1
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Girault JB, Nishino T, Talović M, Nebel MB, Reynolds M, Burrows CA, Elison JT, Lee CM, Snyder AZ, Shen MD, Shen AM, Botteron KN, Estes AM, Dager SR, Gerig G, Hazlett HC, Marrus N, McKinstry RC, Pandey J, Schultz RT, John TS, Styner MA, Zwaigenbaum L, Todorov AA, Piven J, Pruett JR. Functional connectivity between the visual and salience networks and autistic social features at school-age. J Neurodev Disord 2025; 17:23. [PMID: 40295911 PMCID: PMC12036130 DOI: 10.1186/s11689-025-09613-9] [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: 02/03/2025] [Accepted: 04/12/2025] [Indexed: 04/30/2025] Open
Abstract
BACKGROUND Autism spectrum disorder (ASD) is highly heritable and phenotypically variable. Neuroimaging markers reflecting variation in behavior will provide insights into circuitry subserving core features. We examined functional correlates of ASD symptomology at school-age, while accounting for associated behavioral and cognitive domains, in a longitudinal sample followed from infancy and enriched for those with a genetic liability for ASD. METHODS Resting state functional connectivity MRIs (fcMRI) and behavioral data were analyzed from 97 school-age children (8.1-12.0 years, 55 males, 15 ASD) with (n = 63) or without (n = 34) a family history of ASD. fcMRI enrichment analysis (EA) was used to screen for associations between network-level functional connectivity and six behaviors of interest in a data-driven manner: social affect, restricted and repetitive behavior (RRB), generalized anxiety, inattention, motor coordination, and matrix reasoning. RESULTS Functional connectivity between the visual and salience networks was significantly associated with social affect symptoms at school-age after accounting for all other behaviors. Results indicated that stronger connectivity was associated with higher social affect scores. No other behaviors were robustly associated with functional connectivity, though trends were observed between visual-salience connectivity and RRBs. CONCLUSIONS Connectivity between the visual and salience networks may play an important role in social affect symptom variability among children with ASD and those with genetic liability for ASD. These findings align with and extend earlier reports in this sample of the central role of the visual system during infancy in ASD.
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Grants
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K01-MH122779, R01-MH118362, MH118362-02S1 NIMH NIH HHS
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- K23HD112507, R01-HD055741, T32-HD040127, P30-HD003110, P50-HD103573 National Institute of Child Health and Human Development
- P30-NS098577 NINDS NIH HHS
- #140209 Simons Foundation
- National Institute of Mental Health
- National Institute of Neurological Disorders and Stroke
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Affiliation(s)
- Jessica B Girault
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Campus Box #3367, Chapel Hill, NC, USA.
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Tomoyuki Nishino
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Muhamed Talović
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Mary Beth Nebel
- Center for Neurodevelopmental and Imaging Research, Kennedy Krieger Institute, Baltimore, MD, USA
| | - Margaret Reynolds
- Department of Ophthalmology and Visual Sciences, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | | | - Jed T Elison
- Institute of Child Development, University of Minnesota, Minneapolis, MN, USA
| | - Chimei M Lee
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Abraham Z Snyder
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Mark D Shen
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Campus Box #3367, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Kelly N Botteron
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Annette M Estes
- Department of Speech and Hearing Science, University of Washington, Seattle, WA, USA
| | - Stephen R Dager
- Department of Radiology, University of Washington Medical Center, Seattle, WA, USA
| | - Guido Gerig
- Tandon School of Engineering, New York University, New York, NY, USA
| | - Heather C Hazlett
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Campus Box #3367, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Natasha Marrus
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Robert C McKinstry
- Department of Radiology, Washington University in St. Louis, St. Louis, MO, USA
| | - Juhi Pandey
- Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Robert T Schultz
- Center for Autism Research, Children's Hospital of Philadelphia, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Tanya St John
- Department of Speech and Hearing Science, University of Washington, Seattle, WA, USA
| | - Martin A Styner
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | | | - Alexandre A Todorov
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
| | - Joseph Piven
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Campus Box #3367, Chapel Hill, NC, USA
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - John R Pruett
- Department of Psychiatry, Washington University School of Medicine in St. Louis, St. Louis, MO, USA
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2
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Bagheri S, Yu JC, Gallucci J, Tan V, Oliver LD, Dickie EW, Rashidi AG, Foussias G, Lai MC, Buchanan RW, Malhotra AK, Voineskos AN, Ameis SH, Hawco C. Transdiagnostic Neurobiology of Social Cognition and Individual Variability as Measured by Fractional Amplitude of Low-Frequency Fluctuation in Autism and Schizophrenia Spectrum Disorders. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2025:S2451-9022(25)00132-6. [PMID: 40268245 DOI: 10.1016/j.bpsc.2025.04.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2024] [Revised: 04/09/2025] [Accepted: 04/10/2025] [Indexed: 04/25/2025]
Abstract
BACKGROUND Fractional amplitude of low-frequency fluctuation (fALFF) is a validated measure of resting-state spontaneous brain activity. Previous fALFF findings in autism and schizophrenia spectrum disorders (SSDs) have been highly heterogeneous. We aimed to use fALFF in a large sample of typically developing control (TDC), autistic, and SSD participants to explore group differences and relationships with inter-individual variability of fALFF maps and social cognition. METHODS FALFF from 495 participants (185 TDC, 68 autism, and 242 SSD) was computed using functional magnetic resonance imaging as signal power within two frequency bands (i.e., slow-4 and slow-5), normalized by the power in the remaining frequency spectrum. Permutation analysis of linear models was employed to investigate the relationship of fALFF with diagnostic groups, higher-level social cognition, and lower-level social cognition. Each participant's average distance of fALFF map to all others was defined as a variability score, with higher scores indicating less typical maps. RESULTS Lower fALFF in the visual and higher fALFF in the frontal regions were found in both SSD and autistic participants compared with TDCs. Limited differences were observed between autistic and SSD participants in the cuneus regions only. Associations between slow-4 fALFF and higher-level social cognitive scores across the whole sample were observed in the lateral occipitotemporal and temporoparietal junction. Individual variability within the autism and SSD groups was also significantly higher compared with TDC. CONCLUSIONS Similar patterns of fALFF and individual variability in autism and SSD suggest some common neurobiological features across these related heterogeneous conditions.
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Affiliation(s)
- Soroush Bagheri
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Ju-Chi Yu
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Julia Gallucci
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Vinh Tan
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
| | - Lindsay D Oliver
- 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
| | - Erin W Dickie
- 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
| | - Ayesha G Rashidi
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - George Foussias
- 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; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Meng-Chuan Lai
- 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; Institute of Medical Science, University of Toronto, Toronto, ON, Canada; Research Institute, and Department of Psychiatry, The Hospital for Sick Children, Toronto, ON, Canada; Department of Psychology, University of Toronto, Toronto, Ontario, Canada; Autism Research Centre, Department of Psychiatry, University of Cambridge, Cambridge, United Kingdom; Department of Psychiatry, National Taiwan University Hospital and College of Medicine, Taipei, Taiwan
| | - Robert W Buchanan
- Maryland Psychiatric Research Centre, Department of Psychiatry, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Anil K Malhotra
- Division of Psychiatry Research, The Zucker Hillside Hospital, Division of Northwell Health, Glen Oaks, NY, USA; The Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Department of Psychiatry, Hempstead, NY, USA; Centre for Psychiatric Neuroscience, The Feinstein Institute for Medical Research, Manhasset, NY, USA
| | - Aristotle N Voineskos
- 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; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Stephanie H Ameis
- Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada; Cundill Centre for Child and Youth Depression, 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; Institute of Medical Science, University of Toronto, Toronto, ON, Canada
| | - Colin Hawco
- 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; Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
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3
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Feldman D, Prigge M, Alexander A, Zielinski B, Lainhart J, King J. Flexible nonlinear modeling reveals age-related differences in resting-state functional brain connectivity in autistic males from childhood to mid-adulthood. Mol Autism 2025; 16:24. [PMID: 40234995 PMCID: PMC11998146 DOI: 10.1186/s13229-025-00657-1] [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: 11/28/2024] [Accepted: 03/22/2025] [Indexed: 04/17/2025] Open
Abstract
BACKGROUND Divergent age-related functional brain connectivity in autism spectrum disorder (ASD) has been observed using resting-state fMRI, although the specific findings are inconsistent across studies. Common statistical regression approaches that fit identical models across functional brain networks may contribute to these inconsistencies. Relationships among functional networks have been reported to follow unique nonlinear developmental trajectories, suggesting the need for flexible modeling. Here we apply generalized additive models (GAMs) to flexibly adapt to distinct network trajectories and simultaneously describe divergent age-related changes from childhood into mid-adulthood in ASD. METHODS 1107 males, aged 5-40, from the ABIDE I & II cross-sectional datasets were analyzed. Functional connectivity was extracted using a network-based template. Connectivity values were harmonized using COMBAT-GAM. Connectivity-age relationships were assessed with thin-plate spline GAMs. Post-hoc analyses defined the age-ranges of divergent aging in ASD. RESULTS Typically developing (TD) and ASD groups shared 15 brain connections that significantly changed with age (FDR-corrected p < 0.05). Network connectivity exhibited diverse nonlinear age-related trajectories across the functional connectome. Comparing ASD and TD groups, default mode to central executive between-network connectivity followed similar nonlinear paths with no group differences. Contrarily, the ASD group had chronic hypoconnectivity throughout default mode-ventral attentional (salience) and default mode-somatomotor aging trajectories. Within-network somatomotor connectivity was similar between groups in childhood but diverged in adolescence with the ASD group showing decreased within-network connectivity. Network connectivity between the somatomotor network and various other functional networks had fully disrupted age-related pathways in ASD compared to TD, displaying significantly different model curvatures and fits. LIMITATIONS The present analysis includes only male participants and has a restricted age range, limiting analysis of early development and later life aging, years 40 and beyond. Additionally, our analysis is limited to large-scale network cortical functional parcellation. To parse more specificity of brain region connectivity, a fine-grained functional parcellation including subcortical areas may be warranted. CONCLUSION Flexible non-linear modeling minimizes statistical assumptions and allows diagnosis-related brain connections to follow independent data-driven age-related pathways. Using GAMs, we describe complex age-related pathways throughout the human connectome and observe distinct periods of divergence in autism.
