{"id":"W3016870360","doi":"10.1002/hbm.25019","title":"Dark control: The default mode network as a reinforcement learning agent","year":2020,"lang":"en","type":"article","venue":"Human Brain Mapping","topic":"Functional Brain Connectivity Studies","field":"Neuroscience","cited_by":131,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; Mila - Quebec Artificial Intelligence Institute; Montreal Neurological Institute and Hospital","funders":"Canada First Research Excellence Fund; Seventh Framework Programme; Innovative Medicines Initiative; Studienstiftung des Deutschen Volkes; Deutsche Forschungsgemeinschaft","keywords":"Default mode network; Reinforcement learning; Perspective (graphical); Psychology; Cognitive psychology; Action (physics); Computer science; Markov decision process; Cognitive science; Artificial intelligence; Machine learning; Neuroscience; Functional connectivity; Markov process","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":["metaresearch","sts"],"consensus_categories":[],"category_scores_codex":[0.0005301213,0.0002208388,0.0002400209,0.00003792094,0.001938489,0.0001382152,0.0003713889,0.000044321,0.0001309419],"category_scores_gemma":[0.009880648,0.0001798926,0.000130518,0.0003515898,0.000160972,0.0001376632,0.0002786469,0.0004696485,0.0002637035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007635777,"about_ca_system_score_gemma":0.00003645921,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004031425,"about_ca_topic_score_gemma":0.00001334882,"domain_scores_codex":[0.9977612,0.00039078,0.0003012078,0.0005695579,0.0004871908,0.0004900995],"domain_scores_gemma":[0.9952056,0.004220454,0.0001657493,0.000258373,0.000041429,0.0001083602],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00008199536,0.0000198714,0.0007396419,0.00004215798,0.00007188367,0.00004749479,0.005858297,0.5897293,0.2324075,0.04822345,0.1223274,0.0004510968],"study_design_scores_gemma":[0.002658842,0.000657321,0.008802578,0.0001583379,0.00004775507,0.00003384699,0.002033008,0.1826479,0.001047166,0.01628316,0.7847214,0.0009087267],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"commentary","genre_gemma":"empirical","genre_scores_codex":[0.269214,0.0004545471,0.1465001,0.4293073,0.001387231,0.003240145,0.000009015894,0.001787453,0.1481002],"genre_scores_gemma":[0.9029725,0.000005658541,0.00003566638,0.09477223,0.0006529079,0.00007434887,0.000002432418,0.00002718381,0.001457051],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.662394,"threshold_uncertainty_score":0.9993609,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06528342678069163,"score_gpt":0.281909959698544,"score_spread":0.2166265329178524,"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."}}