{"id":"W4415394233","doi":"10.1162/imag.a.999","title":"Expectation dynamically modulates the representational time course of objects and locations","year":2025,"lang":"en","type":"article","venue":"Imaging Neuroscience","topic":"Neural dynamics and brain function","field":"Neuroscience","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canadian Institute for Advanced Research","funders":"Research Computing Centre, University of Queensland; National Health and Medical Research Council; Australian Research Council","keywords":"Decoding methods; Stimulus (psychology); Predictability; Predictive coding; Neural decoding; Visual perception; Cognitive neuroscience of visual object recognition; Information theory; Visual Objects","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003721008,0.0001719787,0.0001750145,0.0001306829,0.0001003195,0.0006668456,0.000235451,0.0002588972,0.001284715],"category_scores_gemma":[0.005591256,0.0002002653,0.0001471298,0.0001255624,0.0002517961,0.0007604376,0.0003801196,0.0003638886,0.0001625095],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001922781,"about_ca_system_score_gemma":0.0002298317,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007328871,"about_ca_topic_score_gemma":0.0008600595,"domain_scores_codex":[0.9997786,0.00004406123,0.00001190471,0.00006829219,0.0000680445,0.00002912419],"domain_scores_gemma":[0.9986732,0.0007083533,0.0003325629,0.0001006949,0.0001155674,0.00006963024],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.001743382,0.00008574183,0.04285836,0.0001609703,0.00006026045,0.0003263994,0.001062355,0.004948808,0.8853381,0.003298854,0.0004607807,0.05965591],"study_design_scores_gemma":[0.00006088973,0.001075606,0.7513382,0.00006905496,0.0001338127,0.0008467407,0.0007288419,0.06842586,0.1611755,0.01368511,0.002364923,0.00009551494],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9770045,0.0001178447,0.01996748,0.00009687229,0.0000209368,0.00001433892,0.00009867606,0.00008307194,0.002596192],"genre_scores_gemma":[0.9962531,0.0000680876,0.003298386,0.00001838128,0.000006108698,0.000007620764,0.00008556068,0.00002197282,0.0002408282],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001284715,"threshold_uncertainty_score":0.004297793,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01060702336744858,"score_gpt":0.2802325574553987,"score_spread":0.2696255340879501,"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."}}