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Affiliation(s)
- Daniel Feldman
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, 84112, USA.
- Department of Radiology & Imaging Sciences, University of Utah, Salt Lake City, UT, 84112, USA.
| | - Molly Prigge
- Department of Radiology & Imaging Sciences, University of Utah, Salt Lake City, UT, 84112, USA
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Andrew Alexander
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Medical Physics, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Brandon Zielinski
- Department of Radiology & Imaging Sciences, University of Utah, Salt Lake City, UT, 84112, USA
- Department of Pediatrics, Neurology, and Neuroscience, University of Florida, Gainesville, FL, 32611, USA
| | - Janet Lainhart
- Waisman Center, University of Wisconsin-Madison, Madison, WI, 53706, USA
- Department of Psychiatry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Jace King
- Department of Biomedical Engineering, University of Utah, Salt Lake City, UT, 84112, USA.
- Department of Radiology & Imaging Sciences, University of Utah, Salt Lake City, UT, 84112, USA.
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4
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Itahashi T, Yamashita A, Takahara Y, Yahata N, Aoki YY, Fujino J, Yoshihara Y, Nakamura M, Aoki R, Okimura T, Ohta H, Sakai Y, Takamura M, Ichikawa N, Okada G, Okada N, Kasai K, Tanaka SC, Imamizu H, Kato N, Okamoto Y, Takahashi H, Kawato M, Yamashita O, Hashimoto RI. Generalizable and transportable resting-state neural signatures characterized by functional networks, neurotransmitters, and clinical symptoms in autism. Mol Psychiatry 2025; 30:1466-1478. [PMID: 39342041 PMCID: PMC11919695 DOI: 10.1038/s41380-024-02759-3] [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: 11/10/2023] [Revised: 09/10/2024] [Accepted: 09/19/2024] [Indexed: 10/01/2024]
Abstract
Autism spectrum disorder (ASD) is a lifelong condition with elusive biological mechanisms. The complexity of factors, including inter-site and developmental differences, hinders the development of a generalizable neuroimaging classifier for ASD. Here, we developed a classifier for ASD using a large-scale, multisite resting-state fMRI dataset of 730 Japanese adults, aiming to capture neural signatures that reflect pathophysiology at the functional network level, neurotransmitters, and clinical symptoms of the autistic brain. Our adult ASD classifier was successfully generalized to adults in the United States, Belgium, and Japan. The classifier further demonstrated its successful transportability to children and adolescents. The classifier contained 141 functional connections (FCs) that were important for discriminating individuals with ASD from typically developing controls. These FCs and their terminal brain regions were associated with difficulties in social interaction and dopamine and serotonin, respectively. Finally, we mapped attention-deficit/hyperactivity disorder (ADHD), schizophrenia (SCZ), and major depressive disorder (MDD) onto the biological axis defined by the ASD classifier. ADHD and SCZ, but not MDD, were located proximate to ASD on the biological dimensions. Our results revealed functional signatures of the ASD brain, grounded in molecular characteristics and clinical symptoms, achieving generalizability and transportability applicable to the evaluation of the biological continuity of related diseases.
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Affiliation(s)
- Takashi Itahashi
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Ayumu Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Yuji Takahara
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Drug Discovery Research Division, Shionogi & Co., Ltd., Osaka, Japan
| | - Noriaki Yahata
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Institute for Quantum Life Science, National Institutes for Quantum Science and Technology, Chiba, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- Department of Quantum Life Science, Graduate School of Science and Engineering, Chiba University, Chiba, Japan
| | - Yuta Y Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Psychiatry, Aoki Clinic, Tokyo, Japan
| | - Junya Fujino
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yujiro Yoshihara
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Motoaki Nakamura
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Ryuta Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Language Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Tsukasa Okimura
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Haruhisa Ohta
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Yuki Sakai
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- XNef, Inc., Kyoto, Japan
| | - Masahiro Takamura
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
- Department of Neurology, Shimane University, Shimane, Japan
| | - Naho Ichikawa
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan
- UTokyo Institute for Diversity and Adaptation of Human Mind (UTIDAHM), The University of Tokyo, Tokyo, Japan
| | - Saori C Tanaka
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Division of Information Science, Nara Institute of Science and Technology, Nara, Japan
| | - Hiroshi Imamizu
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Department of Psychology, Graduate School of Humanities and Sociology, The University of Tokyo, Tokyo, Japan
| | - Nobumasa Kato
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Hidehiko Takahashi
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Center for Brain Integration Research, Tokyo Medical and Dental University, Tokyo, Japan
| | - Mitsuo Kawato
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- XNef, Inc., Kyoto, Japan
| | - Okito Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Center for Advanced Intelligence Project, RIKEN, Tokyo, Japan
| | - Ryu-Ichiro Hashimoto
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan.
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan.
- Department of Language Sciences, Tokyo Metropolitan University, Tokyo, Japan.
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5
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Czekóová K, Mareček R, Staněk R, Hartley C, Kessler K, Hlavatá P, Ošlejšková H, Brázdil M, Shaw DJ. Altered Patterns of Dynamic Functional Connectivity Underpin Reduced Expressions of Social-Emotional Reciprocity in Autistic Adults. Autism Res 2025; 18:725-740. [PMID: 39994920 PMCID: PMC12015814 DOI: 10.1002/aur.70010] [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: 09/18/2024] [Revised: 02/07/2025] [Accepted: 02/12/2025] [Indexed: 02/26/2025]
Abstract
To identify the neurocognitive mechanisms underpinning the social difficulties that characterize autism, we performed functional magnetic resonance imaging on pairs of autistic and non-autistic adults simultaneously whilst they interacted with one another on the iterated Ultimatum Game (iUG)-an interactive task that emulates the reciprocal characteristic of naturalistic interpersonal exchanges. Two age-matched sets of male-male dyads were investigated: 16 comprised an autistic Responder and a non-autistic Proposer, and 19 comprised non-autistic pairs of Responder and Proposer. Players' round-by-round behavior on the iUG was modeled as reciprocal choices, and dynamic functional connectivity (dFC) was measured to identify the neural mechanisms underpinning reciprocal behaviors. Behavioral expressions of reciprocity were significantly reduced in autistic compared with non-autistic Responders, yet no such differences were observed between the non-autistic Proposers in either set of dyads. Furthermore, we identified latent dFC states with temporal properties associated with reciprocity. Autistic interactants spent less time in brain states characterized by dynamic inter-network integration and segregation among the Default Mode Network and cognitive control networks, suggesting that their reduced expressions of social-emotional reciprocity reflect less efficient reconfigurations among brain networks supporting flexible cognition and behavior. These findings advance our mechanistic understanding of the social difficulties characterizing autism.
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Affiliation(s)
- Kristína Czekóová
- Behavioural and Social Neuroscience Research Group, Central European Institute of Technology (CEITEC)Masaryk UniversityBrnoCzechia
- Institute of PsychologyCzech Academy of SciencesBrnoCzechia
- First Department of Neurology, Faculty of MedicineMasaryk UniversityBrnoCzechia
| | - Radek Mareček
- Multimodal and Functional Neuroimaging Laboratory (MAFIL), Central European Institute of Technology (CEITEC)Masaryk UniversityBrnoCzechia
| | - Rostislav Staněk
- Department of Economics, Faculty of Economics and AdministrationMasaryk UniversityBrnoCzechia
| | - Calum Hartley
- Department of PsychologyLancaster UniversityLancasterUK
| | - Klaus Kessler
- School of PsychologyUniversity College DublinDublinIreland
| | - Pavlína Hlavatá
- Behavioural and Social Neuroscience Research Group, Central European Institute of Technology (CEITEC)Masaryk UniversityBrnoCzechia
| | - Hana Ošlejšková
- Department of Child NeurologyUniversity Hospital Brno and Masaryk UniversityBrnoCzechia
| | - Milan Brázdil
- Behavioural and Social Neuroscience Research Group, Central European Institute of Technology (CEITEC)Masaryk UniversityBrnoCzechia
- First Department of NeurologySt. Anne's University Hospital and Faculty of Medicine, Masaryk UniversityBrnoCzechia
| | - Daniel Joel Shaw
- Behavioural and Social Neuroscience Research Group, Central European Institute of Technology (CEITEC)Masaryk UniversityBrnoCzechia
- First Department of Neurology, Faculty of MedicineMasaryk UniversityBrnoCzechia
- Department of Psychology, School of Life and Health SciencesAston UniversityBirminghamUK
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6
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Kim GS, Chandio BQ, Benavidez SM, Feng Y, Thompson PM, Lawrence KE. Mapping Along-Tract White Matter Microstructural Differences in Autism. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2025:2025.03.21.644498. [PMID: 40196471 PMCID: PMC11974747 DOI: 10.1101/2025.03.21.644498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 04/09/2025]
Abstract
Previous diffusion magnetic resonance imaging (dMRI) research has indicated altered white matter microstructure in autism, but the implicated regions are highly inconsistent across studies. Such prior work has largely used conventional dMRI analysis methods, including the traditional microstructure model, based on diffusion tensor imaging (DTI). However, these methods are limited in their ability to precisely map microstructural differences and accurately resolve complex fiber configurations. In our study, we investigated white matter microstructure alterations in autism using the refined along-tract analytic approach, BUndle ANalytics (BUAN), and an advanced microstructure model, the tensor distribution function (TDF). We analyzed dMRI data from 365 autistic and neurotypical participants (5-24 years; 34% female) from 10 cohorts to examine commissural and association tracts. Autism was associated with lower fractional anisotropy and higher diffusivity in localized portions of nearly every commissural and association tract examined; these tracts inter-connected a wide range of brain regions, including frontal, temporal, parietal, and occipital. Taken together, BUAN and TDF allow robust and spatially precise mapping of microstructural properties in autism. Our findings rigorously demonstrate that white matter microstructure alterations in autism may be greater within specific regions of individual tracts, and that the implicated tracts are distributed across the brain.
