{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"omics_type":["Unknown"],"submitter":["Li HT"],"funding":["NIDA NIH HHS","NIA NIH HHS","NIMH NIH HHS"],"pubmed_abstract":["Extant research has implicated functional connectivity of the subgenual anterior cingulate cortex (sgACC) in major depressive disorders or depressive traits in neurotypical populations. However, prior studies have not distinguished the inputs and outputs of the sgACC, and the \"diagnostic\" accuracy of these connectivity metrics remains elusive. Here, we analyzed data of 890 subjects (459 women, age 22 to 35) from the Human Connectome Project using Granger causality analyses (GCA) with the sgACC as the seed and 268 regions of interest from the Shen's atlas as targets. Individual connectivities were assessed with an <i>F</i> test and group results were evaluated with a binomial test, both at a corrected threshold. We identified brain regions with significant input to and output from the sgACC"],"journal":["bioRxiv : the preprint server for biology"],"pagination":["2025.06.25.661556"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC12262191"],"repository":["biostudies-literature"],"pubmed_title":["Functional Inputs to the Subgenual Cingulate Cortex Distinguish Neurotypical Individuals with Severe and Mild Depressive Problems: Granger Causality and Clustering Analyses."],"pmcid":["PMC12262191"],"funding_grant_id":["R01 DA051922","R01 AG072893","U54 MH091657"],"pubmed_authors":["Li HT","Chaudhary S","Chen Y","Li CR","Ide JS"],"additional_accession":[]},"is_claimable":false,"name":"Functional Inputs to the Subgenual Cingulate Cortex Distinguish Neurotypical Individuals with Severe and Mild Depressive Problems: Granger Causality and Clustering Analyses.","description":"Extant research has implicated functional connectivity of the subgenual anterior cingulate cortex (sgACC) in major depressive disorders or depressive traits in neurotypical populations. However, prior studies have not distinguished the inputs and outputs of the sgACC, and the \"diagnostic\" accuracy of these connectivity metrics remains elusive. Here, we analyzed data of 890 subjects (459 women, age 22 to 35) from the Human Connectome Project using Granger causality analyses (GCA) with the sgACC as the seed and 268 regions of interest from the Shen's atlas as targets. Individual connectivities were assessed with an <i>F</i> test and group results were evaluated with a binomial test, both at a corrected threshold. We identified brain regions with significant input to and output from the sgACC","dates":{"release":"2025-01-01T00:00:00Z","publication":"2025 Jun","modification":"2026-07-09T10:25:41.502Z","creation":"2025-08-28T03:09:05.408Z"},"accession":"S-EPMC12262191","cross_references":{"pubmed":["40667126"],"doi":["10.1101/2025.06.25.661556"]}}