neuroscience, Ferrara University Hospital, Ferrara 44124, Italy
| | - Enrico Granieri
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara 44121, Italy
| | - Giacomo Koch
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara 44121, Italy; Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara 44121 , Italy; Non Invasive Brain Stimulation Unit, Istituto di Ricovero e Cura a Carattere Scientifico Santa Lucia, Rome 00179, Italy
| | - Luciano Fadiga
- Department of Neuroscience and Rehabilitation, University of Ferrara, Ferrara 44121, Italy; Center for Translational Neurophysiology of Speech and Communication (CTNSC), Italian Institute of Technology (IIT), Ferrara 44121 , Italy
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Yang D, Svoboda AM, George TG, Mansfield PK, Wheelock MD, Schroeder ML, Rafferty SM, Sherafati A, Tripathy K, Burns-Yocum T, Forsen E, Pruett JR, Marrus NM, Culver JP, Constantino JN, Eggebrecht AT. Mapping neural correlates of biological motion perception in autistic children using high-density diffuse optical tomography. Mol Autism 2024; 15:35. [PMID: 39175054 PMCID: PMC11342641 DOI: 10.1186/s13229-024-00614-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2024] [Accepted: 07/31/2024] [Indexed: 08/24/2024] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD), a neurodevelopmental disorder defined by social communication deficits plus repetitive behaviors and restricted interests, currently affects 1/36 children in the general population. Recent advances in functional brain imaging show promise to provide useful biomarkers of ASD diagnostic likelihood, behavioral trait severity, and even response to therapeutic intervention. However, current gold-standard neuroimaging methods (e.g., functional magnetic resonance imaging, fMRI) are limited in naturalistic studies of brain function underlying ASD-associated behaviors due to the constrained imaging environment. Compared to fMRI, high-density diffuse optical tomography (HD-DOT), a non-invasive and minimally constraining optical neuroimaging modality, can overcome these limitations. Herein, we aimed to establish HD-DOT to evaluate brain function in autistic and non-autistic school-age children as they performed a biological motion perception task previously shown to yield results related to both ASD diagnosis and behavioral traits. METHODS We used HD-DOT to image brain function in 46 ASD school-age participants and 49 non-autistic individuals (NAI) as they viewed dynamic point-light displays of coherent biological and scrambled motion. We assessed group-level cortical brain function with statistical parametric mapping. Additionally, we tested for brain-behavior associations with dimensional metrics of autism traits, as measured with the Social Responsiveness Scale-2, with hierarchical regression models. RESULTS We found that NAI participants presented stronger brain activity contrast (coherent > scrambled) than ASD children in cortical regions related to visual, motor, and social processing. Additionally, regression models revealed multiple cortical regions in autistic participants where brain function is significantly associated with dimensional measures of ASD traits. LIMITATIONS Optical imaging methods are limited in depth sensitivity and so cannot measure brain activity within deep subcortical regions. However, the field of view of this HD-DOT system includes multiple brain regions previously implicated in both task-based and task-free studies on autism. CONCLUSIONS This study demonstrates that HD-DOT is sensitive to brain function that both differentiates between NAI and ASD groups and correlates with dimensional measures of ASD traits. These findings establish HD-DOT as an effective tool for investigating brain function in autistic and non-autistic children. Moreover, this study established neural correlates related to biological motion perception and its association with dimensional measures of ASD traits.
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Affiliation(s)
- Dalin Yang
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Alexandra M Svoboda
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Tessa G George
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Patricia K Mansfield
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Medical Education, Saint Louis University School of Medicine, St. Louis, MO, 63104, USA
| | - Muriah D Wheelock
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Biomedical Engineering, Washington University School of Engineering, St. Louis, MO, 63130, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Mariel L Schroeder
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Speech, Language, and Hearing Science, Purdue University, West Lafayette, IL, 47907, USA
| | - Sean M Rafferty
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
| | - Arefeh Sherafati
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Physics, Washington University School of Arts and Science, St. Louis, MO, 63130, USA
- Department of Neurology, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Kalyan Tripathy
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, 63110, USA
- University of Pittsburgh Medical Center, Western Psychiatric Hospital, Pittsburgh, PA, 15213, USA
| | - Tracy Burns-Yocum
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Evolytics, Parkville, MO, 64152, USA
| | - Elizabeth Forsen
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Doctor of Medicine Program, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - John R Pruett
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Natasha M Marrus
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Joseph P Culver
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA
- Department of Biomedical Engineering, Washington University School of Engineering, St. Louis, MO, 63130, USA
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Physics, Washington University School of Arts and Science, St. Louis, MO, 63130, USA
- Department of Electrical and System Engineering, Washington University School of Engineering, St. Louis, MO, 63112, USA
- Department Imaging Sciences Engineering, Washington University School of Engineering, St. Louis, MO, 63112, USA
| | - John N Constantino
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, 30322, USA
- Division of Behavioral and Mental Health, Children's Healthcare of Atlanta, Atlanta, GA, 30329, USA
| | - Adam T Eggebrecht
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St. Louis, MO, 63110, USA.
- Department of Biomedical Engineering, Washington University School of Engineering, St. Louis, MO, 63130, USA.
- Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Physics, Washington University School of Arts and Science, St. Louis, MO, 63130, USA.
- Department of Electrical and System Engineering, Washington University School of Engineering, St. Louis, MO, 63112, USA.
- Department Imaging Sciences Engineering, Washington University School of Engineering, St. Louis, MO, 63112, USA.
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Ibrahim K, Iturmendi-Sabater I, Vasishth M, Barron DS, Guardavaccaro M, Funaro MC, Holmes A, McCarthy G, Eickhoff SB, Sukhodolsky DG. Neural circuit disruptions of eye gaze processing in autism spectrum disorder and schizophrenia: An activation likelihood estimation meta-analysis. Schizophr Res 2024; 264:298-313. [PMID: 38215566 PMCID: PMC10922721 DOI: 10.1016/j.schres.2023.12.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 09/07/2023] [Accepted: 12/05/2023] [Indexed: 01/14/2024]
Abstract
BACKGROUND Impairment in social cognition, particularly eye gaze processing, is a shared feature common to autism spectrum disorder (ASD) and schizophrenia. However, it is unclear if a convergent neural mechanism also underlies gaze dysfunction in these conditions. The present study examined whether this shared eye gaze phenotype is reflected in a profile of convergent neurobiological dysfunction in ASD and schizophrenia. METHODS Activation likelihood estimation (ALE) meta-analyses were conducted on peak voxel coordinates across the whole brain to identify spatial convergence. Functional coactivation with regions emerging as significant was assessed using meta-analytic connectivity modeling. Functional decoding was also conducted. RESULTS Fifty-six experiments (n = 30 with schizophrenia and n = 26 with ASD) from 36 articles met inclusion criteria, which comprised 354 participants with ASD, 275 with schizophrenia and 613 healthy controls (1242 participants in total). In ASD, aberrant activation was found in the left amygdala relative to unaffected controls during gaze processing. In schizophrenia, aberrant activation was found in the right inferior frontal gyrus and supplementary motor area. Across ASD and schizophrenia, aberrant activation was found in the right inferior frontal gyrus and right fusiform gyrus during gaze processing. Functional decoding mapped the left amygdala to domains related to emotion processing and cognition, the right inferior frontal gyrus to cognition and perception, and the right fusiform gyrus to visual perception, spatial cognition, and emotion perception. These regions also showed meta-analytic connectivity to frontoparietal and frontotemporal circuitry. CONCLUSION Alterations in frontoparietal and frontotemporal circuitry emerged as neural markers of gaze impairments in ASD and schizophrenia. These findings have implications for advancing transdiagnostic biomarkers to inform targeted treatments for ASD and schizophrenia.
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Affiliation(s)
- Karim Ibrahim
- Yale University School of Medicine, Child Study Center, United States of America.
| | | | - Maya Vasishth
- Yale University School of Medicine, Child Study Center, United States of America
| | - Daniel S Barron
- Brigham and Women's Hospital, Department of Psychiatry, Anesthesiology and Pain Medicine, United States of America; Harvard Medical School, Department of Psychiatry, United States of America
| | | | - Melissa C Funaro
- Yale University, Harvey Cushing/John Hay Whitney Medical Library, United States of America
| | - Avram Holmes
- Yale University, Department of Psychology, United States of America; Yale University, Department of Psychiatry, United States of America; Yale University, Wu Tsai Institute, United States of America
| | - Gregory McCarthy
- Yale University, Department of Psychology, United States of America; Yale University, Wu Tsai Institute, United States of America
| | - Simon B Eickhoff
- Institute of Systems Neuroscience, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany; Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, Jülich, Germany
| | - Denis G Sukhodolsky
- Yale University School of Medicine, Child Study Center, United States of America
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Mosconi MW, Stevens CJ, Unruh KE, Shafer R, Elison JT. Endophenotype trait domains for advancing gene discovery in autism spectrum disorder. J Neurodev Disord 2023; 15:41. [PMID: 37993779 PMCID: PMC10664534 DOI: 10.1186/s11689-023-09511-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 11/09/2023] [Indexed: 11/24/2023] Open
Abstract
Autism spectrum disorder (ASD) is associated with a diverse range of etiological processes, including both genetic and non-genetic causes. For a plurality of individuals with ASD, it is likely that the primary causes involve multiple common inherited variants that individually account for only small levels of variation in phenotypic outcomes. This genetic landscape creates a major challenge for detecting small but important pathogenic effects associated with ASD. To address similar challenges, separate fields of medicine have identified endophenotypes, or discrete, quantitative traits that reflect genetic likelihood for a particular clinical condition and leveraged the study of these traits to map polygenic mechanisms and advance more personalized therapeutic strategies for complex diseases. Endophenotypes represent a distinct class of biomarkers useful for understanding genetic contributions to psychiatric and developmental disorders because they are embedded within the causal chain between genotype and clinical phenotype, and they are more proximal to the action of the gene(s) than behavioral traits. Despite their demonstrated power for guiding new understanding of complex genetic structures of clinical conditions, few endophenotypes associated with ASD have been identified and integrated into family genetic studies. In this review, we argue that advancing knowledge of the complex pathogenic processes that contribute to ASD can be accelerated by refocusing attention toward identifying endophenotypic traits reflective of inherited mechanisms. This pivot requires renewed emphasis on study designs with measurement of familial co-variation including infant sibling studies, family trio and quad designs, and analysis of monozygotic and dizygotic twin concordance for select trait dimensions. We also emphasize that clarification of endophenotypic traits necessarily will involve integration of transdiagnostic approaches as candidate traits likely reflect liability for multiple clinical conditions and often are agnostic to diagnostic boundaries. Multiple candidate endophenotypes associated with ASD likelihood are described, and we propose a new focus on the analysis of "endophenotype trait domains" (ETDs), or traits measured across multiple levels (e.g., molecular, cellular, neural system, neuropsychological) along the causal pathway from genes to behavior. To inform our central argument for research efforts toward ETD discovery, we first provide a brief review of the concept of endophenotypes and their application to psychiatry. Next, we highlight key criteria for determining the value of candidate endophenotypes, including unique considerations for the study of ASD. Descriptions of different study designs for assessing endophenotypes in ASD research then are offered, including analysis of how select patterns of results may help prioritize candidate traits in future research. We also present multiple candidate ETDs that collectively cover a breadth of clinical phenomena associated with ASD, including social, language/communication, cognitive control, and sensorimotor processes. These ETDs are described because they represent promising targets for gene discovery related to clinical autistic traits, and they serve as models for analysis of separate candidate domains that may inform understanding of inherited etiological processes associated with ASD as well as overlapping neurodevelopmental disorders.
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Affiliation(s)
- Matthew W Mosconi
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA.
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, USA.
| | - Cassandra J Stevens
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA
- Clinical Child Psychology Program, University of Kansas, Lawrence, KS, USA
| | - Kathryn E Unruh
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA
| | - Robin Shafer
- Schiefelbusch Institute for Life Span Studies and Kansas Center for Autism Research and Training (K-CART), University of Kansas, Lawrence, KS, USA
| | - Jed T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
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Feng M, Xu J. Detection of ASD Children through Deep-Learning Application of fMRI. CHILDREN (BASEL, SWITZERLAND) 2023; 10:1654. [PMID: 37892317 PMCID: PMC10605350 DOI: 10.3390/children10101654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/01/2023] [Revised: 10/01/2023] [Accepted: 10/04/2023] [Indexed: 10/29/2023]
Abstract
Autism spectrum disorder (ASD) necessitates prompt diagnostic scrutiny to enable immediate, targeted interventions. This study unveils an advanced convolutional-neural-network (CNN) algorithm that was meticulously engineered to examine resting-state functional magnetic resonance imaging (fMRI) for early ASD detection in pediatric cohorts. The CNN architecture amalgamates convolutional, pooling, batch-normalization, dropout, and fully connected layers, optimized for high-dimensional data interpretation. Rigorous preprocessing yielded 22,176 two-dimensional echo planar samples from 126 subjects (56 ASD, 70 controls) who were sourced from the Autism Brain Imaging Data Exchange (ABIDE I) repository. The model, trained on 17,740 samples across 50 epochs, demonstrated unparalleled diagnostic metrics-accuracy of 99.39%, recall of 98.80%, precision of 99.85%, and an F1 score of 99.32%-and thereby eclipsed extant computational methodologies. Feature map analyses substantiated the model's hierarchical feature extraction capabilities. This research elucidates a deep learning framework for computer-assisted ASD screening via fMRI, with transformative implications for early diagnosis and intervention.