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Affiliation(s)
- Gaon S Kim
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, 1670 Mindanao Way, Marina del Rey, CA, 90292 USA
| | - Bramsh Q Chandio
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, 1670 Mindanao Way, Marina del Rey, CA, 90292 USA
| | - Sebastian M Benavidez
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, 1670 Mindanao Way, Marina del Rey, CA, 90292 USA
| | - Yixue Feng
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, 1670 Mindanao Way, Marina del Rey, CA, 90292 USA
| | - Paul M Thompson
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, 1670 Mindanao Way, Marina del Rey, CA, 90292 USA
| | - Katherine E Lawrence
- Imaging Genetics Center, Mark and Mary Stevens Neuroimaging & Informatics Institute, Keck School of Medicine, University of Southern California, 1670 Mindanao Way, Marina del Rey, CA, 90292 USA
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7
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Girault JB. The developing visual system: A building block on the path to autism. Dev Cogn Neurosci 2025; 73:101547. [PMID: 40096794 PMCID: PMC11964655 DOI: 10.1016/j.dcn.2025.101547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2024] [Revised: 02/17/2025] [Accepted: 03/03/2025] [Indexed: 03/19/2025] Open
Abstract
Longitudinal neuroimaging studies conducted over the past decade provide evidence of atypical visual system development in the first years of life in autism spectrum disorder (ASD). Findings from genomic analyses, family studies, and postmortem investigations suggest that changes in the visual system in ASD are linked to genetic factors, making the visual system an important neural phenotype along the path from genes to behavior that deserves further study. This article reviews what is known about the developing visual system in ASD in the first years of life; it also explores the potential canalizing role that atypical visual system maturation may have in the emergence of ASD by placing findings in the context of developmental cascades involving brain development, attention, and social and cognitive development. Critical gaps in our understanding of human visual system development are discussed, and future research directions are proposed to improve our understanding of ASD as a complex neurodevelopmental disorder with origins in early brain development.
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Affiliation(s)
- Jessica B Girault
- Carolina Institute for Developmental Disabilities, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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8
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Zhang Y, Zhou Q, Gao L, Li J, Li H, Ji G, Yang H, Wang E, Wang K, Li D. Abnormal Functional Connectivity of the Primary Sensory Network in Autism Spectrum Disorder: Sex Differences, Early Overdevelopment, and Clinical Significance. Brain Behav 2025; 15:e70363. [PMID: 40123151 PMCID: PMC11930894 DOI: 10.1002/brb3.70363] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2024] [Revised: 01/10/2025] [Accepted: 02/04/2025] [Indexed: 03/25/2025] Open
Abstract
INTRODUCTION Primary sensory processing is atypical in patients with autism spectrum disorder (ASD) and affects daily functioning. However, the functional connectivity (FC) patterns of primary networks in ASD have not been systematically investigated. METHODS Primary networks were defined as four regions of interest (ROIs) in each brain hemisphere. We analyzed ROI-wise FC in 105 individuals with ASD and 132 typically developing (TD) participants from Autism Brain Imaging Data Exchange I. We calculated the correlation between abnormal FC and clinical scores. Additionally, data from 53 individuals with ASD from our laboratory's two-site dataset were used to validate the results and assess the effects of sex and age on FC consistency. RESULTS Regarding the ROI-wise connectivity, significant group differences in FC emerged in several regional pairs, particularly in the primary auditory and somatosensory regions. Abnormal brain regions correlated with clinical symptoms. As age increased, abnormal FC had an initial fast and then slowing development trend, and the abnormal FC in females was higher than that in males. The two-site dataset results were consistent with those of the multisite dataset in assessing the influence of age and sex on FC. CONCLUSION Abnormal FC exists in the primary sensory cortex of patients with ASD, which correlates with clinical outcomes and may cause impairments in advanced cognitive functions. In addition, the primary sensory cortex of patients with ASD may undergo excessive growth in the early stages and demonstrate imbalanced development according to sex. These findings may help identify new biomarkers for ASD.
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Affiliation(s)
- Yanan Zhang
- School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiChina
| | - Quan Zhou
- First Clinical Medical CollegeAnhui Medical UniversityHefeiChina
| | - Limei Gao
- School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiChina
| | - Jingwen Li
- School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiChina
| | - Hong Li
- Anhui Hospital Affiliated to the Pediatric Hospital of Fudan University (Anhui Provincial Children's Hospital)HefeiChina
| | - Gong‐Jun Ji
- School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiChina
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiChina
| | - Hua Yang
- First Clinical Medical CollegeAnhui Medical UniversityHefeiChina
| | - Enze Wang
- First Clinical Medical CollegeAnhui Medical UniversityHefeiChina
| | - Kai Wang
- Collaborative Innovation Center of Neuropsychiatric Disorders and Mental HealthHefeiChina
- Department of NeurologyThe First Affiliated Hospital of Anhui Medical UniversityHefeiChina
| | - Dandan Li
- School of Mental Health and Psychological SciencesAnhui Medical UniversityHefeiChina
- Research Center for Translational MedicineThe Second Hospital of Anhui Medical UniversityHefeiChina
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9
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Hill AT, Ford TC, Bailey NW, Lum JAG, Bigelow FJ, Oberman LM, Enticott PG. EEG during dynamic facial emotion processing reveals neural activity patterns associated with autistic traits in children. Cereb Cortex 2025; 35:bhaf020. [PMID: 39927786 PMCID: PMC11808805 DOI: 10.1093/cercor/bhaf020] [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: 08/27/2024] [Revised: 12/09/2024] [Accepted: 01/21/2025] [Indexed: 02/11/2025] Open
Abstract
Altered brain connectivity and atypical neural oscillations have been observed in autism, yet their relationship with autistic traits in nonclinical populations remains underexplored. Here, we employ electroencephalography to examine functional connectivity, oscillatory power, and broadband aperiodic activity during a dynamic facial emotion processing task in 101 typically developing children aged 4 to 12 years. We investigate associations between these electrophysiological measures of brain dynamics and autistic traits as assessed by the Social Responsiveness Scale, 2nd Edition (SRS-2). Our results revealed that increased facial emotion processing-related connectivity across theta (4 to 7 Hz) and beta (13 to 30 Hz) frequencies correlated positively with higher SRS-2 scores, predominantly in right-lateralized (theta) and bilateral (beta) cortical networks. Additionally, a steeper 1/f-like aperiodic slope (spectral exponent) across fronto-central electrodes was associated with higher SRS-2 scores. Greater aperiodic-adjusted theta and alpha oscillatory power further correlated with both higher SRS-2 scores and steeper aperiodic slopes. These findings underscore important links between facial emotion processing-related brain dynamics and autistic traits in typically developing children. Future work could extend these findings to assess these electroencephalography-derived markers as potential mechanisms underlying behavioral difficulties in autism.
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Affiliation(s)
- Aron T Hill
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC 3125, Australia
| | - Talitha C Ford
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC 3125, Australia
- Centre for Mental Health and Brain Sciences, Swinburne University of Technology, Hawthorn, VIC 3122, Australia
| | - Neil W Bailey
- School of Medicine and Psychology, The Australian National University, Canberra, ACT 2601, Australia
- Monarch Research Institute, Monarch Mental Health Group, Sydney, New South Wales 2000, Australia
| | - Jarrad A G Lum
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC 3125, Australia
| | - Felicity J Bigelow
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC 3125, Australia
| | - Lindsay M Oberman
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Peter G Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, VIC 3125, Australia
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10
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Stillesjö S, Hjärtström H, Johansson A, Rudolfsson T, Säfström D, Domellöf E. Action execution and observation in autistic adults: A systematic review of fMRI studies. Autism Res 2025; 18:238-260. [PMID: 39673256 PMCID: PMC11826028 DOI: 10.1002/aur.3291] [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: 05/23/2024] [Accepted: 12/02/2024] [Indexed: 12/16/2024]
Abstract
Motor impairments are common in individuals with autism spectrum disorder (ASD) although less is known about the neural mechanisms related to such difficulties. This review provides an outline of functional magnetic resonance imaging (fMRI) findings associated with execution and observation of naturalistic actions in autistic adults. Summarized outcomes revealed that adults with ASD recruit similar brain regions as neurotypical adults during action execution and during action observation, although with a difference in direction and/or magnitude. For action execution, this included higher and lower activity bilaterally in the precentral cortex, the parietal cortex, the inferior frontal gyrus (IFG), the middle temporal gyrus (MTG), the occipital cortex, and the cerebellum. For action observation, differences mainly concerned both higher and lower activity in bilateral IFG and right precentral gyrus, and lower activity in MTG. Activity overlaps between action execution and observation highlight atypical recruitment of IFG, MTG, precentral, and parieto-occipital regions in ASD. The results show atypical recruitment of brain regions subserving motor planning and/or predictive control in ASD. Atypical brain activations during action observation, and the pattern of activity overlaps, indicate an association with difficulties in understanding others' actions and intentions.
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Affiliation(s)
- Sara Stillesjö
- Department of PsychologyUmeå UniversityUmeåSweden
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
| | - Hanna Hjärtström
- Department of PsychologyUmeå UniversityUmeåSweden
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
| | - Anna‐Maria Johansson
- Department of PsychologyUmeå UniversityUmeåSweden
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
- Department of Health, Education and TechnologyLuleå University of TechnologyLuleåSweden
| | - Thomas Rudolfsson
- Department of PsychologyUmeå UniversityUmeåSweden
- Department of Occupational Health, Psychology and Sports SciencesUniversity of GävleGävleSweden
| | - Daniel Säfström
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
- Department of Medical and Translational BiologyUmeå UniversityUmeåSweden
| | - Erik Domellöf
- Department of PsychologyUmeå UniversityUmeåSweden
- Umeå Center for Functional Brain Imaging (UFBI)Umeå UniversityUmeåSweden
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11
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Li X, Wu S, Yang W, Jiang C, Zhao Z, Wang H, Lin F. Abnormal resting-state brain network dynamics in toddlers with autism spectrum disorder. Eur Child Adolesc Psychiatry 2025:10.1007/s00787-025-02651-7. [PMID: 39853404 DOI: 10.1007/s00787-025-02651-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2024] [Accepted: 01/16/2025] [Indexed: 01/26/2025]
Abstract
Emerging evidence suggests aberrant functional connectivity (FC) of brain networks in children, adolescents, and adults with autism spectrum disorder (ASD). However, little is known about alterations of dynamic FC in toddlers with ASD. The aim of this study was to investigate the characteristics of brain network dynamics in ASD toddlers. We analyzed resting-state functional magnetic resonance imaging data of 41 ASD and 23 typically-developing (TD) toddlers aged 15-45 months using leading eigenvector dynamics analysis. The between-group differences in the temporal properties of state were evaluated, followed by correlation analysis of these differences with autistic factors in ASD. Compared with TD subjects, ASD toddlers had a lower occurrence rate and mean dwell time in the global state. The mean dwell time of this state was negatively correlated with the body and object use of the autism behavior checklist (ABC) score. The ASD group presented a higher occurrence probability in the state related to the visual network, and the dwell time of this state was positively correlated with the relationship building of the ABC score. Moreover, the occurrence probability of the state related to the dorsal attention network and default mode network was positively correlated with the body and object use of the ABC score. Our findings indicate that there are differences in the developmental patterns of large-scale brain functional networks in ASD toddlers, which may contribute to the early identification of ASD and provide meaningful insights into its potential neural mechanisms.
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Affiliation(s)
- Xiuxian Li
- National Center for Magnetic Resonance in Wuhan, State Key Laboratory of Magnetic Resonance Spectroscopy and Imaging, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China
- University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Shengjuan Wu
- Department of Child Health Care, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430070, China
| | - Wenzhong Yang
- Department of Radiology, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430070, China
| | - Chengcheng Jiang
- Department of Radiology, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430070, China
| | - Zhiwei Zhao
- Department of Child Health Care, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430070, China
| | - Hong Wang
- Department of Child Health Care, Maternal and Child Health Hospital of Hubei Province, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430070, China.
| | - Fuchun Lin
- National Center for Magnetic Resonance in Wuhan, State Key Laboratory of Magnetic Resonance Spectroscopy and Imaging, Wuhan Institute of Physics and Mathematics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, 430071, China.
- University of Chinese Academy of Sciences, Beijing, 100049, China.
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12
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Horien C, Mandino F, Greene AS, Shen X, Powell K, Vernetti A, O’Connor D, McPartland JC, Volkmar FR, Chun M, Chawarska K, Lake EM, Rosenberg MD, Satterthwaite T, Scheinost D, Finn E, Constable RT. What is the best brain state to predict autistic traits? MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2025:2025.01.14.24319457. [PMID: 39867399 PMCID: PMC11759253 DOI: 10.1101/2025.01.14.24319457] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 01/28/2025]
Abstract
Autism is a heterogeneous condition, and functional magnetic resonance imaging-based studies have advanced understanding of neurobiological correlates of autistic features. Nevertheless, little work has focused on the optimal brain states to reveal brain-phenotype relationships. In addition, there is a need to better understand the relevance of attentional abilities in mediating autistic features. Using connectome-based predictive modelling, we interrogate three datasets to determine scanning conditions that can boost prediction of clinically relevant phenotypes and assess generalizability. In dataset one, a sample of youth with autism and neurotypical participants, we find that a sustained attention task (the gradual onset continuous performance task) results in high prediction performance of autistic traits compared to a free-viewing social attention task and a resting-state condition. In dataset two, we observe the predictive network model of autistic traits generated from the sustained attention task generalizes to predict measures of attention in neurotypical adults. In dataset three, we show the same predictive network model of autistic traits from dataset one further generalizes to predict measures of social responsiveness in data from the Autism Brain Imaging Data Exchange. In sum, our data suggest that an in-scanner sustained attention challenge can help delineate robust markers of autistic traits and support the continued investigation of the optimal brain states under which to predict phenotypes in psychiatric conditions.
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Affiliation(s)
- Corey Horien
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- MD-PhD Program, Yale School of Medicine, New Haven, CT, USA
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), University of Pennsylvania, Philadelphia, PA, USA
| | - Francesca Mandino
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Abigail S. Greene
- MD-PhD Program, Yale School of Medicine, New Haven, CT, USA
- Department of Psychiatry, Brigham and Women’s Hospital, Boston, MA, USA
| | - Xilin Shen
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
| | - Kelly Powell
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
| | | | - David O’Connor
- BioMedical Engineering and Imaging Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - James C. McPartland
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Fred R. Volkmar
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
- Department of Psychology, Yale University, New Haven, CT, United States
| | - Marvin Chun
- Department of Psychology, Yale University, New Haven, CT, United States
- Wu Tsai Institute, Yale University, New Haven, CT, USA
| | - Katarzyna Chawarska
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT, USA
- Department of Pediatrics, Yale School of Medicine, New Haven, CT, USA
| | - Evelyn M.R. Lake
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Monica D. Rosenberg
- Department of Psychology, University of Chicago, Chicago, IL, USA
- Neuroscience Institute, University of Chicago, Chicago, IL, USA
| | - Theodore Satterthwaite
- Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA
- Penn Lifespan Informatics and Neuroimaging Center (PennLINC), University of Pennsylvania, Philadelphia, PA, USA
- Penn-CHOP Lifespan Brain Institute, University of Pennsylvania, Philadelphia, PA, USA
| | - Dustin Scheinost
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
- Child Study Center, Yale School of Medicine, New Haven, CT, USA
- Wu Tsai Institute, Yale University, New Haven, CT, USA
- Department of Statistics and Data Science, Yale University, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
| | - Emily Finn
- Department of Psychological and Brain Sciences, Dartmouth College, Dartmouth, NH, USA
| | - R. Todd Constable
- MD-PhD Program, Yale School of Medicine, New Haven, CT, USA
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, CT, USA
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
- Interdepartmental Neuroscience Program, Yale University, New Haven, CT, USA
- Department of Neurosurgery, Yale School of Medicine, New Haven, CT, USA
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13
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Segal A, Tiego J, Parkes L, Holmes AJ, Marquand AF, Fornito A. Embracing variability in the search for biological mechanisms of psychiatric illness. Trends Cogn Sci 2025; 29:85-99. [PMID: 39510933 PMCID: PMC11742270 DOI: 10.1016/j.tics.2024.09.010] [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: 05/31/2024] [Revised: 09/23/2024] [Accepted: 09/24/2024] [Indexed: 11/15/2024]
Abstract
Despite decades of research, we lack objective diagnostic or prognostic biomarkers of mental health problems. A key reason for this limited progress is a reliance on the traditional case-control paradigm, which assumes that each disorder has a single cause that can be uncovered by comparing average phenotypic values of patient and control samples. Here, we discuss the problematic assumptions on which this paradigm is based and highlight recent efforts that seek to characterize, rather than minimize, the inherent clinical and biological variability that underpins psychiatric populations. Embracing such variability is necessary to understand pathophysiological mechanisms and develop more targeted and effective treatments.
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Affiliation(s)
- Ashlea Segal
- Wu-Tsai Institute, and Department of Neuroscience, School of Medicine, Yale University, New Haven, CT 06520, USA; School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia.
| | - Jeggan Tiego
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
| | - Linden Parkes
- Brain Health Institute, Department of Psychiatry, Rutgers University, Piscataway, NJ 08854, USA
| | - Avram J Holmes
- Brain Health Institute, Department of Psychiatry, Rutgers University, Piscataway, NJ 08854, USA
| | - Andre F Marquand
- Department of Cognitive Neuroscience, Radboud UMC, 6500 HB Nijmegen, The Netherlands; Donders Institute for Cognition, Brain and Behavior, 6525 EN Nijmegen, The Netherlands
| | - Alex Fornito
- School of Psychological Sciences, Turner Institute for Brain and Mental Health, and Monash Biomedical Imaging, Monash University, Melbourne 3800, Australia
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14
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Chen Y, Yang C, Gao B, Chen K, Jao Keehn RJ, Müller RA, Yuan LX, You Y. Altered Functional Connectivity of Unimodal Sensory and Multisensory Integration Networks Is Related to Symptom Severity in Autism Spectrum Disorder. BIOLOGICAL PSYCHIATRY. COGNITIVE NEUROSCIENCE AND NEUROIMAGING 2024:S2451-9022(24)00313-6. [PMID: 39491786 DOI: 10.1016/j.bpsc.2024.10.014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/15/2024] [Revised: 10/11/2024] [Accepted: 10/22/2024] [Indexed: 11/05/2024]
Abstract
BACKGROUND Atypical sensory processing is a prevalent feature of autism spectrum disorder (ASD) and constitutes a core diagnostic criterion in DSM-5. However, the neurocognitive underpinnings of atypical unimodal and multimodal sensory processing and their relationships with autism symptoms remain unclear. METHODS In this study, we examined intrinsic functional connectivity (FC) patterns among 5 unimodal sensory and multisensory integration (MSI) networks in ASD using a large multisite dataset (N = 646) and investigated the relationships between altered FC, atypical sensory processing, social communicative deficits, and overall autism symptoms using correlation and mediation analyses. RESULTS Compared with typically developing control participants, participants in the ASD group demonstrated increased FC of the olfactory network, decreased FC within the MSI network, and decreased FC of the MSI-unimodal sensory networks. Furthermore, altered FC was positively associated with autism symptom severity, and such associations were completely mediated by atypical sensory processing and social communicative deficits. CONCLUSIONS ASD-specific olfactory overconnectivity and MSI-unimodal sensory underconnectivity lend support to the intense world theory and weak central coherence theory, suggesting olfactory hypersensitivity at the expense of MSI as a potential neural mechanism underlying atypical sensory processing in ASD. These atypical FC patterns suggest potential targets for psychological and neuromodulatory interventions.
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Affiliation(s)
- Yahui Chen
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Chen Yang
- Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, Zhejiang, China; Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, Zhejiang, China
| | - Bicheng Gao
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, Zhejiang, China
| | - Kehui Chen
- Institute of Psychological Sciences, Hangzhou Normal University, Hangzhou, Zhejiang, China
| | - R Joanne Jao Keehn
- Department of Psychology, San Diego State University, San Diego, California
| | - Ralph-Axel Müller
- Department of Psychology, San Diego State University, San Diego, California
| | - Li-Xia Yuan
- School of Physics, Zhejiang University, Hangzhou, Zhejiang, China.
| | - Yuqi You
- Department of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, Zhejiang, China.
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15
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Halliday AR, Vucic SN, Georges B, LaRoche M, Mendoza Pardo MA, Swiggard LO, McDonald K, Olofsson M, Menon SN, Francis SM, Oberman LM, White T, van der Velpen IF. Heterogeneity and convergence across seven neuroimaging modalities: a review of the autism spectrum disorder literature. Front Psychiatry 2024; 15:1474003. [PMID: 39479591 PMCID: PMC11521827 DOI: 10.3389/fpsyt.2024.1474003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2024] [Accepted: 09/30/2024] [Indexed: 11/02/2024] Open
Abstract
Background A growing body of literature classifies autism spectrum disorder (ASD) as a heterogeneous, complex neurodevelopmental disorder that often is identified prior to three years of age. We aim to provide a narrative review of key structural and functional properties that differentiate the neuroimaging profile of autistic youth from their typically developing (TD) peers across different neuroimaging modalities. Methods Relevant studies were identified by searching for key terms in PubMed, with the most recent search conducted on September 1, 2023. Original research papers were included if they applied at least one of seven neuroimaging modalities (structural MRI, functional MRI, DTI, MRS, fNIRS, MEG, EEG) to compare autistic children or those with a family history of ASD to TD youth or those without ASD family history; included only participants <18 years; and were published from 2013 to 2023. Results In total, 172 papers were considered for qualitative synthesis. When comparing ASD to TD groups, structural MRI-based papers (n = 26) indicated larger subcortical gray matter volume in ASD groups. DTI-based papers (n = 14) reported higher mean and radial diffusivity in ASD participants. Functional MRI-based papers (n = 41) reported a substantial number of between-network functional connectivity findings in both directions. MRS-based papers (n = 19) demonstrated higher metabolite markers of excitatory neurotransmission and lower inhibitory markers in ASD groups. fNIRS-based papers (n = 20) reported lower oxygenated hemoglobin signals in ASD. Converging findings in MEG- (n = 20) and EEG-based (n = 32) papers indicated lower event-related potential and field amplitudes in ASD groups. Findings in the anterior cingulate cortex, insula, prefrontal cortex, amygdala, thalamus, cerebellum, corpus callosum, and default mode network appeared numerous times across modalities and provided opportunities for multimodal qualitative analysis. Conclusions Comparing across neuroimaging modalities, we found significant differences between the ASD and TD neuroimaging profile in addition to substantial heterogeneity. Inconsistent results are frequently seen within imaging modalities, comparable study populations and research designs. Still, converging patterns across imaging modalities support various existing theories on ASD.
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Affiliation(s)
- Amanda R. Halliday
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Samuel N. Vucic
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Brianna Georges
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Madison LaRoche
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - María Alejandra Mendoza Pardo
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Liam O. Swiggard
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Kaylee McDonald
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Michelle Olofsson
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
- Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden
| | - Sahit N. Menon
- Noninvasive Neuromodulation Unit, Experimental Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
- School of Medicine, University of California, San Diego, San Diego, CA, United States
| | - Sunday M. Francis
- Noninvasive Neuromodulation Unit, Experimental Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Lindsay M. Oberman
- Noninvasive Neuromodulation Unit, Experimental Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Tonya White
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Isabelle F. van der Velpen
- Section on Social and Cognitive Developmental Neuroscience, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
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16
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Vaisvaser S. Meeting the multidimensional self: fostering selfhood at the interface of Creative Arts Therapies and neuroscience. Front Psychol 2024; 15:1417035. [PMID: 39386142 PMCID: PMC11461312 DOI: 10.3389/fpsyg.2024.1417035] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Accepted: 09/09/2024] [Indexed: 10/12/2024] Open
Abstract
Intriguing explorations at the intersection of the fields of neuroscience and psychology are driven by the quest to understand the neural underpinnings of "the self" and their psychotherapeutic implications. These translational efforts pertain to the unique Creative Arts Therapies (CATs) and the attributes and value of the self-related processes they offer. The self is considered as a multi-layered complex construct, comprising bodily and mental constituents, subjective-objective perspectives, spatial and temporal dimensions. Neuroscience research, mostly functional brain imaging, has proposed cogent models of the constitution, development and experience of the self, elucidating how the multiple dimensions of the self are supported by integrated hierarchical brain processes. The psychotherapeutic use of the art-forms, generating aesthetic experiences and creative processes, touch upon and connect the various layers of self-experience, nurturing the sense of self. The present conceptual analysis will describe and interweave the neural mechanisms and neural network configuration suggested to lie at the core of the ongoing self-experience, its deviations in psychopathology, and implications regarding the psychotherapeutic use of the arts. The well-established, parsimonious and neurobiologically plausible predictive processing account of brain-function will be discussed with regard to selfhood and consciousness. The epistemic affordance of the experiential CATs will further be portrayed, enabling and facilitating the creation of updated self-models of the body in the world. The neuropsychological impact of the relational therapeutic encounter will be delineated, acknowledging the intersubjective brain synchronization through communicative verbal and non-verbal means and aesthetic experiences. The recognition and assimilation of neuroscientific, phenomenological and clinical perspectives concerning the nested dimensionality of the self, ground the relational therapeutic process and the neuroplastic modulations that CATs have to offer on the premise of fostering, shaping and integrating selfhood.
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Affiliation(s)
- Sharon Vaisvaser
- School of Society and the Arts, Ono Academic College, Kiryat Ono, Israel
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17
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Taddei M, Cuesta P, Annunziata S, Bulgheroni S, Esposito S, Visani E, Granvillano A, Dotta S, Rossi DS, Panzica F, Franceschetti S, Varotto G, Riva D. Correlation between autistic traits and brain functional connectivity in preschoolers with autism spectrum disorder: a resting state MEG study. Neurol Sci 2024; 45:4549-4561. [PMID: 38639894 DOI: 10.1007/s10072-024-07528-2] [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: 12/07/2023] [Accepted: 04/09/2024] [Indexed: 04/20/2024]
Abstract
BACKGROUND Neurophysiological studies recognized that Autism Spectrum Disorder (ASD) is associated with altered patterns of over- and under-connectivity. However, little is known about network organization in children with ASD in the early phases of development and its correlation with the severity of core autistic features. METHODS The present study aimed at investigating the association between brain connectivity derived from MEG signals and severity of ASD traits measured with different diagnostic clinical scales, in a sample of 16 children with ASD aged 2 to 6 years. RESULTS A significant correlation emerged between connectivity strength in cortical brain areas implicated in several resting state networks (Default mode, Central executive, Salience, Visual and Sensorimotor) and the severity of communication anomalies, social interaction problems, social affect problems, and repetitive behaviors. Seed analysis revealed that this pattern of correlation was mainly caused by global rather than local effects. CONCLUSIONS The present evidence suggests that altered connectivity strength in several resting state networks is related to clinical features and may contribute to neurofunctional correlates of ASD. Future studies implementing the same method on a wider and stratified sample may further support functional connectivity as a possible biomarker of the condition.
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Affiliation(s)
- Matilde Taddei
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Pablo Cuesta
- Department of Radiology, Rehabilitation, and Physiotherapy, Center for Cognitive and Computational Neuroscience, Complutense University of Madrid, Madrid, Spain
| | - Silvia Annunziata
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
- Fondazione Don Carlo Gnocchi Onlus-IRCCS S. Maria Nascente, Via Capecelatro 66, 20148, Milan, Italy
| | - Sara Bulgheroni
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Silvia Esposito
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Elisa Visani
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Alice Granvillano
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Sara Dotta
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Davide Sebastiano Rossi
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Ferruccio Panzica
- Clinical Engineering Service, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
| | - Silvana Franceschetti
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
| | - Giulia Varotto
- Neurophysiopathology Unit, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy.
- Epilepsy Unit, Bioengineering Group, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy.
- Laboratory for Clinical Neuroscience, Center for Biomedical Technology, University Politécnica de Madrid, Madrid, Spain.
| | - Daria Riva
- Unit for Neurogenetic Syndromes With Intellectual Disabilities and Autism Spectrum Disorders, Fondazione IRCCS Istituto Neurologico Carlo Besta, Via Celoria 11, 20133, Milan, Italy
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Hill AT, Ford TC, Bailey NW, Lum JAG, Bigelow FJ, Oberman LM, Enticott PG. EEG During Dynamic Facial Emotion Processing Reveals Neural Activity Patterns Associated with Autistic Traits in Children. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.27.609816. [PMID: 39372765 PMCID: PMC11451616 DOI: 10.1101/2024.08.27.609816] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 10/08/2024]
Abstract
Altered brain connectivity and atypical neural oscillations have been observed in autism, yet their relationship with autistic traits in non-clinical populations remains underexplored. Here, we employ electroencephalography (EEG) to examine functional connectivity, oscillatory power, and broadband aperiodic activity during a dynamic facial emotion processing (FEP) task in 101 typically developing children aged 4-12 years. We investigate associations between these electrophysiological measures of brain dynamics and autistic traits as assessed by the Social Responsiveness Scale, 2nd Edition (SRS-2). Our results revealed that increased FEP-related connectivity across theta (4-7 Hz) and beta (13-30 Hz) frequencies correlated positively with higher SRS-2 scores, predominantly in right-lateralized (theta) and bilateral (beta) cortical networks. Additionally, a steeper 1/f-like aperiodic slope (spectral exponent) across fronto-central electrodes was associated with higher SRS-2 scores. Greater aperiodic-adjusted theta and alpha oscillatory power further correlated with both higher SRS-2 scores and steeper aperiodic slopes. These findings underscore important links between FEP-related brain dynamics and autistic traits in typically developing children. Future work could extend these findings to assess these EEG-derived markers as potential mechanisms underlying behavioural difficulties in autism.
