{"id":"W3186215048","doi":"10.3389/fnsys.2021.688517","title":"The Impact of Small Time Delays on the Onset of Oscillations and Synchrony in Brain Networks","year":2021,"lang":"en","type":"article","venue":"Frontiers in Systems Neuroscience","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Hotchkiss Brain Institute; University of Calgary; University of Waterloo; University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; Cumming School of Medicine, University of Calgary","keywords":"Eigenvalues and eigenvectors; Synchronization (alternating current); Computer science; Stability (learning theory); Control theory (sociology); Artificial neural network; Biological neural network; Topology (electrical circuits); Dynamics (music); Spectrum (functional analysis); Matrix (chemical analysis); Neuroscience; Mathematics; Physics; Biology; Artificial intelligence; Combinatorics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007376266,0.0001273599,0.0002196415,0.0001170584,0.0001925234,0.00008388689,0.0003496628,0.00004993176,0.000001391002],"category_scores_gemma":[0.001723061,0.00007558313,0.0000635268,0.001172475,0.0004571185,0.00009782265,0.0001001859,0.0002149304,6.271534e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006485262,"about_ca_system_score_gemma":0.0001005346,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000882811,"about_ca_topic_score_gemma":0.00003076763,"domain_scores_codex":[0.9980937,0.0005861666,0.0003863245,0.0003911361,0.0002568602,0.0002857637],"domain_scores_gemma":[0.9981223,0.001201556,0.0002060749,0.0003878469,0.00003624041,0.00004592429],"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":[0.0001450844,0.000224858,0.1335512,0.00004818297,0.000005519235,0.00007874351,0.0003858915,0.4027202,0.4484562,0.004753265,0.007242593,0.00238819],"study_design_scores_gemma":[0.000192087,0.0001848168,0.07830401,0.00008640236,0.000002100411,0.00005587288,0.00009250185,0.9192183,0.001393269,0.0001953359,0.0001779651,0.00009736596],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9951729,0.0001912086,0.002208265,0.0005443951,0.001065885,0.0003730505,0.00003030846,0.00000969246,0.0004043495],"genre_scores_gemma":[0.9993015,0.0001103889,0.00001940426,0.0001665035,0.00001414655,0.00001358041,6.511182e-7,0.000009065562,0.0003647631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.516498,"threshold_uncertainty_score":0.308219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01969040603293262,"score_gpt":0.2411573419992875,"score_spread":0.2214669359663548,"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."}}