{"id":"W2940682109","doi":"10.1016/j.jneumeth.2019.04.010","title":"Component-related BOLD response to localize epileptic focus using simultaneous EEG-fMRI recordings at 3T","year":2019,"lang":"en","type":"article","venue":"Journal of Neuroscience Methods","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Calgary","funders":"Shahed University; Ministry of Trade, Industry and Energy; Cognitive Sciences and Technologies Council; University of Calgary","keywords":"Electroencephalography; EEG-fMRI; Neuroscience; Focus (optics); Psychology; Component (thermodynamics); Epilepsy; Independent component analysis; Functional magnetic resonance imaging; Brain mapping; Cognitive psychology; Audiology; Artificial intelligence; Computer science; Medicine; Physics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000231783,0.0003687571,0.0001600349,0.0003458927,0.0002491589,0.0003760466,0.0002482329,0.0004795482,0.00187458],"category_scores_gemma":[0.0007291739,0.0001742962,0.0002094122,0.0003588382,0.0001922625,0.0003531824,0.0001786327,0.0003872154,0.0002912643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001195363,"about_ca_system_score_gemma":0.0002290555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001580112,"about_ca_topic_score_gemma":0.007020902,"domain_scores_codex":[0.9999299,0.0000177558,0.000003176621,0.00001726366,0.00001965959,0.00001217377],"domain_scores_gemma":[0.9998996,0.00004724717,0.00001117329,0.000008106359,0.0000229327,0.00001091321],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005718999,0.000086407,0.004053161,0.0001671692,0.00008489605,0.0003253815,0.0002401268,0.00182792,0.9511201,0.000795126,0.001166052,0.03956176],"study_design_scores_gemma":[0.0002474741,0.001258576,0.2735202,0.0001162163,0.0006634695,0.00597277,0.000523637,0.08942422,0.614163,0.005935594,0.008055722,0.0001192411],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.800354,0.001111081,0.1894871,0.000552633,0.0001401314,0.0002312105,0.001435292,0.0007576792,0.005930874],"genre_scores_gemma":[0.9442165,0.00052902,0.05258898,0.0002698388,0.00009541227,0.0001560254,0.0004928362,0.0001780293,0.001473449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00187458,"threshold_uncertainty_score":0.006271064,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06481034109567839,"score_gpt":0.3684494726256238,"score_spread":0.3036391315299454,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}