{"id":"W4415896590","doi":"10.1152/physrev.00005.2025","title":"Adaptive episodic memory: how multiple memory representations drive behavior in humans and nonhumans","year":2025,"lang":"en","type":"article","venue":"Physiological Reviews","topic":"Memory and Neural Mechanisms","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Baycrest Hospital; University of Toronto; York University","funders":"Canadian Institutes of Health Research - Antimicrobial Resistance Research Initiative; Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Episodic memory; Engram; Adaptive memory; Explicit memory; Encoding (memory); Implicit memory; Schema (genetic algorithms); Semantic memory; TRACE (psycholinguistics); Spatial memory","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":[0.0002890418,0.0002499828,0.0005752079,0.0001089763,0.000250997,0.00004141304,0.0003315964,0.00009663885,0.0001339935],"category_scores_gemma":[0.002162244,0.000177729,0.0001487727,0.0004239342,0.0002481605,0.0002007332,0.0002185844,0.0003685611,0.00007539357],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003232098,"about_ca_system_score_gemma":0.00001597158,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009396649,"about_ca_topic_score_gemma":0.00003788356,"domain_scores_codex":[0.9974651,0.0008404073,0.0003835984,0.0008370052,0.0001405732,0.0003332856],"domain_scores_gemma":[0.998696,0.0006025936,0.000152441,0.0004308425,0.00002107262,0.00009703462],"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":[0.00003513657,0.0001903143,0.0001854464,0.00004090309,0.000001642086,0.00003537303,0.0001380324,0.000006050407,0.9899532,0.002712789,0.001632792,0.005068376],"study_design_scores_gemma":[0.00162432,0.0007659915,0.05716064,0.0003693688,0.00009831253,0.000009276705,0.0004903841,0.0008736245,0.9210752,0.01326665,0.003523414,0.0007428682],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9946716,0.00115113,0.0002176125,0.0005363989,0.0002441907,0.001869952,0.00001723934,0.00007472793,0.001217144],"genre_scores_gemma":[0.9924076,0.003229699,0.0002781088,0.0017106,0.00004550777,0.0007434975,0.000005206235,0.000008986832,0.001570744],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.068878,"threshold_uncertainty_score":0.7247579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2356752748700799,"score_gpt":0.3869665481747903,"score_spread":0.1512912733047104,"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."}}