{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002282378,0.0002883938,0.0003852384,0.00009924647,0.0001017782,0.0001982029,0.0002437757,0.000230989,0.001019211],"category_scores_gemma":[0.0007163692,0.0001403379,0.0002086329,0.00008561689,0.0003697253,0.0002224011,0.0002767652,0.0005985618,0.0001161804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000212861,"about_ca_system_score_gemma":0.0001905105,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008715878,"about_ca_topic_score_gemma":0.001229857,"domain_scores_codex":[0.9998637,0.00001512692,0.0000124889,0.00003032926,0.00003379236,0.00004435674],"domain_scores_gemma":[0.9997787,0.00006373612,0.00004597711,0.00002651068,0.0000266206,0.00005849793],"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":[0.000176776,0.00002523748,0.000497955,0.00001469427,0.000005326773,0.00001570411,0.00001411032,0.000109474,0.9976283,0.00003183458,0.00001096457,0.001469714],"study_design_scores_gemma":[0.00003445249,0.001124604,0.1050892,0.0000112726,0.00004236262,0.000193163,0.00007142957,0.01271249,0.8801984,0.0002366159,0.0002711121,0.00001496793],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9976419,0.00005815702,0.002013655,0.00002176399,0.00001126017,0.00001126444,0.00005681237,0.00003124619,0.0001539659],"genre_scores_gemma":[0.9978382,0.00006997245,0.001503705,0.00003675977,0.000003737689,0.0000276249,0.00006980796,0.00002567516,0.0004246888],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001019211,"threshold_uncertainty_score":0.003409624,"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."}}