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Affiliation(s)
- Min Feng
- Nanjing Rehabilitation Medical Center, The Affiliated Brain Hospital, Nanjing Medical University, Nanjing 210029, China
- School of Chinese Language and Literature, Nanjing Normal University, Nanjing 210024, China
| | - Juncai Xu
- School of Engineering, Case Western Reserve University, Cleveland, OH 44106, USA;
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Dvornek NC, Sullivan C, Duncan JS, Gupta AR. Copy Number Variation Informs fMRI-based Prediction of Autism Spectrum Disorder. MACHINE LEARNING IN CLINICAL NEUROIMAGING : 6TH INTERNATIONAL WORKSHOP, MLCN 2023, HELD IN CONJUNCTION WITH MICCAI 2023, VANCOUVER, BC, CANADA, OCTOBER 8, 2023, PROCEEDINGS. MLCN (WORKSHOP) (6TH : 2023 : VANCOUVER, B.C.) 2023; 14312:133-142. [PMID: 38371906 PMCID: PMC10868600 DOI: 10.1007/978-3-031-44858-4_13] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
The multifactorial etiology of autism spectrum disorder (ASD) suggests that its study would benefit greatly from multimodal approaches that combine data from widely varying platforms, e.g., neuroimaging, genetics, and clinical characterization. Prior neuroimaging-genetic analyses often apply naive feature concatenation approaches in data-driven work or use the findings from one modality to guide posthoc analysis of another, missing the opportunity to analyze the paired multimodal data in a truly unified approach. In this paper, we develop a more integrative model for combining genetic, demographic, and neuroimaging data. Inspired by the influence of genotype on phenotype, we propose using an attention-based approach where the genetic data guides attention to neuroimaging features of importance for model prediction. The genetic data is derived from copy number variation parameters, while the neuroimaging data is from functional magnetic resonance imaging. We evaluate the proposed approach on ASD classification and severity prediction tasks, using a sex-balanced dataset of 228 ASD and typically developing subjects in a 10-fold cross-validation framework. We demonstrate that our attention-based model combining genetic information, demographic data, and functional magnetic resonance imaging results in superior prediction performance compared to other multimodal approaches.
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Affiliation(s)
- Nicha C Dvornek
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT 06511, USA
| | - Catherine Sullivan
- Department of Pediatrics, Yale School of Medicine, New Haven, CT 06510, USA
| | - James S Duncan
- Department of Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06510, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT 06511, USA
| | - Abha R Gupta
- Department of Pediatrics, Yale School of Medicine, New Haven, CT 06510, USA
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Wang J, Dvornek NC, Staib LH, Duncan JS. Learning Sequential Information in Task-based fMRI for Synthetic Data Augmentation. MACHINE LEARNING IN CLINICAL NEUROIMAGING : 6TH INTERNATIONAL WORKSHOP, MLCN 2023, HELD IN CONJUNCTION WITH MICCAI 2023, VANCOUVER, BC, CANADA, OCTOBER 8, 2023, PROCEEDINGS. MLCN (WORKSHOP) (6TH : 2023 : VANCOUVER, B.C.) 2023; 14312:79-88. [PMID: 39281201 PMCID: PMC11395879 DOI: 10.1007/978-3-031-44858-4_8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/18/2024]
Abstract
Insufficiency of training data is a persistent issue in medical image analysis, especially for task-based functional magnetic resonance images (fMRI) with spatio-temporal imaging data acquired using specific cognitive tasks. In this paper, we propose an approach for generating synthetic fMRI sequences that can then be used to create augmented training datasets in downstream learning tasks. To synthesize high-resolution task-specific fMRI, we adapt the α-GAN structure, leveraging advantages of both GAN and variational autoencoder models, and propose different alternatives in aggregating temporal information. The synthetic images are evaluated from multiple perspectives including visualizations and an autism spectrum disorder (ASD) classification task. The results show that the synthetic task-based fMRI can provide effective data augmentation in learning the ASD classification task.
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Affiliation(s)
- Jiyao Wang
- Biomedical Engineering, Yale University, New Haven, CT 06511, USA
| | - Nicha C Dvornek
- Biomedical Engineering, Yale University, New Haven, CT 06511, USA
- Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06511, USA
| | - Lawrence H Staib
- Biomedical Engineering, Yale University, New Haven, CT 06511, USA
- Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06511, USA
| | - James S Duncan
- Biomedical Engineering, Yale University, New Haven, CT 06511, USA
- Radiology & Biomedical Imaging, Yale School of Medicine, New Haven, CT 06511, USA
- Electrical Engineering, Yale University, New Haven, CT 06511, USA
- Statistics & Data Science, Yale University New Haven, CT, 06511, USA
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Wang Y, Long H, Zhou Q, Bo T, Zheng J. PLSNet: Position-aware GCN-based autism spectrum disorder diagnosis via FC learning and ROIs sifting. Comput Biol Med 2023; 163:107184. [PMID: 37356292 DOI: 10.1016/j.compbiomed.2023.107184] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 05/25/2023] [Accepted: 06/13/2023] [Indexed: 06/27/2023]
Abstract
Brain function connectivity, derived from functional magnetic resonance imaging (fMRI), has enjoyed high popularity in the studies of Autism Spectrum Disorder (ASD) diagnosis. Albeit rapid progress has been made, most studies still suffer from several knotty issues: (1) the hardship of modeling the sophisticated brain neuronal connectivity; (2) the mismatch of identically graph node setup to the variations of different brain regions; (3) the dimensionality explosion resulted from excessive voxels in each fMRI sample; (4) the poor interpretability giving rise to unpersuasive diagnosis. To ameliorate these issues, we propose a position-aware graph-convolution-network-based model, namely PLSNet, with superior accuracy and compelling built-in interpretability for ASD diagnosis. Specifically, a time-series encoder is designed for context-rich feature extraction, followed by a function connectivity generator to model the correlation with long range dependencies. In addition, to discriminate the brain nodes with different locations, the position embedding technique is adopted, giving a unique identity to each graph region. We then embed a rarefying method to sift the salient nodes during message diffusion, which would also benefit the reduction of the dimensionality complexity. Extensive experiments conducted on Autism Brain Imaging Data Exchange demonstrate that our PLSNet achieves state-of-the-art performance. Notably, on CC200 atlas, PLSNet reaches an accuracy of 76.4% and a specificity of 78.6%, overwhelming the previous state-of-the-art with 2.5% and 6.5% under five-fold cross-validation policy. Moreover, the most salient brain regions predicted by PLSNet are closely consistent with the theoretical knowledge in the medical domain, providing potential biomarkers for ASD clinical diagnosis. Our code is available at https://github.com/CodeGoat24/PLSNet.
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Affiliation(s)
- Yibin Wang
- College of Computer Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China
| | - Haixia Long
- College of Computer Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China
| | - Qianwei Zhou
- College of Computer Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China
| | - Tao Bo
- Scientific Center, Shandong Provincial Hospital affiliated to Shandong First Medical University, Jinan 250021, Shandong, China
| | - Jianwei Zheng
- College of Computer Science and Engineering, Zhejiang University of Technology, Hangzhou 310014, Zhejiang, China.
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Bozkus-Genc G, Yucesoy-Ozkan S. Efficacy of a Parent-Implemented Pivotal Response Treatment for Children with Autism Spectrum Disorder. J Autism Dev Disord 2023:10.1007/s10803-023-06113-4. [PMID: 37642872 DOI: 10.1007/s10803-023-06113-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/15/2023] [Indexed: 08/31/2023]
Abstract
PURPOSE Pivotal response treatment (PRT) is a well-established intervention addressing core symptoms of autism spectrum disorder (ASD), with parent involvement as a key component. The current study aimed to examine the effects of PRT parent training on parent fidelity and provide descriptive analyses of parent-child interactions before and after parent training. It also probed parental acceptance and satisfaction with the program. METHODS A concurrent multiple baseline design across participants was used to evaluate the effectiveness of the parent training program. Four parents (range 32-47 years old) and their children with ASD participated in the study. The intervention comprised 12 one-on-one parent training sessions over six consecutive weeks. The visual analysis and effect size calculation (Tau-U) were used to evaluate functional relationship between independent and dependent variables. The descriptive analysis was used to analyze parent-child interaction data. RESULTS The findings reveal that all parents learned and maintained PRT with a high level of fidelity, they also enhanced awareness to create more opportunities for interactions during free play, and the parents were very satisfied with the program. The results also indicate that the six-week parent training program is effective in teaching parents to implement PRT with their children. CONCLUSION These results suggest that the parent training program may be a promising treatment model that is effective, efficient, and cost-effective. Implications for future research and practice are then discussed.
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Affiliation(s)
- Gulden Bozkus-Genc
- School of Education, Department of Special Education, Anadolu University, Eskisehir, Türkiye.
| | - Serife Yucesoy-Ozkan
- School of Education, Department of Special Education, Eskisehir Osmangazi University, Eskisehir, Türkiye
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10
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Tang Y, Tong G, Xiong X, Zhang C, Zhang H, Yang Y. Multi-site diagnostic classification of Autism spectrum disorder using adversarial deep learning on resting-state fMRI. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2023.104892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
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St. John T, Estes AM, Hazlett HC, Marrus N, Burrows CA, Donovan K, Torres Gomez S, Grzadzinski RL, Parish-Morris J, Smith R, Styner M, Garic D, Pandey J, Lee CM, Schultz RT, Botteron KN, Zwaigenbaum L, Piven J, Dager SR. Association of Sex With Neurobehavioral Markers of Executive Function in 2-Year-Olds at High and Low Likelihood of Autism. JAMA Netw Open 2023; 6:e2311543. [PMID: 37140923 PMCID: PMC10160873 DOI: 10.1001/jamanetworkopen.2023.11543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Accepted: 03/19/2023] [Indexed: 05/05/2023] Open
Abstract
Importance Children with autism and their siblings exhibit executive function (EF) deficits early in development, but associations between EF and biological sex or early brain alterations in this population are largely unexplored. Objective To investigate the interaction of sex, autism likelihood group, and structural magnetic resonance imaging alterations on EF in 2-year-old children at high familial likelihood (HL) and low familial likelihood (LL) of autism, based on having an older sibling with autism or no family history of autism in first-degree relatives. Design, Setting, and Participants This prospective cohort study assessed 165 toddlers at HL (n = 110) and LL (n = 55) of autism at 4 university-based research centers. Data were collected from January 1, 2007, to December 31, 2013, and analyzed between August 2021 and June 2022 as part of the Infant Brain Imaging Study. Main Outcomes and Measures Direct assessments of EF and acquired structural magnetic resonance imaging were performed to determine frontal lobe, parietal lobe, and total cerebral brain volume. Results A total of 165 toddlers (mean [SD] age, 24.61 [0.95] months; 90 [54%] male, 137 [83%] White) at HL for autism (n = 110; 17 diagnosed with ASD) and LL for autism (n = 55) were studied. The toddlers at HL for autism scored lower than the toddlers at LL for autism on EF tests regardless of sex (mean [SE] B = -8.77 [4.21]; 95% CI, -17.09 to -0.45; η2p = 0.03). With the exclusion of toddlers with autism, no group (HL vs LL) difference in EF was found in boys (mean [SE] difference, -7.18 [4.26]; 95% CI, 1.24-15.59), but EF was lower in HL girls than LL girls (mean [SE] difference, -9.75 [4.34]; 95% CI, -18.32 to -1.18). Brain-behavior associations were examined, controlling for overall cerebral volume and developmental level. Sex differences in EF-frontal (B [SE] = 16.51 [7.43]; 95% CI, 1.36-31.67; η2p = 0.14) and EF-parietal (B [SE] = 17.68 [6.99]; 95% CI, 3.43-31.94; η2p = 0.17) associations were found in the LL group but not the HL group (EF-frontal: B [SE] = -1.36 [3.87]; 95% CI, -9.07 to 6.35; η2p = 0.00; EF-parietal: B [SE] = -2.81 [4.09]; 95% CI, -10.96 to 5.34; η2p = 0.01). Autism likelihood group differences in EF-frontal (B [SE] = -9.93 [4.88]; 95% CI, -19.73 to -0.12; η2p = 0.08) and EF-parietal (B [SE] = -15.44 [5.18]; 95% CI, -25.86 to -5.02; η2p = 0.16) associations were found in girls not boys (EF-frontal: B [SE] = 6.51 [5.88]; 95% CI, -5.26 to 18.27; η2p = 0.02; EF-parietal: B [SE] = 4.18 [5.48]; 95% CI, -6.78 to 15.15; η2p = 0.01). Conclusions and Relevance This cohort study of toddlers at HL and LL of autism suggests that there is an association between sex and EF and that brain-behavior associations in EF may be altered in children at HL of autism. Furthermore, EF deficits may aggregate in families, particularly in girls.
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Affiliation(s)
- Tanya St. John
- Department of Speech and Hearing Science, University of Washington, Seattle
- University of Washington Autism Center, University of Washington, Seattle
| | - Annette M. Estes
- Department of Speech and Hearing Science, University of Washington, Seattle
- University of Washington Autism Center, University of Washington, Seattle
| | - Heather C. Hazlett
- Carolina Institute for Developmental Disabilities, Carrboro, North Carolina
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Natasha Marrus
- Department of Psychiatry, Washington University School of Medicine in St Louis, Missouri
| | | | - Kevin Donovan
- Department of Biostatistics, University of Pennsylvania, Philadelphia
| | - Santiago Torres Gomez
- McGill Centre for Integrative Neuroscience, Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Rebecca L. Grzadzinski
- Carolina Institute for Developmental Disabilities, Carrboro, North Carolina
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Julia Parish-Morris
- Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Rachel Smith
- Carolina Institute for Developmental Disabilities, Carrboro, North Carolina
| | - Martin Styner
- Carolina Institute for Developmental Disabilities, Carrboro, North Carolina
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Dea Garic
- Carolina Institute for Developmental Disabilities, Carrboro, North Carolina
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Juhi Pandey
- Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Chimei M. Lee
- Department of Pediatrics, University of Minnesota, Minneapolis
| | - Robert T. Schultz
- Center for Autism Research, Children’s Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia
| | - Kelly N. Botteron
- Department of Psychiatry, Washington University School of Medicine in St Louis, Missouri
| | - Lonnie Zwaigenbaum
- Department of Pediatrics, University of Alberta, Edmonton, Alberta, Canada
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, Carrboro, North Carolina
- Department of Psychiatry, University of North Carolina at Chapel Hill School of Medicine, Chapel Hill
| | - Stephen R. Dager
- Department of Radiology, University of Washington Medical Center, Seattle
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12
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Fairchild G, Sully K, Passamonti L, Staginnus M, Darekar A, Sonuga-Barke EJS, Toschi N. Neuroanatomical markers of familial risk in adolescents with conduct disorder and their unaffected relatives. Psychol Med 2023; 53:1721-1731. [PMID: 34607618 DOI: 10.1017/s0033291721003202] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
BACKGROUND Previous studies have reported brain structure abnormalities in conduct disorder (CD), but it is unclear whether these neuroanatomical alterations mediate the effects of familial (genetic and environmental) risk for CD. We investigated brain structure in adolescents with CD and their unaffected relatives (URs) to identify neuroanatomical markers of familial risk for CD. METHODS Forty-one adolescents with CD, 24 URs of CD probands, and 38 healthy controls (aged 12-18), underwent structural magnetic resonance imaging. We performed surface-based morphometry analyses, testing for group differences in cortical volume, thickness, surface area, and folding. We also assessed the volume of key subcortical structures. RESULTS The CD and UR groups both displayed structural alterations (lower surface area and folding) in left inferior parietal cortex compared with controls. In contrast, CD participants showed lower insula and pars opercularis volume than controls, and lower surface area and folding in these regions than controls and URs. The URs showed greater folding in rostral anterior cingulate and inferior temporal cortex than controls and greater medial orbitofrontal folding than CD participants. The surface area and volume differences were not significant when controlling for attention-deficit/hyperactivity disorder comorbidity. There were no group differences in subcortical volumes. CONCLUSIONS These findings suggest that alterations in inferior parietal cortical structure partly mediate the effects of familial risk for CD. These structural changes merit investigation as candidate endophenotypes for CD. Neuroanatomical changes in medial orbitofrontal and anterior cingulate cortex differentiated between URs and the other groups, potentially reflecting neural mechanisms of resilience to CD.
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Affiliation(s)
| | - Kate Sully
- School of Psychology, University of Southampton, Southampton, UK
| | - Luca Passamonti
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
- Institute of Bioimaging and Molecular Physiology, National Research Council, Milan, Italy
| | | | - Angela Darekar
- Department of Medical Physics, University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | | | - Nicola Toschi
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy
- Martinos Center for Biomedical Imaging, Boston, USA
- Harvard Medical School, Boston, USA
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13
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Fittipaldi S, Armony JL, Migeot J, Cadaveira M, Ibáñez A, Baez S. Overactivation of posterior insular, postcentral and temporal regions during preserved experience of envy in autism. Eur J Neurosci 2023; 57:705-717. [PMID: 36628571 PMCID: PMC11170468 DOI: 10.1111/ejn.15911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 01/08/2023] [Accepted: 01/09/2023] [Indexed: 01/12/2023]
Abstract
Social emotions are critical to successfully navigate in a complex social world because they promote self-regulation of behaviour. Difficulties in social behaviour are at the core of autism spectrum disorder (ASD). However, social emotions and their neural correlates have been scarcely investigated in this population. In particular, the experience of envy has not been addressed in ASD despite involving neurocognitive processes crucially compromised in this condition. Here, we used an fMRI adapted version of a well-validated task to investigate the subjective experience of envy and its neural correlates in adults with ASD (n = 30) in comparison with neurotypical controls (n = 28). Results revealed that both groups reported similarly intense experience of envy in association with canonical activation in the anterior cingulate cortex and the anterior insula, among other regions. However, in participants with ASD, the experience of envy was accompanied by overactivation of the posterior insula, the postcentral gyrus and the posterior superior temporal gyrus, regions subserving the processing of painful experiences and mentalizing. This pattern of results suggests that individuals with ASD may use compensatory strategies based on the embodied amplification of pain and additional mentalizing efforts to shape their subjective experience of envy. Results have relevant implications to better understand the heterogeneity of this condition and to develop new intervention targets.
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Affiliation(s)
- Sol Fittipaldi
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), USA, and Trinity College Dublin (TCD), Ireland
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
| | - Jorge L. Armony
- Douglas Mental Health University Institute and Dept. of Psychiatry, McGill University, Montreal, Canada
| | - Joaquín Migeot
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Center for Social and Cognitive Neuroscience (CSCN), School of Psychology, Universidad Adolfo Ibáñez, Santiago, Chile
| | | | - Agustín Ibáñez
- Latin American Brain Health Institute (BrainLat), Universidad Adolfo Ibáñez, Santiago, Chile
- Global Brain Health Institute (GBHI), University of California San Francisco (UCSF), USA, and Trinity College Dublin (TCD), Ireland
- Cognitive Neuroscience Center (CNC), Universidad de San Andres, Buenos Aires, Argentina
- National Scientific and Technical Research Council (CONICET), Buenos Aires, Argentina
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14
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Lemaire BS, Vallortigara G. Life is in motion (through a chick's eye). Anim Cogn 2023; 26:129-140. [PMID: 36222937 PMCID: PMC9877072 DOI: 10.1007/s10071-022-01703-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 10/01/2022] [Accepted: 10/04/2022] [Indexed: 01/29/2023]
Abstract
Cognitive scientists, social psychologists, computer scientists, neuroscientists, ethologists and many others have all wondered how brains detect and interpret the motion of living organisms. It appears that specific cues, incorporated into our brains by natural selection, serve to signal the presence of living organisms. A simple geometric figure such as a triangle put in motion with specific kinematic rules can look alive, and it can even seem to have intentions and goals. In this article, we survey decades of parallel investigations on the motion cues that drive animacy perception-the sensation that something is alive-in non-human animals, especially in precocial species, such as the domestic chick, to identify inborn biological predispositions. At the same time, we highlight the relevance of these studies for an understanding of human typical and atypical cognitive development.
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Affiliation(s)
- Bastien S Lemaire
- Center for Mind and Brain Sciences, University of Trento, Trento, Italy.
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15
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Ni HC, Chao YP, Tseng RY, Wu CT, Cocchi L, Chou TL, Chen RS, Gau SSF, Yeh CH, Lin HY. Lack of effects of four-week theta burst stimulation on white matter macro/microstructure in children and adolescents with autism. Neuroimage Clin 2023; 37:103324. [PMID: 36638598 PMCID: PMC9852693 DOI: 10.1016/j.nicl.2023.103324] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2022] [Revised: 12/18/2022] [Accepted: 01/05/2023] [Indexed: 01/09/2023]
Abstract
Following the published behavioral and cognitive results of this single-blind parallel sham-controlled randomized clinical trial, the current study aimed to explore the impact of intermittent theta burst stimulation (iTBS), a variant of excitatory transcranial magnetic stimulation, over the bilateral posterior superior temporal sulci (pSTS) on white matter macro/microstructure in intellectually able children and adolescents with autism. Participants were randomized and blindly received active or sham iTBS for 4 weeks (the single-blind sham-controlled phase). Then, all participants continued to receive active iTBS for another 4 weeks (the open-label phase). The clinical results were published elsewhere. Here, we present diffusion magnetic resonance imaging data on potential changes in white matter measures after iTBS. Twenty-two participants in Active-Active group and 27 participants in Sham-Active group underwent multi-shell high angular resolution diffusion imaging (64-direction for b = 2000 & 1000 s/mm2, respectively) at baseline, week 4, and week 8. With longitudinal fixel-based analysis, we found no white matter changes following iTBS from baseline to week 4 (a null treatment by time interaction and a null within-group paired comparison in the Active-Active group), nor from baseline to week 8 (null within-group paired comparisons in both Active-Active and Sham-Active groups). As for the brain-symptoms relationship, we did not find baseline white matter metrics associated with symptom changes at week 4 in either group. Our results raise the question of what the minimal cumulative stimulation dose required to induce the white matter plasticity is.
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Affiliation(s)
- Hsing-Chang Ni
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Yi-Ping Chao
- Deparment of Computer Science and Information Engineering, Chang Gung University, Taoyuan, Taiwan; Department of Otorhinolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Rung-Yu Tseng
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan
| | - Chen-Te Wu
- Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Luca Cocchi
- Clinical Brain Networks Group, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
| | - Tai-Li Chou
- Department of Psychology, National Taiwan University, Taipei, Taiwan; Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan; Neurobiology and Cognitive Science Center, National Taiwan University, Taipei, Taiwan
| | - Rou-Shayn Chen
- Department of Neurology, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan
| | - Susan Shur-Fen Gau
- Graduate Institute of Brain and Mind Sciences, College of Medicine, National Taiwan University, Taipei, Taiwan; Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Chun-Hung Yeh
- Department of Psychiatry, Chang Gung Memorial Hospital at Linkou, Taoyuan, Taiwan; Institute for Radiological Research, Chang Gung University, Taoyuan, Taiwan.
| | - Hsiang-Yuan Lin
- Azrieli Adult Neurodevelopmental Centre, Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
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16
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Dougherty JD, Marrus N, Maloney SE, Yip B, Sandin S, Turner TN, Selmanovic D, Kroll KL, Gutmann DH, Constantino JN, Weiss LA. Can the "female protective effect" liability threshold model explain sex differences in autism spectrum disorder? Neuron 2022; 110:3243-3262. [PMID: 35868305 PMCID: PMC9588569 DOI: 10.1016/j.neuron.2022.06.020] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2022] [Revised: 05/09/2022] [Accepted: 06/24/2022] [Indexed: 11/25/2022]
Abstract
Male sex is a strong risk factor for autism spectrum disorder (ASD). The leading theory for a "female protective effect" (FPE) envisions males and females have "differing thresholds" under a "liability threshold model" (DT-LTM). Specifically, this model posits that females require either a greater number or larger magnitude of risk factors (i.e., greater liability) to manifest ASD, which is supported by the finding that a greater proportion of females with ASD have highly penetrant genetic mutations. Herein, we derive testable hypotheses from the DT-LTM for ASD, investigating heritability, familial recurrence, correlation between ASD penetrance and sex ratio, population traits, clinical features, the stability of the sex ratio across diagnostic changes, and highlight other key prerequisites. Our findings reveal that several key predictions of the DT-LTM are not supported by current data, requiring us to establish a different conceptual framework for evaluating alternate models that explain sex differences in ASD.
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Affiliation(s)
- Joseph D Dougherty
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, MO, USA.
| | - Natasha Marrus
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan E Maloney
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Benjamin Yip
- JC School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China
| | - Sven Sandin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Seaver Autism Center for Research and Treatment at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Tychele N Turner
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Din Selmanovic
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA; Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Kristen L Kroll
- Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, MO, USA; Department of Developmental Biology, Washington University School of Medicine, St. Louis, MO, USA
| | - David H Gutmann
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - John N Constantino
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA; Intellectual and Developmental Disabilities Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Lauren A Weiss
- Institute for Human Genetics, Department of Psychiatry and Behavioral Sciences, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA.
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17
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Chien YL, Chen YJ, Tseng WL, Hsu YC, Wu CS, Tseng WYI, Gau SSF. Differences in white matter segments in autistic males, non-autistic siblings, and non-autistic participants: An intermediate phenotype approach. AUTISM : THE INTERNATIONAL JOURNAL OF RESEARCH AND PRACTICE 2022; 27:1036-1052. [PMID: 36254873 DOI: 10.1177/13623613221125620] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
LAY ABSTRACT White matter is the neural pathway that connects neurons in different brain regions. Although research has shown white matter differences between autistic and non-autistic people, little is known about the properties of white matter in non-autistic siblings. In addition, past studies often focused on the whole neural tracts; it is unclear where differences exist in specific segments of the tracts. This study identified neural segments that differed between autistic people, their non-autistic siblings, and the age- and non-autistic people. We found altered segments within the tracts connected to anterior brain regions corresponding to several higher cognitive functions (e.g. executive functions) in autistic people and non-autistic siblings. Segments connecting to regions for social cognition and Theory of Mind were altered only in autistic people, explaining a large portion of autistic traits and may serve as neuroimaging markers. Segments within the tracts associated with fewer autistic traits or connecting brain regions for diverse highly integrated functions showed compensatory increases in the microstructural properties in non-autistic siblings. Our findings suggest that differential white matter segments that are shared between autistic people and non-autistic siblings may serve as potential "intermediate phenotypes"-biological or neuropsychological characteristics in the causal link between genetics and symptoms-of autism. These findings shed light on a promising neuroimaging model to refine the intermediate phenotype of autism which may facilitate further identification of the genetic and biological bases of autism. Future research exploring links between compensatory segments and neurocognitive strengths in non-autistic siblings may help understand brain adaptation to autism.
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Affiliation(s)
- Yi-Ling Chien
- National Taiwan University Hospital and College of Medicine, Taiwan.,National Taiwan University, Taiwan
| | | | | | | | - Chi-Shin Wu
- National Taiwan University Hospital and College of Medicine, Taiwan
| | | | - Susan Shur-Fen Gau
- National Taiwan University Hospital and College of Medicine, Taiwan.,National Taiwan University, Taiwan
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18
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Hogan AL, Winston M, Barstein J, Losh M. Slower Peak Pupillary Response to Emotional Faces in Parents of Autistic Individuals. Front Psychol 2022; 13:836719. [PMID: 36304881 PMCID: PMC9595282 DOI: 10.3389/fpsyg.2022.836719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 05/31/2022] [Indexed: 11/23/2022] Open
Abstract
Background Atypical autonomic arousal has been consistently documented in autism spectrum disorder (ASD) and is thought to contribute to the social-communication phenotype of ASD. Some evidence suggests that clinically unaffected first-degree relatives of autistic individuals may also show subtle differences in indices of autonomic arousal, potentially implicating heritable pathophysiological mechanisms in ASD. This study examined pupillary responses in parents of autistic individuals to investigate evidence that atypical autonomic arousal might constitute a subclinical physiological marker of ASD heritability within families of autistic individuals. Methods Pupillary responses to emotional faces were measured in 47 ASD parents and 20 age-matched parent controls. Macro-level pupillary responses (e.g., mean, peak, latency to peak) and dynamic pupillary responses over the course of the stimulus presentation were compared between groups, and in relationship to subclinical ASD-related features in ASD parents. A small ASD group (n = 20) and controls (n = 17) were also included for exploratory analyses of parent–child correlations in pupillary response. Results Parents of autistic individuals differed in the time course of pupillary response, exhibiting a later primary peak response than controls. In ASD parents, slower peak response was associated with poorer pragmatic language and larger peak response was associated with poorer social cognition. Exploratory analyses revealed correlations between peak pupillary responses in ASD parents and mean and peak pupillary responses in their autistic children. Conclusion Differences in pupillary responses in clinically unaffected parents, together with significant correlations with ASD-related features and significant parent–child associations, suggest that pupillary responses to emotional faces may constitute an objective physiological marker of ASD genetic liability, with potential to inform the mechanistic underpinnings of ASD symptomatology.
