{"doi":"10.1109/embc46164.2021.9630284","title":"SMART (splitting-merging assisted reliable) Independent Component Analysis for Brain Functional Networks","abstract":"Independent component analysis (ICA) has been widely applied to estimate brain functional networks from functional magnetic resonance imaging (fMRI) data. ICA is a data-driven approach, however, the number of components must be prespecified. Indeed, it is difficult to estimate or determine an optimal number of components in fMRI analysis. In this paper, we propose a SMART (splitting-merging assisted reliable) ICA to overcome the problem. Our method first estimates group-level components using different settings and then yields reliable components by using a splitting and merging clustering approach. Subject-specific components are obtained using our previously proposed group information guided ICA (GIG-ICA) based on reliable group-level components to estimate individual-subject independent components. Simulations with unique components for subjects showed our method extracted components with high similarity to the ground truth spatial maps (SMs). For real fMRI data, the functional networks extracted by our method showed both similarity and specificity across subjects. To sum up, our method can effectively and accurately identify subject-specific brain functional networks without a need of parameter setting.Clinical Relevance- SMART ICA automatically extracts reliable subject-specific brain functional networks that can be used for biomarker identification.","journal":"2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)","year":2021,"id":215252,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":7,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9593,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":809954,"name":"Xingyu He","orcid":"0000-0002-9973-0665","position":1,"is_corresponding":false},{"id":256997,"name":"Vince D Calhoun","orcid":null,"position":2,"is_corresponding":false},{"id":227748,"name":"Yuhui Du","orcid":"0000-0002-0079-8177","position":0,"is_corresponding":true}],"reference_count":22,"raw_metadata":null,"created_at":"2026-07-18T23:52:55.971300Z","pmid":"34891937","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}