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Affiliation(s)
- Aron T. Hill
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, Australia
| | - Talitha C. Ford
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, Australia
- Centre for Human Psychopharmacology & Swinburne Neuroimaging, School of Health Sciences, Swinburne University of Technology, Melbourne, Australia
| | - Neil W. Bailey
- School of Medicine and Psychology, The Australian National University, Canberra, ACT, Australia
- Monarch Research Institute Monarch Mental Health Group, Sydney, New South Wales, Australia
| | - Jarrad A. G. Lum
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, Australia
| | - Felicity J. Bigelow
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, Australia
| | - Lindsay M. Oberman
- Noninvasive Neuromodulation Unit, Experimental Therapeutics and Pathophysiology Branch, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, United States
| | - Peter G. Enticott
- Cognitive Neuroscience Unit, School of Psychology, Deakin University, Burwood, Australia
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Kong Y, Roser M, Bègue I, Elandaloussi Y, Neu N, Grigis A, Duchesnay E, Leboyer M, Houenou J, Laidi C. Cerebellum and social abilities: A structural and functional connectivity study in a transdiagnostic sample. Hum Brain Mapp 2024; 45:e26749. [PMID: 38989605 PMCID: PMC11237877 DOI: 10.1002/hbm.26749] [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: 10/12/2023] [Revised: 05/13/2024] [Accepted: 05/21/2024] [Indexed: 07/12/2024] Open
Abstract
The cerebellum has been involved in social abilities and autism. Given that the cerebellum is connected to the cortex via the cerebello-thalamo-cortical loop, the connectivity between the cerebellum and cortical regions involved in social interactions, that is, the right temporo-parietal junction (rTPJ) has been studied in individuals with autism, who suffer from prototypical deficits in social abilities. However, existing studies with small samples of categorical, case-control comparisons have yielded inconsistent results due to the inherent heterogeneity of autism, suggesting that investigating how clinical dimensions are related to cerebellar-rTPJ functional connectivity might be more relevant. Therefore, our objective was to study the functional connectivity between the cerebellum and rTPJ, focusing on its association with social abilities from a dimensional perspective in a transdiagnostic sample. We analyzed structural magnetic resonance imaging (MRI) and functional MRI (fMRI) scans obtained during naturalistic films watching from a large transdiagnostic dataset, the Healthy Brain Network (HBN), and examined the association between cerebellum-rTPJ functional connectivity and social abilities measured with the social responsiveness scale (SRS). We conducted univariate seed-to-voxel analysis, multivariate canonical correlation analysis (CCA), and predictive support vector regression (SVR). We included 1404 subjects in the structural analysis (age: 10.516 ± 3.034, range: 5.822-21.820, 506 females) and 414 subjects in the functional analysis (age: 11.260 ± 3.318 years, range: 6.020-21.820, 161 females). Our CCA model revealed a significant association between cerebellum-rTPJ functional connectivity, full-scale IQ (FSIQ) and SRS scores. However, this effect was primarily driven by FSIQ as suggested by SVR and univariate seed-to-voxel analysis. We also demonstrated the specificity of the rTPJ and the influence of structural anatomy in this association. Our results suggest that there is a complex relationship between cerebellum-rTPJ connectivity, social performance and IQ. This relationship is specific to the cerebellum-rTPJ connectivity, and is largely related to structural anatomy in these two regions. PRACTITIONER POINTS: We analyzed cerebellum-right temporoparietal junction (rTPJ) connectivity in a pediatric transdiagnostic sample. We found a complex relationship between cerebellum and rTPJ connectivity, social performance and IQ. Cerebellum and rTPJ functional connectivity is related to structural anatomy in these two regions.
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Affiliation(s)
- Yue Kong
- INSERM U955, Institut Mondor de la Recherche Biomédicale (IMRB), Univ. Paris East Créteil, Team 15 Translational Neuropsychiatry, DMU IMPACT, Henri Mondor - AP-HP Paris University Hospitals, Créteil, France
- NeuroSpin, CEA, Paris-Saclay University, France, Saclay, France
| | - Mathilde Roser
- INSERM U955, Institut Mondor de la Recherche Biomédicale (IMRB), Univ. Paris East Créteil, Team 15 Translational Neuropsychiatry, DMU IMPACT, Henri Mondor - AP-HP Paris University Hospitals, Créteil, France
- NeuroSpin, CEA, Paris-Saclay University, France, Saclay, France
- Fondation Fondamental, Créteil, France
| | - Indrit Bègue
- Department of Psychiatry, Beth Israel Deaconess Medical School and Harvard Medical School, Boston, Massachusetts, USA
- Department of Psychiatry, McLean Hospital and Harvard Medical School, Boston, Massachusetts, USA
- Neuroimaging and Translational Psychiatry lab, Synapsy Center for Neuroscience and Mental Health Research, Department of Psychiatry, University of Geneva, Geneva, Switzerland
| | - Yannis Elandaloussi
- INSERM U955, Institut Mondor de la Recherche Biomédicale (IMRB), Univ. Paris East Créteil, Team 15 Translational Neuropsychiatry, DMU IMPACT, Henri Mondor - AP-HP Paris University Hospitals, Créteil, France
- NeuroSpin, CEA, Paris-Saclay University, France, Saclay, France
| | - Nathan Neu
- INSERM U955, Institut Mondor de la Recherche Biomédicale (IMRB), Univ. Paris East Créteil, Team 15 Translational Neuropsychiatry, DMU IMPACT, Henri Mondor - AP-HP Paris University Hospitals, Créteil, France
- NeuroSpin, CEA, Paris-Saclay University, France, Saclay, France
| | - Antoine Grigis
- NeuroSpin, CEA, Paris-Saclay University, France, Saclay, France
| | | | - Marion Leboyer
- INSERM U955, Institut Mondor de la Recherche Biomédicale (IMRB), Univ. Paris East Créteil, Team 15 Translational Neuropsychiatry, DMU IMPACT, Henri Mondor - AP-HP Paris University Hospitals, Créteil, France
- Fondation Fondamental, Créteil, France
| | - Josselin Houenou
- INSERM U955, Institut Mondor de la Recherche Biomédicale (IMRB), Univ. Paris East Créteil, Team 15 Translational Neuropsychiatry, DMU IMPACT, Henri Mondor - AP-HP Paris University Hospitals, Créteil, France
- NeuroSpin, CEA, Paris-Saclay University, France, Saclay, France
- Fondation Fondamental, Créteil, France
| | - Charles Laidi
- INSERM U955, Institut Mondor de la Recherche Biomédicale (IMRB), Univ. Paris East Créteil, Team 15 Translational Neuropsychiatry, DMU IMPACT, Henri Mondor - AP-HP Paris University Hospitals, Créteil, France
- NeuroSpin, CEA, Paris-Saclay University, France, Saclay, France
- Fondation Fondamental, Créteil, France
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Rippon G. Differently different?: A commentary on the emerging social cognitive neuroscience of female autism. Biol Sex Differ 2024; 15:49. [PMID: 38872228 PMCID: PMC11177439 DOI: 10.1186/s13293-024-00621-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 05/23/2024] [Indexed: 06/15/2024] Open
Abstract
Autism is a neurodevelopmental condition, behaviourally identified, which is generally characterised by social communication differences, and restrictive and repetitive patterns of behaviour and interests. It has long been claimed that it is more common in males. This observed preponderance of males in autistic populations has served as a focussing framework in all spheres of autism-related issues, from recognition and diagnosis through to theoretical models and research agendas. One related issue is the near total absence of females in key research areas. For example, this paper reports a review of over 120 brain-imaging studies of social brain processes in autism that reveals that nearly 70% only included male participants or minimal numbers (just one or two) of females. Authors of such studies very rarely report that their cohorts are virtually female-free and discuss their findings as though applicable to all autistic individuals. The absence of females can be linked to exclusionary consequences of autism diagnostic procedures, which have mainly been developed on male-only cohorts. There is clear evidence that disproportionately large numbers of females do not meet diagnostic criteria and are then excluded from ongoing autism research. Another issue is a long-standing assumption that the female autism phenotype is broadly equivalent to that of the male autism phenotype. Thus, models derived from male-based studies could be applicable to females. However, it is now emerging that certain patterns of social behaviour may be very different in females. This includes a specific type of social behaviour called camouflaging or masking, linked to attempts to disguise autistic characteristics. With respect to research in the field of sex/gender cognitive neuroscience, there is emerging evidence of female differences in patterns of connectivity and/or activation in the social brain that are at odds with those reported in previous, male-only studies. Decades of research have excluded or overlooked females on the autistic spectrum, resulting in the construction of inaccurate and misleading cognitive neuroscience models, and missed opportunities to explore the brain bases of this highly complex condition. A note of warning needs to be sounded about inferences drawn from past research, but if future research addresses this problem of male bias, then a deeper understanding of autism as a whole, as well as in previously overlooked females, will start to emerge.
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Affiliation(s)
- Gina Rippon
- Emeritus of Cognitive NeuroImaging, Institute of Health and Neurodevelopment, College of Health and Life Sciences, Aston University, Birmingham, B4 7ET, UK.
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21
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Vieira S, Bolton TAW, Schöttner M, Baecker L, Marquand A, Mechelli A, Hagmann P. Multivariate brain-behaviour associations in psychiatric disorders. Transl Psychiatry 2024; 14:231. [PMID: 38824172 PMCID: PMC11144193 DOI: 10.1038/s41398-024-02954-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 05/15/2024] [Accepted: 05/21/2024] [Indexed: 06/03/2024] Open
Abstract
Mapping brain-behaviour associations is paramount to understand and treat psychiatric disorders. Standard approaches involve investigating the association between one brain and one behavioural variable (univariate) or multiple variables against one brain/behaviour feature ('single' multivariate). Recently, large multimodal datasets have propelled a new wave of studies that leverage on 'doubly' multivariate approaches capable of parsing the multifaceted nature of both brain and behaviour simultaneously. Within this movement, canonical correlation analysis (CCA) and partial least squares (PLS) emerge as the most popular techniques. Both seek to capture shared information between brain and behaviour in the form of latent variables. We provide an overview of these methods, review the literature in psychiatric disorders, and discuss the main challenges from a predictive modelling perspective. We identified 39 studies across four diagnostic groups: attention deficit and hyperactive disorder (ADHD, k = 4, N = 569), autism spectrum disorders (ASD, k = 6, N = 1731), major depressive disorder (MDD, k = 5, N = 938), psychosis spectrum disorders (PSD, k = 13, N = 1150) and one transdiagnostic group (TD, k = 11, N = 5731). Most studies (67%) used CCA and focused on the association between either brain morphology, resting-state functional connectivity or fractional anisotropy against symptoms and/or cognition. There were three main findings. First, most diagnoses shared a link between clinical/cognitive symptoms and two brain measures, namely frontal morphology/brain activity and white matter association fibres (tracts between cortical areas in the same hemisphere). Second, typically less investigated behavioural variables in multivariate models such as physical health (e.g., BMI, drug use) and clinical history (e.g., childhood trauma) were identified as important features. Finally, most studies were at risk of bias due to low sample size/feature ratio and/or in-sample testing only. We highlight the importance of carefully mitigating these sources of bias with an exemplar application of CCA.