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19
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Pavlova MA, Romagnano V, Kubon J, Isernia S, Fallgatter AJ, Sokolov AN. Ties between reading faces, bodies, eyes, and autistic traits. Front Neurosci 2022; 16:997263. [PMID: 36248653 PMCID: PMC9554539 DOI: 10.3389/fnins.2022.997263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 08/12/2022] [Indexed: 11/29/2022] Open
Abstract
While reading covered with masks faces during the COVID-19 pandemic, for efficient social interaction, we need to combine information from different sources such as the eyes (without faces hidden by masks) and bodies. This may be challenging for individuals with neuropsychiatric conditions, in particular, autism spectrum disorders. Here we examined whether reading of dynamic faces, bodies, and eyes are tied in a gender-specific way, and how these capabilities are related to autistic traits expression. Females and males accomplished a task with point-light faces along with a task with point-light body locomotion portraying different emotional expressions. They had to infer emotional content of displays. In addition, participants were administered the Reading the Mind in the Eyes Test, modified and Autism Spectrum Quotient questionnaire. The findings show that only in females, inferring emotions from dynamic bodies and faces are firmly linked, whereas in males, reading in the eyes is knotted with face reading. Strikingly, in neurotypical males only, accuracy of face, body, and eyes reading was negatively tied with autistic traits. The outcome points to gender-specific modes in social cognition: females rely upon merely dynamic cues while reading faces and bodies, whereas males most likely trust configural information. The findings are of value for examination of face and body language reading in neuropsychiatric conditions, in particular, autism, most of which are gender/sex-specific. This work suggests that if male individuals with autistic traits experience difficulties in reading covered with masks faces, these deficits may be unlikely compensated by reading (even dynamic) bodies and faces. By contrast, in females, reading covered faces as well as reading language of dynamic bodies and faces are not compulsorily connected to autistic traits preventing them from paying high costs for maladaptive social interaction.
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Affiliation(s)
- Marina A. Pavlova
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Tübingen, Germany
- *Correspondence: Marina A. Pavlova,
| | - Valentina Romagnano
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Julian Kubon
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Sara Isernia
- IRCCS Fondazione Don Carlo Gnocchi ONLUS, Milan, Italy
| | - Andreas J. Fallgatter
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Tübingen, Germany
| | - Alexander N. Sokolov
- Department of Psychiatry and Psychotherapy, Tübingen Center for Mental Health (TüCMH), Medical School and University Hospital, Eberhard Karls University of Tübingen, Tübingen, Germany
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20
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Orchard ER, Dakin SC, van Boxtel JJA. Internal noise measures in coarse and fine motion direction discrimination tasks and the correlation with autism traits. J Vis 2022; 22:19. [PMID: 36149675 PMCID: PMC9520516 DOI: 10.1167/jov.22.10.19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 08/18/2022] [Indexed: 11/24/2022] Open
Abstract
Motion perception is essential for visual guidance of behavior and is known to be limited by both internal additive noise (i.e., a constant level of random fluctuations in neural activity independent of the stimulus) and motion pooling (global integration of local motion signals across space). People with autism spectrum disorder (ASD) display abnormalities in motion processing, which have been linked to both elevated noise and abnormal pooling. However, to date, the impact of a third limit-induced internal noise (internal noise that scales up with increases in external stimulus noise)-has not been investigated in motion perception of any group. Here, we describe an extension on the double-pass paradigm to quantify additive noise and induced noise in a motion paradigm. We also introduce a new way to experimentally estimate motion pooling. We measured the impact of induced noise on direction discrimination, which we ascribe to fluctuations in decision-related variables. Our results are suggestive of higher internal noise in individuals with high ASD traits only on coarse but not fine motion direction discrimination tasks. However, we report no significant correlations between autism traits and additive noise, induced noise, or motion pooling in either task. We conclude that, under some conditions, the internal noise may be higher in individuals with pronounced ASD traits and that the assessment of induced internal noise is a useful way of exploring decision-related limits on motion perception, irrespective of ASD traits.
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Affiliation(s)
- Edwina R Orchard
- Department of Psychology, Faculty of Arts and Sciences, Yale University, New Haven, CT, USA
- Yale Child Study Center, School of Medicine, Yale University, New Haven, CT, USA
| | - Steven C Dakin
- School of Optometry & Vision Science, University of Auckland, Auckland, New Zealand
- New Zealand National Eye Centre, University of Auckland, Auckland, New Zealand
- UCL Institute of Ophthalmology, University College London, London, UK
| | - Jeroen J A van Boxtel
- Discipline of Psychology, Faculty of Health, University of Canberra, Bruce, ACT, Australia
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, Australia
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21
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Ayaz H, Baker WB, Blaney G, Boas DA, Bortfeld H, Brady K, Brake J, Brigadoi S, Buckley EM, Carp SA, Cooper RJ, Cowdrick KR, Culver JP, Dan I, Dehghani H, Devor A, Durduran T, Eggebrecht AT, Emberson LL, Fang Q, Fantini S, Franceschini MA, Fischer JB, Gervain J, Hirsch J, Hong KS, Horstmeyer R, Kainerstorfer JM, Ko TS, Licht DJ, Liebert A, Luke R, Lynch JM, Mesquida J, Mesquita RC, Naseer N, Novi SL, Orihuela-Espina F, O’Sullivan TD, Peterka DS, Pifferi A, Pollonini L, Sassaroli A, Sato JR, Scholkmann F, Spinelli L, Srinivasan VJ, St. Lawrence K, Tachtsidis I, Tong Y, Torricelli A, Urner T, Wabnitz H, Wolf M, Wolf U, Xu S, Yang C, Yodh AG, Yücel MA, Zhou W. Optical imaging and spectroscopy for the study of the human brain: status report. NEUROPHOTONICS 2022; 9:S24001. [PMID: 36052058 PMCID: PMC9424749 DOI: 10.1117/1.nph.9.s2.s24001] [Citation(s) in RCA: 55] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/14/2023]
Abstract
This report is the second part of a comprehensive two-part series aimed at reviewing an extensive and diverse toolkit of novel methods to explore brain health and function. While the first report focused on neurophotonic tools mostly applicable to animal studies, here, we highlight optical spectroscopy and imaging methods relevant to noninvasive human brain studies. We outline current state-of-the-art technologies and software advances, explore the most recent impact of these technologies on neuroscience and clinical applications, identify the areas where innovation is needed, and provide an outlook for the future directions.
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Affiliation(s)
- Hasan Ayaz
- Drexel University, School of Biomedical Engineering, Science, and Health Systems, Philadelphia, Pennsylvania, United States
- Drexel University, College of Arts and Sciences, Department of Psychological and Brain Sciences, Philadelphia, Pennsylvania, United States
| | - Wesley B. Baker
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
- Perelman School of Medicine at the University of Pennsylvania, Philadelphia, Pennsylvania, United States
| | - Giles Blaney
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - David A. Boas
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Heather Bortfeld
- University of California, Merced, Departments of Psychological Sciences and Cognitive and Information Sciences, Merced, California, United States
| | - Kenneth Brady
- Lurie Children’s Hospital, Northwestern University Feinberg School of Medicine, Department of Anesthesiology, Chicago, Illinois, United States
| | - Joshua Brake
- Harvey Mudd College, Department of Engineering, Claremont, California, United States
| | - Sabrina Brigadoi
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
| | - Erin M. Buckley
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
- Emory University School of Medicine, Department of Pediatrics, Atlanta, Georgia, United States
| | - Stefan A. Carp
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Robert J. Cooper
- University College London, Department of Medical Physics and Bioengineering, DOT-HUB, London, United Kingdom
| | - Kyle R. Cowdrick
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Joseph P. Culver
- Washington University School of Medicine, Department of Radiology, St. Louis, Missouri, United States
| | - Ippeita Dan
- Chuo University, Faculty of Science and Engineering, Tokyo, Japan
| | - Hamid Dehghani
- University of Birmingham, School of Computer Science, Birmingham, United Kingdom
| | - Anna Devor
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Turgut Durduran
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
- Institució Catalana de Recerca I Estudis Avançats (ICREA), Barcelona, Spain
| | - Adam T. Eggebrecht
- Washington University in St. Louis, Mallinckrodt Institute of Radiology, St. Louis, Missouri, United States
| | - Lauren L. Emberson
- University of British Columbia, Department of Psychology, Vancouver, British Columbia, Canada
| | - Qianqian Fang
- Northeastern University, Department of Bioengineering, Boston, Massachusetts, United States
| | - Sergio Fantini
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - Maria Angela Franceschini
- Massachusetts General Hospital, Harvard Medical School, Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, Massachusetts, United States
| | - Jonas B. Fischer
- ICFO – The Institute of Photonic Sciences, The Barcelona Institute of Science and Technology, Castelldefels, Barcelona, Spain
| | - Judit Gervain
- University of Padua, Department of Developmental and Social Psychology, Padua, Italy
- Université Paris Cité, CNRS, Integrative Neuroscience and Cognition Center, Paris, France
| | - Joy Hirsch
- Yale School of Medicine, Department of Psychiatry, Neuroscience, and Comparative Medicine, New Haven, Connecticut, United States
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Keum-Shik Hong
- Pusan National University, School of Mechanical Engineering, Busan, Republic of Korea
- Qingdao University, School of Automation, Institute for Future, Qingdao, China
| | - Roarke Horstmeyer
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
- Duke University, Department of Electrical and Computer Engineering, Durham, North Carolina, United States
- Duke University, Department of Physics, Durham, North Carolina, United States
| | - Jana M. Kainerstorfer
- Carnegie Mellon University, Department of Biomedical Engineering, Pittsburgh, Pennsylvania, United States
- Carnegie Mellon University, Neuroscience Institute, Pittsburgh, Pennsylvania, United States
| | - Tiffany S. Ko
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Daniel J. Licht
- Children’s Hospital of Philadelphia, Division of Neurology, Philadelphia, Pennsylvania, United States
| | - Adam Liebert
- Polish Academy of Sciences, Nalecz Institute of Biocybernetics and Biomedical Engineering, Warsaw, Poland
| | - Robert Luke
- Macquarie University, Department of Linguistics, Sydney, New South Wales, Australia
- Macquarie University Hearing, Australia Hearing Hub, Sydney, New South Wales, Australia
| | - Jennifer M. Lynch
- Children’s Hospital of Philadelphia, Division of Cardiothoracic Anesthesiology, Philadelphia, Pennsylvania, United States
| | - Jaume Mesquida
- Parc Taulí Hospital Universitari, Critical Care Department, Sabadell, Spain
| | - Rickson C. Mesquita
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Brazilian Institute of Neuroscience and Neurotechnology, Campinas, São Paulo, Brazil
| | - Noman Naseer
- Air University, Department of Mechatronics and Biomedical Engineering, Islamabad, Pakistan
| | - Sergio L. Novi
- University of Campinas, Institute of Physics, Campinas, São Paulo, Brazil
- Western University, Department of Physiology and Pharmacology, London, Ontario, Canada
| | | | - Thomas D. O’Sullivan
- University of Notre Dame, Department of Electrical Engineering, Notre Dame, Indiana, United States
| | - Darcy S. Peterka
- Columbia University, Zuckerman Mind Brain Behaviour Institute, New York, United States
| | | | - Luca Pollonini
- University of Houston, Department of Engineering Technology, Houston, Texas, United States
| | - Angelo Sassaroli
- Tufts University, Department of Biomedical Engineering, Medford, Massachusetts, United States
| | - João Ricardo Sato
- Federal University of ABC, Center of Mathematics, Computing and Cognition, São Bernardo do Campo, São Paulo, Brazil
| | - Felix Scholkmann
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Lorenzo Spinelli
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Vivek J. Srinivasan
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- NYU Langone Health, Department of Ophthalmology, New York, New York, United States
- NYU Langone Health, Department of Radiology, New York, New York, United States
| | - Keith St. Lawrence
- Lawson Health Research Institute, Imaging Program, London, Ontario, Canada
- Western University, Department of Medical Biophysics, London, Ontario, Canada
| | - Ilias Tachtsidis
- University College London, Department of Medical Physics and Biomedical Engineering, London, United Kingdom
| | - Yunjie Tong
- Purdue University, Weldon School of Biomedical Engineering, West Lafayette, Indiana, United States
| | - Alessandro Torricelli
- Politecnico di Milano, Dipartimento di Fisica, Milan, Italy
- National Research Council (CNR), IFN – Institute for Photonics and Nanotechnologies, Milan, Italy
| | - Tara Urner
- Georgia Institute of Technology, Wallace H. Coulter Department of Biomedical Engineering, Atlanta, Georgia, United States
| | - Heidrun Wabnitz
- Physikalisch-Technische Bundesanstalt (PTB), Berlin, Germany
| | - Martin Wolf
- University of Zurich, University Hospital Zurich, Department of Neonatology, Biomedical Optics Research Laboratory, Zürich, Switzerland
| | - Ursula Wolf
- University of Bern, Institute of Complementary and Integrative Medicine, Bern, Switzerland
| | - Shiqi Xu
- Duke University, Department of Biomedical Engineering, Durham, North Carolina, United States
| | - Changhuei Yang
- California Institute of Technology, Department of Electrical Engineering, Pasadena, California, United States
| | - Arjun G. Yodh
- University of Pennsylvania, Department of Physics and Astronomy, Philadelphia, Pennsylvania, United States
| | - Meryem A. Yücel
- Boston University Neurophotonics Center, Boston, Massachusetts, United States
- Boston University, College of Engineering, Department of Biomedical Engineering, Boston, Massachusetts, United States
| | - Wenjun Zhou
- University of California Davis, Department of Biomedical Engineering, Davis, California, United States
- China Jiliang University, College of Optical and Electronic Technology, Hangzhou, Zhejiang, China
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22
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Duarte JV, Abreu R, Castelo-Branco M. A two-stage framework for neural processing of biological motion. Neuroimage 2022; 259:119403. [PMID: 35738331 DOI: 10.1016/j.neuroimage.2022.119403] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2022] [Revised: 05/18/2022] [Accepted: 06/19/2022] [Indexed: 11/26/2022] Open
Abstract
It remains to be understood how biological motion is hierarchically computed, from discrimination of local biological motion animacy to global dynamic body perception. Here, we addressed this functional separation of the correlates of the perception of local biological motion from perception of global motion of a body. We hypothesized that local biological motion processing can be isolated, by using a single dot motion perceptual decision paradigm featuring the biomechanical details of local realistic motion of a single joint. To ensure that we were indeed tackling processing of biological motion properties we used a discrimination instead of detection task. We discovered using representational similarity analysis that two key early dorsal and two ventral stream regions (visual motion selective hMT+ and V3A, extrastriate body area EBA and a region within fusiform gyrus FFG) showed robust and separable signals related to encoding of local biological motion and global motion-mediated shape. These signals reflected two independent processing stages, as revealed by representational similarity analysis and deconvolution of fMRI responses to each motion pattern. This study showed that higher level pSTS encodes both classes of biological motion in a similar way, revealing a higher-level integrative stage, reflecting scale independent biological motion perception. Our results reveal a two-stage framework for neural computation of biological motion, with an independent contribution of dorsal and ventral regions for the initial stage.
