{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001230152,0.00007899172,0.00007154568,0.00008269475,0.0002918085,0.0000908244,0.0002258385,0.00001098915,0.000003968728],"category_scores_gemma":[0.0007363867,0.0000583886,0.00002557329,0.0005461379,0.000530345,0.0002697058,0.00008884563,0.00008316746,0.000002603005],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001198808,"about_ca_system_score_gemma":0.00005912902,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001406944,"about_ca_topic_score_gemma":0.000002128875,"domain_scores_codex":[0.9990658,0.0000799172,0.0001641798,0.0003560202,0.0001977596,0.0001362823],"domain_scores_gemma":[0.9991923,0.0004291309,0.00008460289,0.0002115729,0.00005560281,0.00002678163],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000005130058,0.00003163221,0.002758927,0.000005123103,3.626958e-7,0.000001453284,0.000110181,0.001172612,0.989427,0.004305364,0.0001166107,0.002065568],"study_design_scores_gemma":[0.000131846,0.00001749238,0.1481674,0.00001743062,0.000007098094,0.00002444176,0.00007067956,0.7666436,0.08036636,0.004393331,0.00008690958,0.00007334701],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9850562,0.0000301316,0.006094068,0.006727723,0.0004433765,0.0002234508,0.00001097177,0.00005755352,0.001356531],"genre_scores_gemma":[0.9976861,0.00001370127,0.00007412462,0.001567784,0.000009570813,0.00001068773,0.000001402824,0.000004559582,0.0006320163],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9090607,"threshold_uncertainty_score":0.2381018,"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."}}