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Affiliation(s)
- S Vieira
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
- Center for Research in Neuropsychology and Cognitive Behavioral Intervention, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal.
| | - T A W Bolton
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Neurosurgery Service and Gamma Knife Center, Lausanne University Hospital, Lausanne, Switzerland
| | - M Schöttner
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - L Baecker
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - A Marquand
- Donders Institute for Brain, Cognition and Behavior, Radboud University Nijmegen, Nijmegen, The Netherlands
- Department for Cognitive Neuroscience, Radboud University Medical Center Nijmegen, Nijmegen, The Netherlands
- Department of Neuroimaging, Institute of Psychiatry, Psychology, & Neuroscience, King's College London, London, UK
| | - A Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - P Hagmann
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
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Wang L, Qin Y, Yang S, Jin D, Zhu Y, Li X, Li W, Wang Y, Jin C. Posterior default mode network is associated with the social performance in male children with autism spectrum disorder: A dynamic causal modeling analysis based on triple-network model. Hum Brain Mapp 2024; 45:e26750. [PMID: 38853710 PMCID: PMC11163228 DOI: 10.1002/hbm.26750] [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: 01/10/2024] [Revised: 05/12/2024] [Accepted: 05/22/2024] [Indexed: 06/11/2024] Open
Abstract
The triple-network model has been widely applied in neuropsychiatric disorders including autism spectrum disorder (ASD). However, the mechanism of causal regulations within the triple-network and their relations with symptoms of ASD remains unclear. 81 male ASD and 80 well matched typically developing control (TDC) were included in this study, recruited from Autism Brain Image Data Exchange-I datasets. Spatial reference-based independent component analysis was used to identify the anterior and posterior part of default-mode network (aDMN and pDMN), salience network (SN), and bilateral executive-control network (ECN) from resting-state functional magnetic resonance imaging data. Spectral dynamic causal model and parametric empirical Bayes with Bayesian model reduction/average were adopted to explore the effective connectivity (EC) within triple-network and the relationship between EC and autism diagnostic observation schedule (ADOS) scores. After adjusting for age and site effect, ASD and TDC groups both showed inhibition patterns. Compared with TDC, ASD group showed weaker self-inhibition in aDMN and pDMN, stronger inhibition in pDMN→aDMN, weaker inhibition in aDMN→LECN, pDMN→SN, LECN→SN, and LECN→RECN. Furthermore, negative relationships between ADOS scores and pDMN self-inhibition strength, as well as with the EC of pDMN→aDMN were observed in ASD group. The present study reveals imbalanced effective connections within triple-networks in ASD children. More attentions should be focused at the pDMN, which modulates the core symptoms of ASD and may serve as an important region for ASD diagnosis and the target region for ASD treatments.
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Affiliation(s)
- Lei Wang
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Yue Qin
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Shuhan Yang
- Department of Disease Control and PreventionNinth Hospital of Xi'anXi'anChina
| | - Dayong Jin
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Yinhu Zhu
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Xin Li
- Department of RadiologyXi'an Daxing HospitalXi'anChina
| | - Wei Li
- Department of Radiology, Tangdu HospitalAir Force Military Medical UniversityXi'anChina
| | - Yarong Wang
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
| | - Chenwang Jin
- Department of RadiologyThe First Affiliated Hospital of Xi'an Jiaotong UniversityXi'anChina
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23
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Barreto C, Curtin A, Topoglu Y, Day-Watkins J, Garvin B, Foster G, Ormanoglu Z, Sheridan E, Connell J, Bennett D, Heffler K, Ayaz H. Prefrontal Cortex Responses to Social Video Stimuli in Young Children with and without Autism Spectrum Disorder. Brain Sci 2024; 14:503. [PMID: 38790481 PMCID: PMC11119834 DOI: 10.3390/brainsci14050503] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2024] [Revised: 05/09/2024] [Accepted: 05/11/2024] [Indexed: 05/26/2024] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder affecting individuals worldwide and characterized by deficits in social interaction along with the presence of restricted interest and repetitive behaviors. Despite decades of behavioral research, little is known about the brain mechanisms that influence social behaviors among children with ASD. This, in part, is due to limitations of traditional imaging techniques specifically targeting pediatric populations. As a portable and scalable optical brain monitoring technology, functional near infrared spectroscopy (fNIRS) provides a measure of cerebral hemodynamics related to sensory, motor, or cognitive function. Here, we utilized fNIRS to investigate the prefrontal cortex (PFC) activity of young children with ASD and with typical development while they watched social and nonsocial video clips. The PFC activity of ASD children was significantly higher for social stimuli at medial PFC, which is implicated in social cognition/processing. Moreover, this activity was also consistently correlated with clinical measures, and higher activation of the same brain area only during social video viewing was associated with more ASD symptoms. This is the first study to implement a neuroergonomics approach to investigate cognitive load in response to realistic, complex, and dynamic audiovisual social stimuli for young children with and without autism. Our results further confirm that new generation of portable fNIRS neuroimaging can be used for ecologically valid measurements of the brain function of toddlers and preschool children with ASD.
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Affiliation(s)
- Candida Barreto
- School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA 19104, USA
| | - Adrian Curtin
- School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA 19104, USA
| | - Yigit Topoglu
- School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA 19104, USA
| | | | - Brigid Garvin
- St. Christopher’s Hospital for Children, Philadelphia, PA 19134, USA
| | - Grant Foster
- School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA 19104, USA
| | - Zuhal Ormanoglu
- School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA 19104, USA
| | | | - James Connell
- School of Education, Drexel University, Philadelphia, PA 19104, USA
| | - David Bennett
- Department of Psychiatry, College of Medicine, Drexel University, Philadelphia, PA 19129, USA
| | - Karen Heffler
- Department of Psychiatry, College of Medicine, Drexel University, Philadelphia, PA 19129, USA
| | - Hasan Ayaz
- School of Biomedical Engineering, Science, and Health Systems, Drexel University, Philadelphia, PA 19104, USA
- A.J. Drexel Autism Institute, Philadelphia, PA 19104, USA
- Department of Psychological and Brain Sciences, College of Arts and Sciences, Drexel University, Philadelphia, PA 19104, USA
- Drexel Solutions Institute, Drexel University, Philadelphia, PA 19104, USA
- Center for Injury Research and Prevention, Children’s Hospital of Philadelphia, Philadelphia, PA 19104, USA
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24
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Wilkes BJ, Archer DB, Farmer AL, Bass C, Korah H, Vaillancourt DE, Lewis MH. Cortico-basal ganglia white matter microstructure is linked to restricted repetitive behavior in autism spectrum disorder. Mol Autism 2024; 15:6. [PMID: 38254158 PMCID: PMC10804694 DOI: 10.1186/s13229-023-00581-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2023] [Accepted: 12/23/2023] [Indexed: 01/24/2024] Open
Abstract
BACKGROUND Restricted repetitive behavior (RRB) is one of two behavioral domains required for the diagnosis of autism spectrum disorder (ASD). Neuroimaging is widely used to study brain alterations associated with ASD and the domain of social and communication deficits, but there has been less work regarding brain alterations linked to RRB. METHODS We utilized neuroimaging data from the National Institute of Mental Health Data Archive to assess basal ganglia and cerebellum structure in a cohort of children and adolescents with ASD compared to typically developing (TD) controls. We evaluated regional gray matter volumes from T1-weighted anatomical scans and assessed diffusion-weighted scans to quantify white matter microstructure with free-water imaging. We also investigated the interaction of biological sex and ASD diagnosis on these measures, and their correlation with clinical scales of RRB. RESULTS Individuals with ASD had significantly lower free-water corrected fractional anisotropy (FAT) and higher free-water (FW) in cortico-basal ganglia white matter tracts. These microstructural differences did not interact with biological sex. Moreover, both FAT and FW in basal ganglia white matter tracts significantly correlated with measures of RRB. In contrast, we found no significant difference in basal ganglia or cerebellar gray matter volumes. LIMITATIONS The basal ganglia and cerebellar regions in this study were selected due to their hypothesized relevance to RRB. Differences between ASD and TD individuals that may occur outside the basal ganglia and cerebellum, and their potential relationship to RRB, were not evaluated. CONCLUSIONS These new findings demonstrate that cortico-basal ganglia white matter microstructure is altered in ASD and linked to RRB. FW in cortico-basal ganglia and intra-basal ganglia white matter was more sensitive to group differences in ASD, whereas cortico-basal ganglia FAT was more closely linked to RRB. In contrast, basal ganglia and cerebellar volumes did not differ in ASD. There was no interaction between ASD diagnosis and sex-related differences in brain structure. Future diffusion imaging investigations in ASD may benefit from free-water estimation and correction in order to better understand how white matter is affected in ASD, and how such measures are linked to RRB.