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Affiliation(s)
- João Valente Duarte
- Centre of Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Faculty of Medicine, University of Coimbra, Portugal
| | - Rodolfo Abreu
- Centre of Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal
| | - Miguel Castelo-Branco
- Centre of Biomedical Imaging and Translational Research (CIBIT), Institute of Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Portugal; Faculty of Medicine, University of Coimbra, Portugal.
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23
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Mohammadzaheri F, Koegel LK, Soleymani Z, Khosrowabadi R, Bakhshi E. Neural Correlates of Enhancing Question Asking and Initiations in Children with Autism Spectrum Disorders: A Randomized Clinical Trial. Soc Neurosci 2022; 17:181-192. [PMID: 35296214 DOI: 10.1080/17470919.2022.2054858] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
Children diagnosed with autism spectrum disorder (ASD) demonstrate challenges in various areas of social communication. The aim of this study was to examine the effect of Pivotal Response Treatment (PRT) targeting question-asking on brain activity in twenty 6-12-year-old autistic boys, using a Randomized Clinical Trial (RCT) design. Verbal children, diagnosed with autism, who lacked question asking in their communication were matched based on age and mean length utterance (MLU) and were randomly placed in either PRT intervention or treatment as usual (TAU) groups. Sessions were individually administered, lasting for 60 minutes three days a week for a two-month period. All children were tested before and after intervention to assess behavioral areas (questions, general communicative skills, and MLU) and both groups underwent electroencephalography for 10 minutes in open and closed eye resting-state conditions to assess neural correlates. Data were analyzed using covariance analysis and post-hoc using Mann-Whitney and Wilcoxon methods. Significant behavioral improvements in the PRT group were observed after intervention that correlated with changes in Electroencephalography (EEG) oscillations at several brain regions compared to the TAU group. The results of this study support other studies suggesting collateral neural changes following the PRT.
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Affiliation(s)
- Fereshteh Mohammadzaheri
- Department of Speech Therapy, Rehabilitation College, Tehran University of Medical Science, Tehran, Iran
| | - Lynn Kern Koegel
- Department of Psychiatry and Behavioral Sciences, Stanford School of Medicine, Stanford University, Palo Alto, California
| | - Zahra Soleymani
- Department of Speech Therapy, Rehabilitation College, Tehran University of Medical Science, Tehran, Iran
| | - Reza Khosrowabadi
- Institute for Cognitive and Brain Sciences, Shahid Beheshti University GC, Tehran, Iran
| | - Enayatollah Bakhshi
- Department of Biostatics and Epidemiology, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
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24
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McKechanie AG, Lawrie SM, Whalley HC, Stanfield AC. A functional MRI facial emotion-processing study of autism in individuals with special educational needs. Psychiatry Res Neuroimaging 2022; 320:111426. [PMID: 34911009 DOI: 10.1016/j.pscychresns.2021.111426] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2021] [Revised: 11/16/2021] [Accepted: 12/07/2021] [Indexed: 11/22/2022]
Abstract
This study aimed to investigate the functional imaging associations of autism in individuals with special educational needs and demonstrate the feasibility of such research. The study included 18 individuals (3 female,15 male; mean age 24.3; mean IQ 69.7) with special educational needs (SEN), of whom 9 met criteria for autism. The task examined the Blood-oxygen-level dependant response to fearful and neutral faces. Individuals in the autism group had 2 clusters of significantly reduced activity centred on the left superior frontal gyrus and left angular gyrus compared to those with SEN alone in response to the fearful faces. In the response to neutral faces, individuals in the autism group also had a cluster of significantly greater activity centred on the right precentral gyrus compared to those with SEN alone. We suggest that autistic characteristics in individuals with SEN are associated with changes in fearful facial emotion processing analogous to those previously reported in autistic individuals without SEN, and who are of average or above average cognitive ability. The finding of enhanced response to neutral facial stimuli needs further investigation, although we speculate this may relate to reports of the experience of 'hyper-mentalisation' in social situations as reported by some autistic individuals.
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Affiliation(s)
- Andrew G McKechanie
- Patrick Wild Centre, University of Edinburgh, Edinburgh, United Kingdom; Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom.
| | - Stephen M Lawrie
- Patrick Wild Centre, University of Edinburgh, Edinburgh, United Kingdom; Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Heather C Whalley
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew C Stanfield
- Patrick Wild Centre, University of Edinburgh, Edinburgh, United Kingdom; Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
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25
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Duan Y, Zhao W, Luo C, Liu X, Jiang H, Tang Y, Liu C, Yao D. Identifying and Predicting Autism Spectrum Disorder Based on Multi-Site Structural MRI With Machine Learning. Front Hum Neurosci 2022; 15:765517. [PMID: 35273484 PMCID: PMC8902595 DOI: 10.3389/fnhum.2021.765517] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 12/13/2021] [Indexed: 11/13/2022] Open
Abstract
Although emerging evidence has implicated structural/functional abnormalities of patients with Autism Spectrum Disorder(ASD), definitive neuroimaging markers remain obscured due to inconsistent or incompatible findings, especially for structural imaging. Furthermore, brain differences defined by statistical analysis are difficult to implement individual prediction. The present study has employed the machine learning techniques under the unified framework in neuroimaging to identify the neuroimaging markers of patients with ASD and distinguish them from typically developing controls(TDC). To enhance the interpretability of the machine learning model, the study has processed three levels of assessments including model-level assessment, feature-level assessment, and biology-level assessment. According to these three levels assessment, the study has identified neuroimaging markers of ASD including the opercular part of bilateral inferior frontal gyrus, the orbital part of right inferior frontal gyrus, right rolandic operculum, right olfactory cortex, right gyrus rectus, right insula, left inferior parietal gyrus, bilateral supramarginal gyrus, bilateral angular gyrus, bilateral superior temporal gyrus, bilateral middle temporal gyrus, and left inferior temporal gyrus. In addition, negative correlations between the communication skill score in the Autism Diagnostic Observation Schedule (ADOS_G) and regional gray matter (GM) volume in the gyrus rectus, left middle temporal gyrus, and inferior temporal gyrus have been detected. A significant negative correlation has been found between the communication skill score in ADOS_G and the orbital part of the left inferior frontal gyrus. A negative correlation between verbal skill score and right angular gyrus and a significant negative correlation between non-verbal communication skill and right angular gyrus have been found. These findings in the study have suggested the GM alteration of ASD and correlated with the clinical severity of ASD disease symptoms. The interpretable machine learning framework gives sight to the pathophysiological mechanism of ASD but can also be extended to other diseases.
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Affiliation(s)
- YuMei Duan
- Department of Computer and Software, Chengdu Jincheng College, Chengdu, China
| | - WeiDong Zhao
- College of Computer, Chengdu University, Chengdu, China
| | - Cheng Luo
- The Key Laboratory for Neuro Information of Ministry of Education, Center for Information in Bio Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - XiaoJu Liu
- Department of Abdominal Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - Hong Jiang
- Department of Neurosurgery, Rui-Jin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - YiQian Tang
- College of Computer, Chengdu University, Chengdu, China
| | - Chang Liu
- College of Computer, Chengdu University, Chengdu, China
- The Key Laboratory for Neuro Information of Ministry of Education, Center for Information in Bio Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - DeZhong Yao
- The Key Laboratory for Neuro Information of Ministry of Education, Center for Information in Bio Medicine, High-Field Magnetic Resonance Brain Imaging Key Laboratory of Sichuan Province, School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
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26
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Xu L, Zheng X, Yao S, Li J, Fu M, Li K, Zhao W, Li H, Becker B, Kendrick KM. The mirror neuron system compensates for amygdala dysfunction - associated social deficits in individuals with higher autistic traits. Neuroimage 2022; 251:119010. [PMID: 35182751 DOI: 10.1016/j.neuroimage.2022.119010] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 02/13/2022] [Accepted: 02/15/2022] [Indexed: 12/25/2022] Open
Abstract
The amygdala is a core node in the social brain which exhibits structural and functional abnormalities in Autism spectrum disorder and there is evidence that the mirror neuron system (MNS) can functionally compensate for impaired emotion processing following amygdala lesions. In the current study, we employed an fMRI paradigm in 241 subjects investigating MNS and amygdala responses to observation, imagination and imitation of dynamic facial expressions and whether these differed in individuals with higher (n = 77) as opposed to lower (n = 79) autistic traits. Results indicated that individuals with higher compared to lower autistic traits showed worse recognition memory for fearful faces, smaller real-life social networks, and decreased left basolateral amygdala (BLA) responses to imitation. Additionally, functional connectivity between the left BLA and the left inferior frontal gyrus (IFG) as well as some other MNS regions was increased in individuals with higher autistic traits, especially during imitation of fearful expressions. The left BLA-IFG connectivity significantly moderated the autistic group differences on recognition memory for fearful faces, indicating that increased amygdala-MNS connectivity could diminish the social behavioral differences between higher and lower autistic trait groups. Overall, findings demonstrate decreased imitation-related amygdala activity in individuals with higher autistic traits in the context of increased amygdala-MNS connectivity which may functionally compensate for amygdala dysfunction and social deficits. Training targeting the MNS may capitalize on this compensatory mechanism for therapeutic benefits in Autism spectrum disorder.
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Affiliation(s)
- Lei Xu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China; Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, China
| | - Xiaoxiao Zheng
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China; Brain Cognition and Brain Disease Institute (BCBDI), Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Shuxia Yao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Jialin Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Meina Fu
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Keshuang Li
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China; School of Psychology and Cognitive Science, East China Normal University, Shanghai, China
| | - Weihua Zhao
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China
| | - Hong Li
- Institute of Brain and Psychological Sciences, Sichuan Normal University, Chengdu, China
| | - Benjamin Becker
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
| | - Keith M Kendrick
- The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China.
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27
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Chen B. A Preliminary Study of Abnormal Centrality of Cortical Regions and Subsystems in Whole Brain Functional Connectivity of Autism Spectrum Disorder Boys. Clin EEG Neurosci 2022; 53:3-11. [PMID: 34152841 DOI: 10.1177/15500594211026282] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The abnormal cortices of autism spectrum disorder (ASD) brains are uncertain. However, the pathological alterations of ASD brains are distributed throughout interconnected cortical systems. Functional connections (FCs) methodology identifies cooperation and separation characteristics of information process in macroscopic cortical activity patterns under the context of network neuroscience. Embracing the graph theory concepts, this paper introduces eigenvector centrality index (EC score) ground on the FCs, and further develops a new framework for researching the dysfunctional cortex of ASD in holism significance. The important process is to uncover noticeable regions and subsystems endowed with antagonistic stance in EC-scores of 26 ASD boys and 28 matched healthy controls (HCs). For whole brain regional EC scores of ASD boys, orbitofrontal superior medial cortex, insula R, posterior cingulate gyrus L, and cerebellum 9 L are endowed with different EC scores significantly. In the brain subsystems level, EC scores of DMN, prefrontal lobe, and cerebellum are aberrant in the ASD boys. Generally, the EC scores display widespread distribution of diseased regions in ASD brains. Meanwhile, the discovered regions and subsystems, such as MPFC, AMYG, INS, prefrontal lobe, and DMN, are engaged in social processing. Meanwhile, the CBCL externalizing problem scores are associated with EC scores.
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Affiliation(s)
- Bo Chen
- 12626Hangzhou Dianzi University, Hangzhou, Zhejiang, PR China
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28
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BrainGNN: Interpretable Brain Graph Neural Network for fMRI Analysis. Med Image Anal 2021; 74:102233. [PMID: 34655865 PMCID: PMC9916535 DOI: 10.1016/j.media.2021.102233] [Citation(s) in RCA: 115] [Impact Index Per Article: 38.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2020] [Revised: 09/04/2021] [Accepted: 09/10/2021] [Indexed: 01/11/2023]
Abstract
Understanding which brain regions are related to a specific neurological disorder or cognitive stimuli has been an important area of neuroimaging research. We propose BrainGNN, a graph neural network (GNN) framework to analyze functional magnetic resonance images (fMRI) and discover neurological biomarkers. Considering the special property of brain graphs, we design novel ROI-aware graph convolutional (Ra-GConv) layers that leverage the topological and functional information of fMRI. Motivated by the need for transparency in medical image analysis, our BrainGNN contains ROI-selection pooling layers (R-pool) that highlight salient ROIs (nodes in the graph), so that we can infer which ROIs are important for prediction. Furthermore, we propose regularization terms-unit loss, topK pooling (TPK) loss and group-level consistency (GLC) loss-on pooling results to encourage reasonable ROI-selection and provide flexibility to encourage either fully individual- or patterns that agree with group-level data. We apply the BrainGNN framework on two independent fMRI datasets: an Autism Spectrum Disorder (ASD) fMRI dataset and data from the Human Connectome Project (HCP) 900 Subject Release. We investigate different choices of the hyper-parameters and show that BrainGNN outperforms the alternative fMRI image analysis methods in terms of four different evaluation metrics. The obtained community clustering and salient ROI detection results show a high correspondence with the previous neuroimaging-derived evidence of biomarkers for ASD and specific task states decoded for HCP. Our code is available at https://github.com/xxlya/BrainGNN_Pytorch.
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McPartland JC, Lerner MD, Bhat A, Clarkson T, Jack A, Koohsari S, Matuskey D, McQuaid GA, Su WC, Trevisan DA. Looking Back at the Next 40 Years of ASD Neuroscience Research. J Autism Dev Disord 2021; 51:4333-4353. [PMID: 34043128 PMCID: PMC8542594 DOI: 10.1007/s10803-021-05095-5] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/14/2021] [Indexed: 12/18/2022]
Abstract
During the last 40 years, neuroscience has become one of the most central and most productive approaches to investigating autism. In this commentary, we assemble a group of established investigators and trainees to review key advances and anticipated developments in neuroscience research across five modalities most commonly employed in autism research: magnetic resonance imaging, functional near infrared spectroscopy, positron emission tomography, electroencephalography, and transcranial magnetic stimulation. Broadly, neuroscience research has provided important insights into brain systems involved in autism but not yet mechanistic understanding. Methodological advancements are expected to proffer deeper understanding of neural circuitry associated with function and dysfunction during the next 40 years.
