{"doi":"10.1002/advs.202200887","title":"Interictal SEEG Resting‐State Connectivity Localizes the Seizure Onset Zone and Predicts Seizure Outcome","abstract":"Localization of epileptogenic zone currently requires prolonged intracranial recordings to capture seizure, which may take days to weeks. The authors developed a novel method to identify the seizure onset zone (SOZ) and predict seizure outcome using short-time resting-state stereotacticelectroencephalography (SEEG) data. In a cohort of 27 drug-resistant epilepsy patients, the authors estimated the information flow via directional connectivity and inferred the excitation-inhibition ratio from the 1/f power slope. They hypothesized that the antagonism of information flow at multiple frequencies between SOZ and non-SOZ underlying the relatively stable epilepsy resting state could be related to the disrupted excitation-inhibition balance. They found flatter 1/f power slope in non-SOZ regions compared to the SOZ, with dominant information flow from non-SOZ to SOZ regions. Greater differences in resting-state information flow between SOZ and non-SOZ regions are associated with favorable seizure outcome. By integrating a balanced random forest model with resting-state connectivity, their method localized the SOZ with an accuracy of 88% and predicted the seizure outcome with an accuracy of 92% using clinically determined SOZ. Overall, this study suggests that brief resting-state SEEG data can significantly facilitate the identification of SOZ and may eventually predict seizure outcomes without requiring long-term ictal recordings.","journal":"Advanced Science","year":2022,"id":235918,"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":74,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9481,"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":469436,"name":"Vasileios Kokkinos","orcid":"0000-0002-4309-5455","position":1,"is_corresponding":false},{"id":271427,"name":"Shuai Ye","orcid":"0000-0002-9862-4983","position":2,"is_corresponding":false},{"id":765566,"name":"Alexandra Urban","orcid":"0000-0003-4025-6417","position":3,"is_corresponding":false},{"id":668067,"name":"Anto Bagić","orcid":"0000-0002-6284-8336","position":4,"is_corresponding":false},{"id":241367,"name":"Mark P. Richardson","orcid":"0000-0001-8925-3140","position":5,"is_corresponding":false},{"id":271429,"name":"Bin He","orcid":"0000-0003-2944-8602","position":6,"is_corresponding":false},{"id":344116,"name":"Haiteng Jiang","orcid":"0000-0003-0739-8413","position":0,"is_corresponding":true}],"reference_count":80,"raw_metadata":null,"created_at":"2026-07-19T00:21:53.333008Z","pmid":"35545899","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":[]}