{"id":"W2968921024","doi":"10.3389/fnins.2019.00900","title":"Intrinsic Frequencies of the Resting-State fMRI Signal: The Frequency Dependence of Functional Connectivity and the Effect of Mode Mixing","year":2019,"lang":"en","type":"article","venue":"Frontiers in Neuroscience","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Baycrest Hospital","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Resting state fMRI; Functional connectivity; Mixing (physics); Default mode network; SIGNAL (programming language); Physics; Neuroscience; Statistical physics; Psychology; Computer science; Quantum mechanics","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":[0.001301042,0.0005607864,0.0003062784,0.0004822708,0.000246382,0.0005614351,0.0005145646,0.0005620112,0.0008158661],"category_scores_gemma":[0.007376928,0.0003272422,0.0005260432,0.0003048538,0.0007221083,0.0009844661,0.0005378359,0.0007248513,0.0001588831],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002621698,"about_ca_system_score_gemma":0.000310617,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00104466,"about_ca_topic_score_gemma":0.001054024,"domain_scores_codex":[0.9996774,0.0001045317,0.00001763664,0.00009223064,0.00007974599,0.00002851039],"domain_scores_gemma":[0.9985095,0.001063042,0.000136374,0.000177532,0.00006973471,0.00004374654],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0008615558,0.0001738079,0.01930479,0.0006270136,0.0004217791,0.0007827285,0.0009573508,0.2129057,0.5929375,0.02202605,0.0009583251,0.1480435],"study_design_scores_gemma":[0.00002844597,0.0002669209,0.03973602,0.00005872249,0.000118504,0.0006821084,0.00007496272,0.8366416,0.1028226,0.0176283,0.001844753,0.00009716906],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4705859,0.0006950459,0.5261407,0.000242844,0.00005888793,0.00007733692,0.0002726406,0.0003688423,0.00155784],"genre_scores_gemma":[0.9054028,0.0003873031,0.09293691,0.00005837774,0.0000297762,0.00009383621,0.0002528728,0.0001680861,0.00066996],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001301042,"threshold_uncertainty_score":0.006880641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01676701560825034,"score_gpt":0.2305942912809631,"score_spread":0.2138272756727128,"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."}}