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Affiliation(s)
| | - Matthew D Lerner
- Department of Psychology, Stony Brook University, Stony Brook, NY, USA
| | - Anjana Bhat
- Department of Physical Therapy, University of Delaware, Newark, DE, USA
| | - Tessa Clarkson
- Department of Psychology, Temple University, Philadelphia, PA, USA
| | - Allison Jack
- Department of Psychology, George Mason University, Fairfax, VA, USA
| | - Sheida Koohsari
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - David Matuskey
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Yale School of Medicine, New Haven, CT, USA
- Department of Neurology, Yale School of Medicine, New Haven, CT, USA
| | - Goldie A McQuaid
- Department of Psychology, George Mason University, Fairfax, VA, USA
| | - Wan-Chun Su
- Department of Physical Therapy, University of Delaware, Newark, DE, USA
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Germann J, Gouveia FV, Brentani H, Bedford SA, Tullo S, Chakravarty MM, Devenyi GA. Involvement of the habenula in the pathophysiology of autism spectrum disorder. Sci Rep 2021; 11:21168. [PMID: 34707133 PMCID: PMC8551275 DOI: 10.1038/s41598-021-00603-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2021] [Accepted: 10/13/2021] [Indexed: 11/09/2022] Open
Abstract
The habenula is a small epithalamic structure with widespread connections to multiple cortical, subcortical and brainstem regions. It has been identified as the central structure modulating the reward value of social interactions, behavioral adaptation, sensory integration and circadian rhythm. Autism spectrum disorder (ASD) is characterized by social communication deficits, restricted interests, repetitive behaviors, and is frequently associated with altered sensory perception and mood and sleep disorders. The habenula is implicated in all these behaviors and results of preclinical studies suggest a possible involvement of the habenula in the pathophysiology of this disorder. Using anatomical magnetic resonance imaging and automated segmentation we show that the habenula is significantly enlarged in ASD subjects compared to controls across the entire age range studied (6-30 years). No differences were observed between sexes. Furthermore, support-vector machine modeling classified ASD with 85% accuracy (model using habenula volume, age and sex) and 64% accuracy in cross validation. The Social Responsiveness Scale (SRS) significantly differed between groups, however, it was not related to individual habenula volume. The present study is the first to provide evidence in human subjects of an involvement of the habenula in the pathophysiology of ASD.
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Affiliation(s)
- Jürgen Germann
- grid.231844.80000 0004 0474 0428University Health Network, 399 Bathurst Street, Toronto, ON Canada ,grid.14709.3b0000 0004 1936 8649Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC Canada
| | - Flavia Venetucci Gouveia
- grid.42327.300000 0004 0473 9646Neuroscience and Mental Health, Hospital for Sick Children Research Institute, Toronto, ON Canada
| | - Helena Brentani
- grid.11899.380000 0004 1937 0722Department of Psychiatry, University of Sao Paulo, Medical School, São Paulo, São Paulo Brazil ,grid.500696.cNational Institute of Developmental Psychiatry for Children and Adolescents, CNPq, São Paulo, São Paulo Brazil
| | - Saashi A. Bedford
- grid.14709.3b0000 0004 1936 8649Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC Canada ,grid.5335.00000000121885934Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom
| | - Stephanie Tullo
- grid.14709.3b0000 0004 1936 8649Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC Canada ,grid.14709.3b0000 0004 1936 8649Integrated Program in Neuroscience, McGill University, Montreal, QC Canada
| | - M. Mallar Chakravarty
- grid.14709.3b0000 0004 1936 8649Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC Canada ,grid.14709.3b0000 0004 1936 8649Department of Biomedical Engineering, McGill University, Montreal, QC Canada ,grid.14709.3b0000 0004 1936 8649Department of Psychiatry, McGill University, Montreal, QC Canada
| | - Gabriel A. Devenyi
- grid.14709.3b0000 0004 1936 8649Cerebral Imaging Centre, Douglas Mental Health University Institute, McGill University, Montreal, QC Canada ,grid.14709.3b0000 0004 1936 8649Department of Psychiatry, McGill University, Montreal, QC Canada
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31
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Banker SM, Gu X, Schiller D, Foss-Feig JH. Hippocampal contributions to social and cognitive deficits in autism spectrum disorder. Trends Neurosci 2021; 44:793-807. [PMID: 34521563 DOI: 10.1016/j.tins.2021.08.005] [Citation(s) in RCA: 106] [Impact Index Per Article: 35.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 07/07/2021] [Accepted: 08/10/2021] [Indexed: 10/20/2022]
Abstract
Autism spectrum disorder (ASD) is characterized by hallmark impairments in social functioning. Nevertheless, nonsocial cognition, including hippocampus-dependent spatial reasoning and episodic memory, is also commonly impaired in ASD. ASD symptoms typically emerge between 12 and 24 months of age, a time window associated with critical developmental events in the hippocampus. Despite this temporal overlap and evidence of hippocampal structural abnormalities in ASD individuals, relatively few human studies have focused on hippocampal function in ASD. Herein, we review the existing evidence for the involvement of the hippocampus in ASD and highlight the hippocampus as a promising area of interest for future research in ASD.
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Affiliation(s)
- Sarah M Banker
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Xiaosi Gu
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Daniela Schiller
- Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Center for Computational Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Jennifer H Foss-Feig
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Seaver Autism Center for Research and Treatment, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Friedman Brain Institute, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
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32
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Ibrahim K, Soorya LV, Halpern DB, Gorenstein M, Siper PM, Wang AT. Social cognitive skills groups increase medial prefrontal cortex activity in children with autism spectrum disorder. Autism Res 2021; 14:2495-2511. [PMID: 34486810 DOI: 10.1002/aur.2603] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Revised: 07/25/2021] [Accepted: 08/09/2021] [Indexed: 12/21/2022]
Abstract
Few studies have examined the neural mechanisms of change following social skills interventions for children with autism spectrum disorder (ASD). This study examined the neural effects of social cognitive skills groups during functional MRI (fMRI) tasks of irony comprehension and eye gaze processing in school-aged children with ASD. Verbally fluent children (ages 8-11) were randomized to social cognitive skills groups or facilitated play comparison groups. Behavioral assessments and fMRI scans were obtained at baseline and endpoint (12 weeks). During fMRI, children completed two separate tasks to engage social cognition circuitry: comprehension of potentially ironic scenarios (n = 34) and viewing emotionally expressive faces with direct or averted gaze (n = 24). Whole-brain analyses were conducted to examine neural changes following treatment. Regression analyses were also conducted to explore the relationship between neural and behavioral changes. When comparing the two groups directly, the social cognitive skills group showed greater increases in activity in the medial prefrontal cortex (mPFC), implicated in theory of mind, relative to the comparison group for both irony comprehension and gaze processing tasks. Increased mPFC activity during the irony task was associated with improvement in social functioning on the Social Responsiveness Scale across both groups. Findings indicate that social cognitive skills interventions may increase activity in regions associated with social cognition and mentalizing abilities. LAY SUMMARY: Social skills groups are a common intervention for school-aged children with ASD. However, few studies have examined the neural response to social skills groups in school-aged children with ASD. Here, we report on a study evaluating neural outcomes from an empirically supported social cognitive skills training curriculum using fMRI. This study seeks to understand the effects of targeting emotion recognition and theory of mind on the brain circuitry involved in social cognition in verbally fluent children ages 8-11. Results indicate increased neural activity in the mPFC, a region considered to be a central hub of the "social brain," in children randomized to social cognitive skills groups relative to a comparison group that received a high-quality, child-directed play approach. In addition, increased activation in the mPFC during an irony comprehension task was associated with gains in social functioning across both groups from pre- to post-treatment. This is the first fMRI study of social skills treatment outcomes following a randomized trial with an active treatment condition in school-aged children with ASD.
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Affiliation(s)
- Karim Ibrahim
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Yale Child Study Center, Yale University School of Medicine, New Haven, Connecticut, USA
| | - Latha V Soorya
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Rush Medical College, Rush University, Chicago, Illinois, USA
| | - Danielle B Halpern
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Michelle Gorenstein
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Paige M Siper
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - A Ting Wang
- Seaver Autism Center, Icahn School of Medicine at Mount Sinai, New York, New York, USA
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33
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Ahammed MS, Niu S, Ahmed MR, Dong J, Gao X, Chen Y. DarkASDNet: Classification of ASD on Functional MRI Using Deep Neural Network. Front Neuroinform 2021; 15:635657. [PMID: 34248531 PMCID: PMC8265393 DOI: 10.3389/fninf.2021.635657] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 04/26/2021] [Indexed: 12/17/2022] Open
Abstract
Non-invasive whole-brain scans aid the diagnosis of neuropsychiatric disorder diseases such as autism, dementia, and brain cancer. The assessable analysis for autism spectrum disorders (ASD) is rationally challenging due to the limitations of publicly available datasets. For diagnostic or prognostic tools, functional Magnetic Resonance Imaging (fMRI) exposed affirmation to the biomarkers in neuroimaging research because of fMRI pickup inherent connectivity between the brain and regions. There are profound studies in ASD with introducing machine learning or deep learning methods that have manifested advanced steps for ASD predictions based on fMRI data. However, utmost antecedent models have an inadequacy in their capacity to manipulate performance metrics such as accuracy, precision, recall, and F1-score. To overcome these problems, we proposed an avant-garde DarkASDNet, which has the competence to extract features from a lower level to a higher level and bring out promising results. In this work, we considered 3D fMRI data to predict binary classification between ASD and typical control (TC). Firstly, we pre-processed the 3D fMRI data by adopting proper slice time correction and normalization. Then, we introduced a novel DarkASDNet which surpassed the benchmark accuracy for the classification of ASD. Our model's outcomes unveil that our proposed method established state-of-the-art accuracy of 94.70% to classify ASD vs. TC in ABIDE-I, NYU dataset. Finally, we contemplated our model by performing evaluation metrics including precision, recall, F1-score, ROC curve, and AUC score, and legitimize by distinguishing with recent literature descriptions to vindicate our outcomes. The proposed DarkASDNet architecture provides a novel benchmark approach for ASD classification using fMRI processed data.
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Affiliation(s)
- Md Shale Ahammed
- Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, Jinan, China
| | - Sijie Niu
- Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, Jinan, China
| | | | - Jiwen Dong
- Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, Jinan, China
| | - Xizhan Gao
- Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, Jinan, China
| | - Yuehui Chen
- Shandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, Jinan, China
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34
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Lawrence KE, Hernandez LM, Fuster E, Padgaonkar NT, Patterson G, Jung J, Okada NJ, Lowe JK, Hoekstra JN, Jack A, Aylward E, Gaab N, Van Horn JD, Bernier RA, McPartland JC, Webb SJ, Pelphrey KA, Green SA, Bookheimer SY, Geschwind DH, Dapretto M. Impact of autism genetic risk on brain connectivity: a mechanism for the female protective effect. Brain 2021; 145:378-387. [PMID: 34050743 PMCID: PMC8967090 DOI: 10.1093/brain/awab204] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2020] [Revised: 04/23/2021] [Accepted: 05/11/2021] [Indexed: 01/27/2023] Open
Abstract
The biological mechanisms underlying the greater prevalence of autism spectrum disorder in males than females remain poorly understood. One hypothesis posits that this female protective effect arises from genetic load for autism spectrum disorder differentially impacting male and female brains. To test this hypothesis, we investigated the impact of cumulative genetic risk for autism spectrum disorder on functional brain connectivity in a balanced sample of boys and girls with autism spectrum disorder and typically developing boys and girls (127 youth, ages 8-17). Brain connectivity analyses focused on the salience network, a core intrinsic functional connectivity network which has previously been implicated in autism spectrum disorder. The effects of polygenic risk on salience network functional connectivity were significantly modulated by participant sex, with genetic load for autism spectrum disorder influencing functional connectivity in boys with and without autism spectrum disorder but not girls. These findings support the hypothesis that autism spectrum disorder risk genes interact with sex differential processes, thereby contributing to the male bias in autism prevalence and proposing an underlying neurobiological mechanism for the female protective effect.
