{"doi":"10.1101/2022.01.31.22270169","title":"Moment-to-moment fluctuations of hemodynamic responses in posterior default mode networks differentially predict level of attentional lapses in adolescents with Attention-Deficit/Hyperactivity Disorder","abstract":"Abstract Background The neurobiological underpinnings of the characteristically higher intra-individual variability of reaction times (IIVRT) in patients with ADHD remain poorly understood. The aim of the current study was to characterize the role of the default mode and other canonical brain networks measured by functional magnetic resonance imaging (fMRI) to task performance fluctuations measured by IIVRT. To our knowledge, no prior fMRI study has shown the involvement of posterior default mode network (DMN) in ADHD IIVRT. We expected that moment-to-moment fluctuations in hemodynamic responses in posterior DMN would predict higher IIVRT in ADHD. Methods Adolescents (12 to 19 years old) with ADHD (n= 55) and healthy controls (n= 55) performed a fMRI Go/NoGo task. Whole-brain independent component analysis (ICA) segregated hemodynamic responses into functional brain networks, then further decomposed into individual trial-specific estimates of hemodynamic response amplitude. Mean and variability metrics of these amplitudes were tested in stepwise linear regression analyses to identify which functional brain networks predicted high IIVRT. Results As hypothesized, variability in hemodynamic responses in posterior DMN regions predicted level of IIVRT. In posterior cingulate cortex this variability predicted higher IIVRT only in ADHD, whereas in precuneus variability in hemodynamic responses predicted lower IIVRT. Average hemodynamic responses in a bilateral superior temporal cortex network predicted higher IIVRT only in ADHD. Conclusion Our findings suggest that estimating variability in hemodynamic responses is crucial to understand the involvement of the intrinsic default mode in attentional lapses in ADHD. The parcellation into subnetworks showed the differentiating role of default mode in attentional lapses in ADHD.","journal":"medRxiv","year":2022,"id":305665,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.959,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":1000075,"name":"Yu Sun Chung","orcid":null,"position":1,"is_corresponding":false},{"id":1000076,"name":"Sabin Khadka","orcid":null,"position":2,"is_corresponding":false},{"id":298355,"name":"Michael C. Stevens","orcid":"0000-0002-3799-5465","position":3,"is_corresponding":false},{"id":999797,"name":"Lin Sørensen","orcid":"0000-0002-2112-8957","position":0,"is_corresponding":true}],"reference_count":61,"raw_metadata":null,"created_at":"2026-07-19T00:32:44.983506Z","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":[]}