BROWSE

Related Scientist

cnir's photo.

cnir
뇌과학이미징연구단
more info

ITEM VIEW & DOWNLOAD

Structural connectome alterations between individuals with autism and neurotypical controls using feature representation learning

DC Field Value Language
dc.contributor.authorJang, Yurim-
dc.contributor.authorHyoungshin Choi-
dc.contributor.authorYoo, Seulki-
dc.contributor.authorHyunjin Park-
dc.contributor.authorBo-yong Park-
dc.date.accessioned2024-03-29T04:50:20Z-
dc.date.available2024-03-29T04:50:20Z-
dc.date.created2024-02-06-
dc.date.issued2024-01-
dc.identifier.issn1744-9081-
dc.identifier.urihttps://pr.ibs.re.kr/handle/8788114/14968-
dc.description.abstractAutism spectrum disorder is one of the most common neurodevelopmental conditions associated with sensory and social communication impairments. Previous neuroimaging studies reported that atypical nodal- or network-level functional brain organization in individuals with autism was associated with autistic behaviors. Although dimensionality reduction techniques have the potential to uncover new biomarkers, the analysis of whole-brain structural connectome abnormalities in a low-dimensional latent space is underinvestigated. In this study, we utilized autoencoder-based feature representation learning for diffusion magnetic resonance imaging-based structural connectivity in 80 individuals with autism and 61 neurotypical controls that passed strict quality controls. We generated low-dimensional latent features using the autoencoder model for each group and adopted an integrated gradient approach to assess the contribution of the input data for predicting latent features during the encoding process. Subsequently, we compared the integrated gradient values between individuals with autism and neurotypical controls and observed differences within the transmodal regions and between the sensory and limbic systems. Finally, we identified significant associations between integrated gradient values and communication abilities in individuals with autism. Our findings provide insights into the whole-brain structural connectome in autism and may help identify potential biomarkers for autistic connectopathy.-
dc.language영어-
dc.publisherBioMed Central-
dc.titleStructural connectome alterations between individuals with autism and neurotypical controls using feature representation learning-
dc.typeArticle-
dc.type.rimsART-
dc.identifier.wosid001148299600001-
dc.identifier.scopusid2-s2.0-85183007891-
dc.identifier.rimsid82510-
dc.contributor.affiliatedAuthorHyoungshin Choi-
dc.contributor.affiliatedAuthorHyunjin Park-
dc.contributor.affiliatedAuthorBo-yong Park-
dc.identifier.doi10.1186/s12993-024-00228-z-
dc.identifier.bibliographicCitationBehavioral and Brain Functions, v.20, no.1-
dc.relation.isPartOfBehavioral and Brain Functions-
dc.citation.titleBehavioral and Brain Functions-
dc.citation.volume20-
dc.citation.number1-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalWebOfScienceCategoryBehavioral Sciences-
dc.relation.journalWebOfScienceCategoryNeurosciences-
dc.subject.keywordPlusSPECTRUM DISORDER-
dc.subject.keywordPlusCONNECTIVITY-
dc.subject.keywordPlusTRACTOGRAPHY-
dc.subject.keywordPlusADOLESCENTS-
dc.subject.keywordPlusABILITIES-
dc.subject.keywordPlusDEFICITS-
dc.subject.keywordPlusEMOTION-
dc.subject.keywordPlusNETWORK-
dc.subject.keywordPlusCORTEX-
dc.subject.keywordAuthorAutism spectrum disorder-
dc.subject.keywordAuthorAutoencoder-
dc.subject.keywordAuthorFeature representation learning-
dc.subject.keywordAuthorStructural connectivity-
dc.subject.keywordAuthorIntegrated gradient-
Appears in Collections:
Center for Neuroscience Imaging Research (뇌과학 이미징 연구단) > 1. Journal Papers (저널논문)
Files in This Item:
There are no files associated with this item.

qrcode

  • facebook

    twitter

  • Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
해당 아이템을 이메일로 공유하기 원하시면 인증을 거치시기 바랍니다.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse