{"id":"W3106232040","doi":"10.1038/s41598-020-77090-2","title":"Operant conditioning of motor cortex neurons reveals neuron-subtype-specific responses in a brain-machine interface task","year":2020,"lang":"en","type":"article","venue":"Scientific Reports","topic":"EEG and Brain-Computer Interfaces","field":"Neuroscience","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Rehabilitation Institute; University of Toronto; University Health Network","funders":"Physicians' Services Incorporated Foundation; Natural Sciences and Engineering Research Council of Canada; Government of Canada","keywords":"Neuroscience; Motor cortex; Operant conditioning; Task (project management); Brain–computer interface; Interface (matter); Conditioning; Neuron; Computer science; Psychology; Electroencephalography; Reinforcement; Stimulation","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00103843,0.0002694246,0.0004412869,0.000311073,0.0002449508,0.0003573247,0.0005493197,0.00006598738,0.0002168746],"category_scores_gemma":[0.002374341,0.0002469007,0.000137452,0.001099051,0.0005584377,0.0003911772,0.0003234292,0.0003709991,0.00005481714],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003665217,"about_ca_system_score_gemma":0.0001369665,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001846181,"about_ca_topic_score_gemma":0.000009631798,"domain_scores_codex":[0.9957802,0.0004518002,0.001105671,0.001531577,0.0006621258,0.0004686738],"domain_scores_gemma":[0.9976508,0.0006500226,0.000540842,0.0008288025,0.000105341,0.0002241758],"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":[0.0001120495,0.00009806449,0.001160653,0.00003835066,0.000003144968,0.001092748,0.001504331,0.0003001866,0.9814677,0.00009078463,0.01378651,0.0003454729],"study_design_scores_gemma":[0.000555533,0.0005034244,0.01060412,0.0002384689,0.00001019124,0.0007943027,0.0001753117,0.005017729,0.9044532,0.0007599939,0.07640272,0.0004849634],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9911042,0.0002333002,0.0005603498,0.00300933,0.003775654,0.0005513047,0.00006419497,0.0001285657,0.0005730915],"genre_scores_gemma":[0.9968458,0.0000098748,0.0001990109,0.001091795,0.00006054448,0.0000159533,0.000011775,0.00003335892,0.001731906],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07701447,"threshold_uncertainty_score":0.9999983,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03550842107961094,"score_gpt":0.2847859997007278,"score_spread":0.2492775786211168,"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."}}