{"id":"W4411209042","doi":"10.1016/j.cell.2025.05.025","title":"Dopamine encodes deep network teaching signals for individual learning trajectories","year":2025,"lang":"en","type":"article","venue":"Cell","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Gatsby Charitable Foundation; Medical Research Council; Canadian Institute for Advanced Research; Royal Society; UK Research and Innovation; Wellcome Trust; European Research Council; Human Frontier Science Program","keywords":"Biology; Optogenetics; Dopamine; Neuroscience; Dopaminergic; Associative learning; Machine learning; Artificial intelligence; Stimulus (psychology); Cognitive psychology; Computer science; Psychology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002895852,0.0001047435,0.0001169066,0.00005320306,0.0004459482,0.0001024022,0.0001552379,0.00004725873,0.00001735075],"category_scores_gemma":[0.0004095196,0.00009450953,0.00006122797,0.0001635367,0.00003552637,0.00009901718,0.00005427302,0.0002295763,0.000006326243],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001716429,"about_ca_system_score_gemma":0.00001933339,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004746585,"about_ca_topic_score_gemma":0.000005968604,"domain_scores_codex":[0.9991117,0.0001025284,0.000146724,0.0002752047,0.00010817,0.0002556531],"domain_scores_gemma":[0.9989905,0.0008101803,0.00006180818,0.00009099954,0.00001586666,0.00003066231],"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":[0.00006865807,0.00008413159,0.001728241,0.0001017374,0.000008309794,0.000005733954,0.0003413902,0.02990435,0.9319327,0.008741144,0.002556678,0.0245269],"study_design_scores_gemma":[0.001341361,0.000644625,0.002139627,0.0001034067,0.00009097264,0.000006342699,0.000384222,0.1137879,0.7201958,0.01516928,0.1455379,0.00059865],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9271747,0.0001772544,0.05259395,0.0003282851,0.001600645,0.0004106187,0.000009689514,0.0001892612,0.01751554],"genre_scores_gemma":[0.9905472,0.00001297536,0.0006076148,0.0005697637,0.0002239504,0.00002509193,0.00001016267,0.0000119719,0.007991275],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.211737,"threshold_uncertainty_score":0.3853987,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02159981098291369,"score_gpt":0.2603644705444803,"score_spread":0.2387646595615666,"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."}}