Stratifying ASD and characterizing the functional connectivity of subtypes in resting-state fMRI

Ren, Pengchen; Bi, Qingshang; Pang, Wenbin; Wang, Meijuan; Zhou, Qionglin; Ye, Xiaoshan; Li, Ling; Xiao, Le

doi:10.1016/j.bbr.2023.114458

Cited by 10 publications

(4 citation statements)

References 59 publications

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“…In recent years, patterns of rs-FC in fronto-limbic circuits are being explored as potential biomarkers of different psychiatric disorders (Parkes et al, 2020). With the advent of large cohort imaging studies, it has even been possible to identify different subtypes of depression (Chai et al, 2023), autism (Ren et al, 2023), anxiety (Li et al, 2023), and schizophrenia (Zhu et al, 2016) based on their differential patterns of rs-FC. One potential use for these biomarkers is to identify and then target neuromodulation therapies such as deep brain stimulation (DBS) to specific circuits to ameliorate symptoms (Holtzheimer and Mayberg, 2011).…”

Section: Conclusion and Relevance To Psychiatric Disordersmentioning

confidence: 99%

“…In particular, it has been used to track variation in frontal circuits in development (Grayson and Fair, 2017), aging (Rosenberg et al, 2020), as well as neurological and psychiatric disease (Greicius, 2008). Indeed, in psychiatric research, patterns of rs-FC in fronto-limbic circuits have become increasingly used as biomarkers of different subtypes of depression (Chai et al, 2023), autism (Ren et al, 2023), anxiety (Li et al, 2023), and schizophrenia (Zhu et al, 2016). The validation and use of these biomarkers hold the potential to enable personalized treatments for subtypes of psychiatric disorders (Yamada et al, 2017; Lee et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation

Elorette,

Fujimoto,

Stoll

et al. 2023

Preprint

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Measures of fMRI resting-state functional connectivity (rs-FC) are an essential tool for basic and clinical investigations of fronto-limbic circuits. Understanding the relationship between rs-FC and neural activity in these circuits is therefore vital. Here we introduced inhibitory designer receptors exclusively activated by designer drugs (DREADDs) into the macaque amygdala and activated them with a highly selective and potent DREADD agonist, deschloroclozapine. We evaluated the causal effect of activating the DREADD receptors on rs-FC and neural activity within circuits connecting amygdala and frontal cortex. Interestingly, activating the inhibitory DREADD increased rs-FC between amygdala and ventrolateral prefrontal cortex. Neurophysiological recordings revealed that the DREADD-induced increase in fMRI rs-FC was associated with increased local field potential coherency in the alpha band (6.5-14.5Hz) between amygdala and ventrolateral prefrontal cortex. Thus, our multi-disciplinary approach reveals the specific signature of neuronal activity that underlies rs-FC in fronto-limbic circuits.

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Section: Conclusion and Relevance To Psychiatric Disordersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation

Elorette,

Fujimoto,

Stoll

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…FC is usually a measurement of time processes between different brain regions based on Pearson's correlation. FC changes in the resting state of ASD subtypes may identify specific changes in neural network function in each subtype (Ren et al, 2023 ). However, the interactions among brain function, structure, and clinical traits in ASD remain unclear.…”

Section: Introductionmentioning

confidence: 99%

Brain functional gradient and structure features in adolescent and adult autism spectrum disorders

Ruan,

Chen,

Yao

et al. 2024

Human Brain Mapping

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Understanding how function and structure are organized and their coupling with clinical traits in individuals with autism spectrum disorder (ASD) is a primary goal in network neuroscience research for ASD. Atypical brain functional networks and structures in individuals with ASD have been reported, but whether these associations show heterogeneous hierarchy modeling in adolescents and adults with ASD remains to be clarified. In this study, 176 adolescent and 74 adult participants with ASD without medication or comorbidities and sex, age matched healthy controls (HCs) from 19 research groups from the openly shared Autism Brain Imaging Data Exchange II database were included. To investigate the relationship between the functional gradient, structural changes, and clinical symptoms of brain networks in adolescents and adults with ASD, functional gradient and voxel‐based morphometry (VBM) analyses based on 1000 parcels defined by Schaefer mapped to Yeo's seven‐network atlas were performed. Pearson's correlation was calculated between the gradient scores, gray volume and density, and clinical traits. The subsystem‐level analysis showed that the second gradient scores of the default mode networks and frontoparietal network in patients with ASD were relatively compressed compared to adolescent HCs. Adult patients with ASD showed an overall compression gradient of 1 in the ventral attention networks. In addition, the gray density and volumes of the subnetworks showed no significant differences between the ASD and HC groups at the adolescent stage. However, adults with ASD showed decreased gray density in the limbic network. Moreover, numerous functional gradient parameters, but not VBM parameters, in adolescents with ASD were considerably correlated with clinical traits in contrast to those in adults with ASD. Our findings proved that the atypical changes in adolescent ASD mainly involve the brain functional network, while in adult ASD, the changes are more related to brain structure, including gray density and volume. These changes in functional gradients or structures are markedly correlated with clinical traits in patients with ASD. Our study provides a novel understanding of the pathophysiology of the structure–function hierarchy in ASD.

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“…Future studies could further explore individual differences within the ASD group because individuals with ASD often exhibit significant variations in the quality and quantity of social-communication deficits, varying from minimal social behaviors to sufficient but atypical social interactions (Lord et al ., 2020 ). Previous studies using neuroimaging techniques have revealed various subtypes of ASD, underscoring the heterogeneous nature of this disorder (Chen et al ., 2019 ; Choi et al ., 2022 ; Guo et al ., 2023 ; Ren et al ., 2023 ; Shan et al ., 2022 ). Such individual differences could affect the comparison of ASD with TD controls or other neurodevelopmental disorders at the group level, hence, accounting for the individual factors may aid more accurately reveal the DTI features of ASD subtypes and further improve the precision of diagnosis of different subtypes of ASD.…”

mentioning

confidence: 99%

Early diagnosis of autism spectrum disorder using structural connectivity biomarker

Lau,

Leung,

Poon

et al. 2024

Psychoradiology

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Stratifying ASD and characterizing the functional connectivity of subtypes in resting-state fMRI

Cited by 10 publications

References 59 publications

The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation

The neural basis of resting-state fMRI functional connectivity in fronto-limbic circuits revealed by chemogenetic manipulation

Brain functional gradient and structure features in adolescent and adult autism spectrum disorders

Early diagnosis of autism spectrum disorder using structural connectivity biomarker

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