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Affiliation(s)
- Katherine E Lawrence
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA,Correspondence to: Mirella Dapretto Ahmanson-Lovelace Brain Mapping Center 660 Charles E. Young Drive South Los Angeles, CA 90095, USA E-mail:
| | - Leanna M Hernandez
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Emily Fuster
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Namita T Padgaonkar
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Genevieve Patterson
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Jiwon Jung
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Nana J Okada
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Jennifer K Lowe
- Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Jackson N Hoekstra
- Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Allison Jack
- Department of Psychology, George Mason University, Fairfax, VA 22030, USA
| | - Elizabeth Aylward
- Center for Integrative Brain Research, Seattle Children’s Research Institute, Seattle, WA 98101, USA
| | - Nadine Gaab
- Harvard Graduate School of Education, Cambridge, MA 02138, USA
| | - John D Van Horn
- Department of Psychology and School of Data Science, University of Virginia, Charlottesville, VA 22904, USA
| | - Raphael A Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA
| | | | - Sara J Webb
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA 98195, USA,Center on Child Health, Behavior, and Development, Seattle Children’s Research Institute, Seattle, WA 98101, USA
| | - Kevin A Pelphrey
- Department of Neurology, University of Virginia, Charlottesville, VA 22904, USA
| | - Shulamite A Green
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
| | - Daniel H Geschwind
- Department of Neurology, University of California Los Angeles, Los Angeles, CA 90095, USA,Center for Neurobehavioral Genetics, University of California Los Angeles, Los Angeles, CA, 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences, University of California Los Angeles, Los Angeles, CA 90095, USA
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35
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Mazzoni N, Ricciardelli P, Actis-Grosso R, Venuti P. Difficulties in Recognising Dynamic but not Static Emotional Body Movements in Autism Spectrum Disorder. J Autism Dev Disord 2021; 52:1092-1105. [PMID: 33866488 PMCID: PMC8854267 DOI: 10.1007/s10803-021-05015-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/06/2021] [Indexed: 01/03/2023]
Abstract
In this study, we investigated whether the difficulties in body motion (BM) perception may led to deficit in emotion recognition in Autism spectrum disorder (ASD). To this aim, individuals with high-functioning ASD were asked to recognise fearful, happy, and neutral BM depicted as static images or dynamic point-light and full-light displays. Results showed slower response times in participants with ASD only in recognising dynamic stimuli, but no group differences in accuracy. This suggests that i) a deficit in action chaining mechanism in ASD may prevent the recognition of dynamic BM automatically and rapidly, ii) individuals with ASD and high cognitive resources can develop alternative—but equally successful—strategies to recognise emotional body expressions. Implications for treatment are discussed
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Affiliation(s)
- Noemi Mazzoni
- OFDLab - Department of Psychology and Cognitive Science, University of Trento, Via Matteo del Ben, 5B, 38068 Rovereto, Italy
| | - Paola Ricciardelli
- Department of Psychology, University of Milano - Bicocca, Milan, Italy
- Milan Centre for Neuroscience, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20126 Milan, Italy
| | - Rossana Actis-Grosso
- Department of Psychology, University of Milano - Bicocca, Milan, Italy
- Milan Centre for Neuroscience, University of Milano-Bicocca, Piazza dell’Ateneo Nuovo 1, 20126 Milan, Italy
| | - Paola Venuti
- OFDLab - Department of Psychology and Cognitive Science, University of Trento, Via Matteo del Ben, 5B, 38068 Rovereto, Italy
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36
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Jack A, Sullivan CAW, Aylward E, Bookheimer SY, Dapretto M, Gaab N, Van Horn JD, Eilbott J, Jacokes Z, Torgerson CM, Bernier RA, Geschwind DH, McPartland JC, Nelson CA, Webb SJ, Pelphrey KA, Gupta AR. A neurogenetic analysis of female autism. Brain 2021; 144:1911-1926. [PMID: 33860292 PMCID: PMC8320285 DOI: 10.1093/brain/awab064] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 12/01/2020] [Accepted: 12/11/2020] [Indexed: 01/08/2023] Open
Abstract
Females versus males are less frequently diagnosed with autism spectrum disorder (ASD), and while understanding sex differences is critical to delineating the systems biology of the condition, female ASD is understudied. We integrated functional MRI and genetic data in a sex-balanced sample of ASD and typically developing youth (8–17 years old) to characterize female-specific pathways of ASD risk. Our primary objectives were to: (i) characterize female ASD (n = 45) brain response to human motion, relative to matched typically developing female youth (n = 45); and (ii) evaluate whether genetic data could provide further insight into the potential relevance of these brain functional differences. For our first objective we found that ASD females showed markedly reduced response versus typically developing females, particularly in sensorimotor, striatal, and frontal regions. This difference between ASD and typically developing females does not resemble differences between ASD (n = 47) and typically developing males (n = 47), even though neural response did not significantly differ between female and male ASD. For our second objective, we found that ASD females (n = 61), versus males (n = 66), showed larger median size of rare copy number variants containing gene(s) expressed in early life (10 postconceptual weeks to 2 years) in regions implicated by the typically developing female > female functional MRI contrast. Post hoc analyses suggested this difference was primarily driven by copy number variants containing gene(s) expressed in striatum. This striatal finding was reproducible among n = 2075 probands (291 female) from an independent cohort. Together, our findings suggest that striatal impacts may contribute to pathways of risk in female ASD and advocate caution in drawing conclusions regarding female ASD based on male-predominant cohorts.
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Affiliation(s)
- Allison Jack
- Department of Psychology, George Mason University, Fairfax, VA 22030, USA
| | | | - Elizabeth Aylward
- Center for Integrative Brain Research, Seattle Children's Research Institute, Seattle, WA 98101, USA
| | - Susan Y Bookheimer
- Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
| | - Mirella Dapretto
- Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
| | - Nadine Gaab
- Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA 02115 USA.,Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA.,Harvard Graduate School of Education, Cambridge, MA 02138, USA
| | - John D Van Horn
- Department of Psychology, University of Virginia, Charlottesville, VA, USA.,School of Data Science, University of Virginia, Charlottesville, VA, USA
| | - Jeffrey Eilbott
- Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA
| | - Zachary Jacokes
- School of Data Science, University of Virginia, Charlottesville, VA, USA
| | - Carinna M Torgerson
- Neuroscience Graduate Program, University of Southern California, Los Angeles, CA 90007, USA
| | - Raphael A Bernier
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA.,Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, WA 98101, USA
| | - Daniel H Geschwind
- Department of Psychiatry and Biobehavioral Sciences and Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA.,Department of Neurology and Center for Neurobehavioral Genetics, University of California Los Angeles School of Medicine, Los Angeles, CA 90095, USA
| | | | - Charles A Nelson
- Division of Developmental Medicine, Department of Medicine, Boston Children's Hospital, Boston, MA 02115 USA.,Department of Pediatrics, Harvard Medical School, Boston, MA 02115, USA
| | - Sara J Webb
- Department of Psychiatry and Behavioral Sciences, University of Washington, Seattle, WA, USA.,Center for Child Health, Behavior, and Development, Seattle Children's Research Institute, Seattle, WA 98101, USA
| | - Kevin A Pelphrey
- Department of Psychology, University of Virginia, Charlottesville, VA, USA.,Department of Neurology, Brain Institute, and School of Education and Human Development, University of Virginia, Charlottesville, VA, USA
| | - Abha R Gupta
- Department of Pediatrics, Yale School of Medicine, New Haven, CT 06510, USA.,Child Study Center, Yale School of Medicine, New Haven, CT 06510, USA.,Department of Neuroscience, Yale School of Medicine, New Haven, CT 06510, USA
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37
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Enriquez KD, Gupta AR, Hoffman EJ. Signaling Pathways and Sex Differential Processes in Autism Spectrum Disorder. Front Psychiatry 2021; 12:716673. [PMID: 34690830 PMCID: PMC8531220 DOI: 10.3389/fpsyt.2021.716673] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Accepted: 09/02/2021] [Indexed: 12/21/2022] Open
Abstract
Autism spectrum disorders (ASDs) are a group of neurodevelopmental disorders associated with deficits in social communication and restrictive, repetitive patterns of behavior, that affect up to 1 in 54 children. ASDs clearly demonstrate a male bias, occurring ~4 times more frequently in males than females, though the basis for this male predominance is not well-understood. In recent years, ASD risk gene discovery has accelerated, with many whole-exome sequencing studies identifying genes that converge on common pathways, such as neuronal communication and regulation of gene expression. ASD genetics studies have suggested that there may be a "female protective effect," such that females may have a higher threshold for ASD risk, yet its etiology is not well-understood. Here, we review common biological pathways implicated by ASD genetics studies as well as recent analyses of sex differential processes in ASD using imaging genomics, transcriptomics, and animal models. Additionally, we discuss recent investigations of ASD risk genes that have suggested a potential role for estrogens as modulators of biological pathways in ASD, and highlight relevant molecular and cellular pathways downstream of estrogen signaling as potential avenues for further investigation.
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Affiliation(s)
- Kristen D Enriquez
- Program on Neurogenetics, Child Study Center, Yale University School of Medicine, New Haven, CT, United States
| | - Abha R Gupta
- Program on Neurogenetics, Child Study Center, Yale University School of Medicine, New Haven, CT, United States.,Department of Pediatrics, Yale University School of Medicine, New Haven, CT, United States.,Department of Neuroscience, Yale University School of Medicine, New Haven, CT, United States
| | - Ellen J Hoffman
- Program on Neurogenetics, Child Study Center, Yale University School of Medicine, New Haven, CT, United States.,Department of Neuroscience, Yale University School of Medicine, New Haven, CT, United States
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Sarovic D. A Unifying Theory for Autism: The Pathogenetic Triad as a Theoretical Framework. Front Psychiatry 2021; 12:767075. [PMID: 34867553 PMCID: PMC8637925 DOI: 10.3389/fpsyt.2021.767075] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 10/27/2021] [Indexed: 12/27/2022] Open
Abstract
This paper presents a unifying theory for autism by applying the framework of a pathogenetic triad to the scientific literature. It proposes a deconstruction of autism into three contributing features (an autistic personality dimension, cognitive compensation, and neuropathological risk factors), and delineates how they interact to cause a maladaptive behavioral phenotype that may require a clinical diagnosis. The autistic personality represents a common core condition, which induces a set of behavioral issues when pronounced. These issues are compensated for by cognitive mechanisms, allowing the individual to remain adaptive and functional. Risk factors, both exogenous and endogenous ones, show pathophysiological convergence through their negative effects on neurodevelopment. This secondarily affects cognitive compensation, which disinhibits a maladaptive behavioral phenotype. The triad is operationalized and methods for quantification are presented. With respect to the breadth of findings in the literature that it can incorporate, it is the most comprehensive model yet for autism. Its main implications are that (1) it presents the broader autism phenotype as a non-pathological core personality domain, which is shared across the population and uncoupled from associated features such as low cognitive ability and immune dysfunction, (2) it proposes that common genetic variants underly the personality domain, and that rare variants act as risk factors through negative effects on neurodevelopment, (3) it outlines a common pathophysiological mechanism, through inhibition of neurodevelopment and cognitive dysfunction, by which a wide range of endogenous and exogenous risk factors lead to autism, and (4) it suggests that contributing risk factors, and findings of immune and autonomic dysfunction are clinically ascertained rather than part of the core autism construct.
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Affiliation(s)
- Darko Sarovic
- Gillberg Neuropsychiatry Centre, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Department of Radiology, Sahlgrenska University Hospital, Gothenburg, Sweden.,MedTech West, Gothenburg, Sweden
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Della Rosa PA, Canini M, Marchetta E, Cirillo S, Pontesilli S, Scotti R, Natali Sora MG, Poloniato A, Barera G, Falini A, Scifo P, Baldoli C. The effects of the functional interplay between the Default Mode and Executive Control Resting State Networks on cognitive outcome in preterm born infants at 6 months of age. Brain Cogn 2020; 147:105669. [PMID: 33341657 DOI: 10.1016/j.bandc.2020.105669] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 11/27/2020] [Accepted: 12/04/2020] [Indexed: 10/22/2022]
Abstract
Preterm birth can affect cognitive functions, such as attention or more generally executive control mechanisms, with severity in impairments proportional to prematurity. The functional cross-talk between the Default Mode (DMN) and Executive Control (ECN) networks mirrors the integrity of cognitive processing and is directly related to brain development. In this study, a cohort of 20 preterm-born infants was investigated using rs-fMRI. First, we addressed biological maturity of the DMN per se and its interplay with the ECN in terms of patterns of increased functional connectivity. Second, we assessed the impact of the degree of prematurity on the DMN-ECN functional interplay development in relation to cognitive outcome at six months. Our results highlighted the emergence of DMN in preterm neonates, with connectivity strength and synchronization between the anterior DMN hub and frontal areas increasing as a function of biological maturity. Further, cognitive scores at 6 months were predicted by mPFC-ECN connectivity strength with degree of prematurity impacting on mPFC-ECN connectivity and triggering differential patterns of functional maturation of the ECN for very early/early and moderate/late preterm neonates. Our findings suggest that the prematurity window allows to observe precursors of functional plasticity that may underlie different developmental trajectories in preterm children.
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Affiliation(s)
| | - Matteo Canini
- Department of Neuroradiology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Elisa Marchetta
- Department of Neuroradiology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Sara Cirillo
- Department of Neuroradiology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Silvia Pontesilli
- Department of Neuroradiology, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Roberta Scotti
- Department of Neuroradiology, IRCCS Ospedale San Raffaele, Milan, Italy
| | | | - Antonella Poloniato
- Unit of Neonatology, Department of Pediatrics, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Graziano Barera
- Unit of Neonatology, Department of Pediatrics, IRCCS Ospedale San Raffaele, Milan, Italy
| | - Andrea Falini
- Department of Neuroradiology, IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, Milan, Italy
| | - Paola Scifo
- Department of Nuclear Medicine, IRCCS Ospedale San Raffaele, Milan, Italy.
| | - Cristina Baldoli
- Department of Neuroradiology, IRCCS Ospedale San Raffaele, Vita-Salute San Raffaele University, Milan, Italy
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Williams EH, Bilbao-Broch L, Downing PE, Cross ES. Examining the value of body gestures in social reward contexts. Neuroimage 2020; 222:117276. [PMID: 32818616 PMCID: PMC7779365 DOI: 10.1016/j.neuroimage.2020.117276] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2020] [Revised: 08/09/2020] [Accepted: 08/10/2020] [Indexed: 11/23/2022] Open
Abstract
Brain regions associated with the processing of tangible rewards (such as money, food, or sex) are also involved in anticipating social rewards and avoiding social punishment. To date, studies investigating the neural underpinnings of social reward have presented feedback via static or dynamic displays of faces to participants. However, research demonstrates that participants find another type of social stimulus, namely, biological motion, rewarding as well, and exert effort to engage with this type of stimulus. Here we examine whether feedback presented via body gestures in the absence of facial cues also acts as a rewarding stimulus and recruits reward-related brain regions. To achieve this, we investigated the neural underpinnings of anticipating social reward and avoiding social disapproval presented via gestures alone, using a social incentive delay task. As predicted, the anticipation of social reward and avoidance of social disapproval engaged reward-related brain regions, including the nucleus accumbens, in a manner similar to previous studies' reports of feedback presented via faces and money. This study provides the first evidence that human body motion alone engages brain regions associated with reward processing in a similar manner to other social (i.e. faces) and non-social (i.e. money) rewards. The findings advance our understanding of social motivation in human perception and behavior.
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Affiliation(s)
- Elin H Williams
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, England
| | - Laura Bilbao-Broch
- Korea Institute for Science and Technology, University of Science and Technology, Seoul, South Korea
| | - Paul E Downing
- Wales Institute for Cognitive Neuroscience, Bangor University, Bangor, Wales
| | - Emily S Cross
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, Scotland; Department of Cognitive Science, Macquarie University, Sydney, Australia.
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Oxytocin treatment attenuates amygdala activity in autism: a treatment-mechanism study with long-term follow-up. Transl Psychiatry 2020; 10:383. [PMID: 33159033 PMCID: PMC7648620 DOI: 10.1038/s41398-020-01069-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/09/2020] [Revised: 09/29/2020] [Accepted: 10/20/2020] [Indexed: 12/12/2022] Open
Abstract
Intranasal administration of the neuropeptide oxytocin (IN-OT) is increasingly considered as a potential treatment for targeting the core symptoms of autism spectrum disorder (ASD), but the effects of continual use on neural substrates are fairly unexplored and long-term effects are unknown. In this double-blind, randomized, placebo-controlled study, we investigated the effects of single-dose and multiple-dose IN-OT treatment (4 weeks of daily (24 IU) administrations) on brain activity related to processing emotional states. Thirty-eight adult men with ASD (aged between 18 and 35 years) underwent functional magnetic resonance imaging of the posterior superior temporal gyrus (pSTS) and amygdala regions while processing emotional states from point-light biological motion. In line with prior research, a single dose of IN-OT induced a reliable increase in pSTS brain activity during the processing of point-light biological motion, but no consistent long-term changes in pSTS activity were induced after the multiple-dose treatment. In terms of bilateral amygdala, the multiple-dose treatment induced a consistent attenuation in brain activity, which outlasted the period of actual administrations until four weeks and one year post-treatment. Critically, participants with stronger attenuations in amygdala-activity showed greater behavioral improvements, particularly in terms of self-reported feelings of avoidant attachment and social functioning. Together, these observations provide initial insights into the long-lasting neural consequences of chronic IN-OT use on amygdala functioning and provide first indications that the acute versus chronic effects of IN-OT administration may be qualitatively different. Larger studies are however warranted to further elucidate the long-term impact of IN-OT treatment on human neural substrates and its behavioral consequences.
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Ahmed MR, Zhang Y, Liu Y, Liao H. Single Volume Image Generator and Deep Learning-Based ASD Classification. IEEE J Biomed Health Inform 2020; 24:3044-3054. [DOI: 10.1109/jbhi.2020.2998603] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
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Minio-Paluello I, Porciello G, Pascual-Leone A, Baron-Cohen S. Face individual identity recognition: a potential endophenotype in autism. Mol Autism 2020; 11:81. [PMID: 33081830 PMCID: PMC7576748 DOI: 10.1186/s13229-020-00371-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2019] [Accepted: 08/11/2020] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Face individual identity recognition skill is heritable and independent of intellectual ability. Difficulties in face individual identity recognition are present in autistic individuals and their family members and are possibly linked to oxytocin polymorphisms in families with an autistic child. While it is reported that developmental prosopagnosia (i.e., impaired face identity recognition) occurs in 2-3% of the general population, no prosopagnosia prevalence estimate is available for autism. Furthermore, an autism within-group approach has not been reported towards characterizing impaired face memory and to investigate its possible links to social and communication difficulties. METHODS The present study estimated the prevalence of prosopagnosia in 80 autistic adults with no intellectual disability, investigated its cognitive characteristics and links to autism symptoms' severity, personality traits, and mental state understanding from the eye region by using standardized tests and questionnaires. RESULTS More than one third of autistic participants showed prosopagnosia. Their face memory skill was not associated with their symptom's severity, empathy, alexithymia, or general intelligence. Face identity recognition was instead linked to mental state recognition from the eye region only in autistic individuals who had prosopagnosia, and this relationship did not depend on participants' basic face perception skills. Importantly, we found that autistic participants were not aware of their face memory skills. LIMITATIONS We did not test an epidemiological sample, and additional work is necessary to establish whether these results generalize to the entire autism spectrum. CONCLUSIONS Impaired face individual identity recognition meets the criteria to be a potential endophenotype in autism. In the future, testing for face memory could be used to stratify autistic individuals into genetically meaningful subgroups and be translatable to autism animal models.
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Affiliation(s)
- Ilaria Minio-Paluello
- Department of Psychology, Sapienza University of Rome, Rome, Italy.
- IRCCS Fondazione Santa Lucia, Rome, Italy.
- Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.
| | - Giuseppina Porciello
- Department of Psychology, Sapienza University of Rome, Rome, Italy
- IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Alvaro Pascual-Leone
- Hinda and Arthur Marcus Institute for Aging Research and Center for Memory Health, Hebrew SeniorLife, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Guttmann Brain Health Institute, Institut Guttmann de Neurorehabilitació, Universitat Autonoma de Barcelona, Badalona, Spain
| | - Simon Baron-Cohen
- Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, UK
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Eggebrecht AT, Dworetsky A, Hawks Z, Coalson R, Adeyemo B, Davis S, Gray D, McMichael A, Petersen SE, Constantino JN, Pruett JR. Brain function distinguishes female carriers and non-carriers of familial risk for autism. Mol Autism 2020; 11:82. [PMID: 33081838 PMCID: PMC7574590 DOI: 10.1186/s13229-020-00381-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2020] [Accepted: 09/22/2020] [Indexed: 01/13/2023] Open
Abstract
Background Autism spectrum disorder (ASD) is characterized by high population-level heritability and a three-to-one male-to-female ratio that occurs independent of sex linkage. Prior research in a mixed-sex pediatric sample identified neural signatures of familial risk elicited by passive viewing of point light motion displays, suggesting the possibility that both resilience and risk of autism might be associated with brain responses to biological motion. To confirm a relationship between these signatures and inherited risk of autism, we tested them in families enriched for genetic loading through undiagnosed (“carrier”) females. Methods Using functional magnetic resonance imaging, we examined brain responses to passive viewing of point light displays—depicting biological versus non-biological motion—in a sample of undiagnosed adult females enriched for inherited susceptibility to ASD on the basis of affectation in their respective family pedigrees. Brain responses in carrier females were compared to responses in age-, SRS-, and IQ-matched non-carrier-females—i.e., females unrelated to individuals with ASD. We conducted a hypothesis-driven analysis focused on previously published regions of interest as well as exploratory, brain-wide analyses designed to characterize more fully the rich responses to this paradigm. Results We observed robust responses to biological motion. Notwithstanding, the 12 regions implicated by prior research did not exhibit the hypothesized interaction between group (carriers vs. controls) and point light displays (biological vs. non-biological motion). Exploratory, brain-wide analyses identified this interaction in three novel regions. Post hoc analyses additionally revealed significant variations in the time course of brain activation in 20 regions spanning occipital and temporal cortex, indicating group differences in response to point light displays (irrespective of the nature of motion) for exploration in future studies. Limitations We were unable to successfully eye-track all participants, which prevented us from being able to control for potential differences in eye gaze position. Conclusions These methods confirmed pronounced neural signatures that differentiate brain responses to biological and scrambled motion. Our sample of undiagnosed females enriched for family genetic loading enabled discovery of numerous contrasts between carriers and non-carriers of risk of ASD that may index variations in visual attention and motion processing related to genetic susceptibility and inform our understanding of mechanisms incurred by inherited liability for ASD.
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Affiliation(s)
- Adam T Eggebrecht
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA. .,Washington University School of Medicine, C.B. 8225, 4515 McKinley Ave., St. Louis, MO, 63110, USA.
| | - Ally Dworetsky
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA
| | - Zoë Hawks
- Department of Psychological and Brain Sciences, Washington University in St. Louis, 1 Brookings Dr., St Louis, MO, 63130, USA
| | - Rebecca Coalson
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA
| | - Babatunde Adeyemo
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA
| | - Savannah Davis
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA
| | - Daniel Gray
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA
| | - Alana McMichael
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA
| | - Steven E Petersen
- Department of Neurology, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA
| | - John N Constantino
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA
| | - John R Pruett
- Department of Psychiatry, Washington University School of Medicine, 660 S. Euclid Ave, St Louis, MO, 63110, USA
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Pooling Regularized Graph Neural Network for fMRI Biomarker Analysis. MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION : MICCAI ... INTERNATIONAL CONFERENCE ON MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION 2020; 12267:625-635. [PMID: 33043324 PMCID: PMC7544244 DOI: 10.1007/978-3-030-59728-3_61] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Understanding how certain brain regions relate to a specific neurological disorder has been an important area of neuroimaging research. A promising approach to identify the salient regions is using Graph Neural Networks (GNNs), which can be used to analyze graph structured data, e.g. brain networks constructed by functional magnetic resonance imaging (fMRI). We propose an interpretable GNN framework with a novel salient region selection mechanism to determine neurological brain biomarkers associated with disorders. Specifically, we design novel regularized pooling layers that highlight salient regions of interests (ROIs) so that we can infer which ROIs are important to identify a certain disease based on the node pooling scores calculated by the pooling layers. Our proposed framework, Pooling Regularized-GNN (PR-GNN), encourages reasonable ROI-selection and provides flexibility to preserve either individual- or group-level patterns. We apply the PR-GNN framework on a Biopoint Autism Spectral Disorder (ASD) fMRI dataset. We investigate different choices of the hyperparameters and show that PR-GNN outperforms baseline methods in terms of classification accuracy. The salient ROI detection results show high correspondence with the previous neuroimaging-derived biomarkers for ASD.
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Demographic-Guided Attention in Recurrent Neural Networks for Modeling Neuropathophysiological Heterogeneity. ACTA ACUST UNITED AC 2020. [PMID: 34308438 DOI: 10.1007/978-3-030-59861-7_37] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register]
Abstract
Heterogeneous presentation of a neurological disorder suggests potential differences in the underlying pathophysiological changes that occur in the brain. We propose to model heterogeneous patterns of functional network differences using a demographic-guided attention (DGA) mechanism for recurrent neural network models for prediction from functional magnetic resonance imaging (fMRI) time-series data. The context computed from the DGA head is used to help focus on the appropriate functional networks based on individual demographic information. We demonstrate improved classification on 3 subsets of the ABIDE I dataset used in published studies that have previously produced state-of-the-art results, evaluating performance under a leave-one-site-out cross-validation framework for better generalizeability to new data. Finally, we provide examples of interpreting functional network differences based on individual demographic variables.
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Chen B. A preliminary study of atypical cortical change ability of dynamic whole-brain functional connectivity in autism spectrum disorder. Int J Neurosci 2020; 132:213-225. [PMID: 32762276 DOI: 10.1080/00207454.2020.1806837] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
OBJECTIVES Designing new objectively diagnostic methods of autism spectrum disorder (ASD) are burning questions. Dynamic functional connectivity (DFC) methodology based on fMRI data are an effective lever to investigate changeability evolution of signal synchronization in macroscopic neural activity patterns. METHODS Embracing the network dynamics concepts, this paper introduces changeability index (C-score)which is focused on time-varying aspects of FCs, and develops a new framework for researching the roots of ASD brains at resting states in holism significance. The important process is to uncover noticeable regions and subsystems endowed with antagonistic stance in C-scores of between atypical and typical DFCs of 30 healthy controls (HCs) and 48 ASD patients. RESULTS The abnormities of edge C-scores are found across widespread brain cortex in ASD brains. For whole brain regional C-scores of ASD patients, orbitofrontal middle cortex L, inferior triangular frontal gyrus L, middle occipital gyrus L, postcentral gyrus L, supramarginal L, supramarginal R, cerebellum 8 L, and cerebellum 10 Rare endowed with significantly different C-scores.At brain subsystems level, C-scores in left hemisphere, right hemisphere, top hemisphere, bottom hemisphere, frontal lobe, parietal lobe, occipital lobe, cerebellum sub systems are abnormal in ASD patients. CONCLUSIONS The ASD brains have whole-brain abnormity on widespread regions. Through the strict evidence-based study, it was found that the changeability index (C-score) is a meaningful biological marker to explore cortical activity in ASD.
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Affiliation(s)
- Bo Chen
- School of Science, Hangzhou Dianzi University, Hangzhou, Zhejiang, PR China
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Abstract
Adaptive social behavior and mental well-being depend on not only recognizing emotional expressions but also, inferring the absence of emotion. While the neurobiology underwriting the perception of emotions is well studied, the mechanisms for detecting a lack of emotional content in social signals remain largely unknown. Here, using cutting-edge analyses of effective brain connectivity, we uncover the brain networks differentiating neutral and emotional body language. The data indicate greater activation of the right amygdala and midline cerebellar vermis to nonemotional as opposed to emotional body language. Most important, the effective connectivity between the amygdala and insula predicts people's ability to recognize the absence of emotion. These conclusions extend substantially current concepts of emotion perception by suggesting engagement of limbic effective connectivity in recognizing the lack of emotion in body language reading. Furthermore, the outcome may advance the understanding of overly emotional interpretation of social signals in depression or schizophrenia by providing the missing link between body language reading and limbic pathways. The study thus opens an avenue for multidisciplinary research on social cognition and the underlying cerebrocerebellar networks, ranging from animal models to patients with neuropsychiatric conditions.
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Abstract
Endophenotypes are measurable markers of genetic vulnerability to current or future disorder. Autism spectrum disorder (ASD) is well-suited to be examined within an endophenotype framework given past and current emphases on the broader autism phenotype and early detection. We conducted a scoping review to identify potential socially-related endophenotypes of ASD. We focused on paradigms related to sociality (e.g., theory of mind (TOM), social attention), which comprise most of this literature. We integrated findings from traditional behavioral paradigms with brain-based measures (e.g., electroencephalography, functional magnetic resonance imaging). Broadly, infant research regarding social attention and responsivity (Research Domain Criteria (RDoC) domain of affiliation) and attention to faces and voices (social communication) finds consistent abnormality in vulnerable infant siblings. Several additional paradigms that have shown differences in vulnerable infants and young children include animacy perception tasks (perception and understanding of others), measures of recognition and response to familiar faces (attachment), and joint attention and false-belief tasks (understanding mental states). Research areas such as alexithymia (the perception and understanding of self), empathic responding, and vocal prosody may hold interest; however, challenges in measurement across populations and age ranges is a limiting factor. Future work should address sex differences and age dependencies, specificity to ASD, and heterogeneous genetic pathways to disorder within samples individuals with ASD and relatives.
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Abstract
Laughter is a positive vocal emotional expression: most laughter is found in social interactions [1]. We are overwhelmingly more likely to laugh when we are with other people [1], and laughter can play a very important communicative role [2]. We do of course also laugh at humor - but can laughter influence how funny we actually perceive the humorous material to be? In this study, we show that the presence of laughter enhances how funny people find jokes and that this effect is increased for spontaneous laughter. This effect was present for both neurotypical and autistic participants, indicating similarities in their implicit processing of laughter.
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