{"doi":"10.1364/boe.6.002337","title":"Dynamic functional connectivity revealed by resting-state functional near-infrared spectroscopy","abstract":null,"journal":"Biomedical Optics Express","year":2015,"id":593974,"datarank":0.5775221402565088,"base_score":3.8501476017100584,"endowment":3.8501476017100584,"self_citation_contribution":0.5775221402565088,"citation_network_contribution":0.0,"self_endowment_contribution":0.5775221402565088,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":46,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":null,"is_data_producer":false,"deposit_databanks":null,"is_oa":false,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":null,"fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":294220,"name":"Hanli Liu","orcid":"0000-0002-9312-5691","position":1,"is_corresponding":false},{"id":330172,"name":"Xuhong Liao","orcid":null,"position":2,"is_corresponding":false},{"id":167660,"name":"Jingping Xu","orcid":null,"position":3,"is_corresponding":false},{"id":434203,"name":"Wenli Liu","orcid":"0000-0003-1036-4564","position":4,"is_corresponding":false},{"id":426453,"name":"Fenghua Tian","orcid":"0000-0001-8985-9679","position":5,"is_corresponding":false},{"id":328624,"name":"Yong He","orcid":"0000-0002-7039-2850","position":6,"is_corresponding":false},{"id":707935,"name":"Haijing Niu","orcid":"0000-0002-3887-1966","position":7,"is_corresponding":false},{"id":681924,"name":"Zhen Li","orcid":"0000-0002-9783-169X","position":0,"is_corresponding":false}],"reference_count":0,"raw_metadata":{"has_enrichment":true,"resolved":true,"title":"Dynamic functional connectivity revealed by resting-state functional near-infrared spectroscopy","abstract":"The brain is a complex network with time-varying functional connectivity (FC) and network organization. However, it remains largely unknown whether resting-state fNIRS measurements can be used to characterize dynamic characteristics of intrinsic brain organization. In this study, for the first time, we used the whole-cortical fNIRS time series and a sliding-window correlation approach to demonstrate that fNIRS measurement can be ultimately used to quantify the dynamic characteristics of resting-state brain connectivity. Our results reveal that the fNIRS-derived FC is time-varying, and the variability strength (Q) is correlated negatively with the time-averaged, static FC. Furthermore, the Q values also show significant differences in connectivity between different spatial locations (e.g., intrahemispheric and homotopic connections). The findings are reproducible across both sliding-window lengths and different brain scanning sessions, suggesting that the dynamic characteristics in fNIRS-derived cerebral functional correlation results from true cerebral fluctuation.","is_dataset_classified":null,"base_score":3.8501476017100584,"endowment":3.8501476017100584,"datacite_reuse_total":0,"file_count":0,"downloads":0,"views":0,"has_version_chain":false,"is_dataset":false,"is_oa":false,"pmid":"26203365","pmcid":"PMC4505693","openalex_id":"https://openalex.org/W2241382951","authors":[],"funders":[{"funder_name":"Fundamental Research Funds for the Central Universities","grant_id":"2012LYB06","title":null},{"funder_name":"National Natural Science Foundation of China (NSFC)","grant_id":"81030028","title":null},{"funder_name":"National Natural Science Foundation of China (NSFC)","grant_id":"81201122","title":null},{"funder_name":"National Science Fund for Distinguished Young Scholars","grant_id":"81225012","title":null},{"funder_name":"Specialized Research Fund for the Doctoral Program of Higher Education, and the Open Research Fund of the State Key Laboratory of Cognitive Neuroscience and Learning","grant_id":"","title":null}],"total_grants":5,"fwci":3.6732,"citation_percentile":0.92973253,"influential_citations":0,"citation_trend":[{"year":2016,"count":3},{"year":2017,"count":5},{"year":2018,"count":7},{"year":2019,"count":5},{"year":2020,"count":8},{"year":2021,"count":2},{"year":2022,"count":5},{"year":2024,"count":3},{"year":2025,"count":6},{"year":2026,"count":2}],"oa_status":"gold","license":"cc-by-nc-sa","oa_locations":[{"url":"https://doi.org/10.1364/boe.6.002337","host_type":"journal"},{"url":"https://doi.org/10.1364/boe.6.002337","host_type":"publisher"},{"url":"https://www.osapublishing.org/viewmedia.cfm?URI=boe-6-7-2337&seq=0","host_type":"publisher"},{"url":"https://pubmed.ncbi.nlm.nih.gov/26203365","host_type":"repository"},{"url":"https://www.ncbi.nlm.nih.gov/pmc/articles/4505693","host_type":"repository"},{"url":"http://hdl.handle.net/10106/26468","host_type":"repository"}],"fields_of_study":["Optical Imaging and Spectroscopy Techniques","Functional Brain Connectivity Studies","Advanced Chemical Sensor Technologies"],"mesh_terms":[],"keywords":["Dynamic functional connectivity","Resting state fMRI","Functional near-infrared spectroscopy","Functional connectivity","Neuroscience","Correlation","Sliding window protocol","Computer science","Biological system","Pattern recognition (psychology)","Artificial intelligence","Window (computing)","Psychology","Mathematics","Cognition","Biology","(170.3880) Medical And Biological Imaging","(170.5380) Physiology","(170.2655) Functional Monitoring And Imaging"],"sdg_mappings":[],"linked_datasets":[],"clinical_trials":[],"software_tools":[],"database_accessions":[],"source":"live","citation_network_status":"fetched"},"created_at":"2026-07-27T13:02:58.438340Z","pmid":null,"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":[]}