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Affiliation(s)
- Bradley J Wilkes
- Department of Applied Physiology and Kinesiology, University of Florida, P.O. Box 118205, Gainesville, FL, 32611, USA.
| | - Derek B Archer
- Vanderbilt Memory and Alzheimer's Center, Department of Neurology, Vanderbilt School of Medicine, Nashville, TN, USA
- Department of Neurology, Vanderbilt Genetics Institute, Vanderbilt School of Medicine, Nashville, TN, USA
| | - Anna L Farmer
- Department of Psychology, University of Florida, Gainesville, FL, USA
| | - Carly Bass
- Department of Psychiatry, University of Florida, Gainesville, FL, USA
| | - Hannah Korah
- Department of Pharmacology, College of Medicine, University of Arizona, Tucson, AZ, USA
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, University of Florida, P.O. Box 118205, Gainesville, FL, 32611, USA
- Department of Biomedical Engineering, University of Florida, Gainesville, FL, USA
- Department of Neurology, Fixel Center for Neurological Diseases, Program in Movement Disorders and Neurorestoration, University of Florida, Gainesville, FL, USA
| | - Mark H Lewis
- Department of Psychology, University of Florida, Gainesville, FL, USA
- Department of Psychiatry, University of Florida, Gainesville, FL, USA
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25
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Wang M, Xu D, Zhang L, Jiang H. Application of Multimodal MRI in the Early Diagnosis of Autism Spectrum Disorders: A Review. Diagnostics (Basel) 2023; 13:3027. [PMID: 37835770 PMCID: PMC10571992 DOI: 10.3390/diagnostics13193027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2023] [Revised: 09/13/2023] [Accepted: 09/20/2023] [Indexed: 10/15/2023] Open
Abstract
Autism spectrum disorder (ASD) is a neurodevelopmental disorder in children. Early diagnosis and intervention can remodel the neural structure of the brain and improve quality of life but may be inaccurate if based solely on clinical symptoms and assessment scales. Therefore, we aimed to analyze multimodal magnetic resonance imaging (MRI) data from the existing literature and review the abnormal changes in brain structural-functional networks, perfusion, neuronal metabolism, and the glymphatic system in children with ASD, which could help in early diagnosis and precise intervention. Structural MRI revealed morphological differences, abnormal developmental trajectories, and network connectivity changes in the brain at different ages. Functional MRI revealed disruption of functional networks, abnormal perfusion, and neurovascular decoupling associated with core ASD symptoms. Proton magnetic resonance spectroscopy revealed abnormal changes in the neuronal metabolites during different periods. Decreased diffusion tensor imaging signals along the perivascular space index reflected impaired glymphatic system function in children with ASD. Differences in age, subtype, degree of brain damage, and remodeling in children with ASD led to heterogeneity in research results. Multimodal MRI is expected to further assist in early and accurate clinical diagnosis of ASD through deep learning combined with genomics and artificial intelligence.
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Affiliation(s)
- Miaoyan Wang
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
| | - Dandan Xu
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
| | - Lili Zhang
- Department of Child Health Care, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China
| | - Haoxiang Jiang
- Department of Radiology, Affiliated Children’s Hospital of Jiangnan University, Wuxi 214000, China; (M.W.); (D.X.)
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26
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Gießing C. Identifying Reproducible Biomarkers of Autism Based on Functional Brain Connectivity. Biol Psychiatry 2023; 94:2-3. [PMID: 37316103 DOI: 10.1016/j.biopsych.2023.04.021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 04/25/2023] [Indexed: 06/16/2023]
Affiliation(s)
- Carsten Gießing
- Biological Psychology Lab, Department of Psychology, School of Medicine and Health Sciences, Research Center Neurosensory Science and Systems, Carl von Ossietzky University Oldenburg, Oldenburg, Germany.
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27
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Xie H, Moraczewski D, McNaughton KA, Warnell KR, Alkire D, Merchant JS, Kirby LA, Yarger HA, Redcay E. Social reward network connectivity differs between autistic and neurotypical youth during social interaction. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.05.543807. [PMID: 37333161 PMCID: PMC10274709 DOI: 10.1101/2023.06.05.543807] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
A core feature of autism is difficulties with social interaction. Atypical social motivation is proposed to underlie these difficulties. However, prior work testing this hypothesis has shown mixed support and has been limited in its ability to understand real-world social-interactive processes in autism. We attempted to address these limitations by scanning neurotypical and autistic youth (n = 86) during a text-based reciprocal social interaction that mimics a "live" chat and elicits social reward processes. We focused on task-evoked functional connectivity (FC) of regions responsible for motivational-reward and mentalizing processes within the broader social reward circuitry. We found that task-evoked FC between these regions was significantly modulated by social interaction and receipt of social-interactive reward. Compared to neurotypical peers, autistic youth showed significantly greater task-evoked connectivity of core regions in the mentalizing network (e.g., posterior superior temporal sulcus) and the amygdala, a key node in the reward network. Furthermore, across groups, the connectivity strength between these mentalizing and reward regions was negatively correlated with self-reported social motivation and social reward during the scanner task. Our results highlight an important role of FC within the broader social reward circuitry for social-interactive reward. Specifically, greater context-dependent FC (i.e., differences between social engagement and non-social engagement) may indicate an increased "neural effort" during social reward and relate to differences in social motivation within autistic and neurotypical populations.
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Affiliation(s)
- Hua Xie
- Neuroscience and Cognitive Science Program, University of Maryland, College Park, Maryland, USA
- Department of Psychology, University of Maryland, College Park, Maryland, USA
- Center for Neuroscience Research, Children’s National Hospital, Washington, D.C., USA
- The George Washington University School of Medicine, Washington, D.C., USA
| | - Dustin Moraczewski
- Data Science and Sharing Team, National Institute of Mental Health, Bethesda, Maryland, USA
| | - Kathryn A. McNaughton
- Neuroscience and Cognitive Science Program, University of Maryland, College Park, Maryland, USA
- Department of Psychology, University of Maryland, College Park, Maryland, USA
| | | | - Diana Alkire
- Neuroscience and Cognitive Science Program, University of Maryland, College Park, Maryland, USA
- Department of Psychology, University of Maryland, College Park, Maryland, USA
| | - Junaid S. Merchant
- Neuroscience and Cognitive Science Program, University of Maryland, College Park, Maryland, USA
- Department of Psychology, University of Maryland, College Park, Maryland, USA
| | - Laura A. Kirby
- Department of Psychology, University of Maryland, College Park, Maryland, USA
| | - Heather A. Yarger
- Neuroscience and Cognitive Science Program, University of Maryland, College Park, Maryland, USA
- Department of Psychology, University of Maryland, College Park, Maryland, USA
| | - Elizabeth Redcay
- Neuroscience and Cognitive Science Program, University of Maryland, College Park, Maryland, USA
- Department of Psychology, University of Maryland, College Park, Maryland, USA
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28
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Itahashi T, Yamashita A, Takahara Y, Yahata N, Aoki YY, Fujino J, Yoshihara Y, Nakamura M, Aoki R, Ohta H, Sakai Y, Takamura M, Ichikawa N, Okada G, Okada N, Kasai K, Tanaka SC, Imamizu H, Kato N, Okamoto Y, Takahashi H, Kawato M, Yamashita O, Hashimoto RI. Generalizable neuromarker for autism spectrum disorder across imaging sites and developmental stages: A multi-site study. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.26.534053. [PMID: 37034620 PMCID: PMC10081283 DOI: 10.1101/2023.03.26.534053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/19/2023]
Abstract
Autism spectrum disorder (ASD) is a lifelong condition, and its underlying biological mechanisms remain elusive. The complexity of various factors, including inter-site and development-related differences, makes it challenging to develop generalizable neuroimaging-based biomarkers for ASD. This study used a large-scale, multi-site dataset of 730 Japanese adults to develop a generalizable neuromarker for ASD across independent sites (U.S., Belgium, and Japan) and different developmental stages (children and adolescents). Our adult ASD neuromarker achieved successful generalization for the US and Belgium adults (area under the curve [AUC] = 0.70) and Japanese adults (AUC = 0.81). The neuromarker demonstrated significant generalization for children (AUC = 0.66) and adolescents (AUC = 0.71; all P < 0.05 , family-wise-error corrected). We identified 141 functional connections (FCs) important for discriminating individuals with ASD from TDCs. These FCs largely centered on social brain regions such as the amygdala, hippocampus, dorsomedial and ventromedial prefrontal cortices, and temporal cortices. Finally, we mapped schizophrenia (SCZ) and major depressive disorder (MDD) onto the biological axis defined by the neuromarker and explored the biological continuity of ASD with SCZ and MDD. We observed that SCZ, but not MDD, was located proximate to ASD on the biological dimension defined by the ASD neuromarker. The successful generalization in multifarious datasets and the observed relations of ASD with SCZ on the biological dimensions provide new insights for a deeper understanding of ASD.
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Affiliation(s)
- Takashi Itahashi
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Ayumu Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Graduate School of Information Science and Technology, The University of Tokyo, Tokyo, Japan
| | - Yuji Takahara
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Laboratory for Drug Discovery and Disease Research, SHIONOGI & CO., LTD, Osaka, Japan
| | - Noriaki Yahata
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Institute for Quantum Life Science, National Institutes for Quantum Science and Technology, Chiba, Japan
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Yuta Y. Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Psychiatry, Aoki Clinic, Tokyo, Japan
| | - Junya Fujino
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yujiro Yoshihara
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Motoaki Nakamura
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Ryuta Aoki
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Language Sciences, Tokyo Metropolitan University, Tokyo, Japan
| | - Haruhisa Ohta
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Yuki Sakai
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
| | - Masahiro Takamura
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
- Department of Neurology, Shimane University, Shimane, Japan
| | - Naho Ichikawa
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Go Okada
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Naohiro Okada
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan
| | - Kiyoto Kasai
- Department of Neuropsychiatry, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
- The International Research Center for Neurointelligence (WPI-IRCN) at The University of Tokyo Institutes for Advanced Study (UTIAS), The University of Tokyo, Tokyo, Japan
- UTokyo Institute for Diversity and Adaptation of Human Mind (UTIDAHM), The University of Tokyo, Tokyo, Japan
| | - Saori C. Tanaka
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Division of Information Science, Nara Institute of Science and Technology, Nara, Japan
| | - Hiroshi Imamizu
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- Department of Psychology, Graduate School of Humanities and Sociology, The University of Tokyo, Tokyo, Japan
| | - Nobumasa Kato
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
| | - Yasumasa Okamoto
- Department of Psychiatry and Neurosciences, Hiroshima University, Hiroshima, Japan
| | - Hidehiko Takahashi
- Department of Psychiatry and Behavioral Sciences, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, Tokyo, Japan
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
- Center for Brain Integration Research, Tokyo Medical and Dental University, Tokyo, Japan
| | - Mitsuo Kawato
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- XNef Incorporation, Kyoto, Japan
| | - Okito Yamashita
- Brain Information Communication Research Laboratory Group, Advanced Telecommunications Research Institute International, Kyoto, Japan
- RIKEN, Center for Advanced Intelligence Project, Tokyo, Japan
| | - Ryu-ichiro Hashimoto
- Medical Institute of Developmental Disabilities Research, Showa University, Tokyo, Japan
- Department of Psychiatry, Graduate School of Medicine, Kyoto University, Kyoto, Japan
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