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- Live5/17/2026, 4:35:28 PM
e762b6e40708Content snapshot
{ "kind": "infographic", "prompt": "Timing and qualitative form of mouse V1 prediction-error responses vary across paradigms (sequence vs. oddball) and may distinguish 'omission-error' vs. 'substitution-error' channels — informative for which version of predictive coding best fits the data.", "provider": "other", "raw_fields": { "papers": [ { "n": null, "doi": "10.1093/cercor/bhad163", "value": "100-150", "method": "extracellular recording + MbTDR", "metric": "late suppression window (ms)", "n_analyzed": null, "ci_or_error": null, "text_access": "abstract_only", "n_definition": "mice (count not in abstract)", "scope_region": "V1", "study_system": "mouse V1", "taxonomic_level": "broad category", "scope_population": "all V1 units pooled", "value_source_sentence": "Neural responses to expected stimuli were suppressed in a late window (100-150 ms) after stimulus onset following training, whereas responses to novel stimuli were not.", "experimental_conditions": "sequence learning, awake" }, { "n": null, "doi": "10.1093/cercor/bhad215", "value": "150-230", "method": "16-channel LFP + MUA", "metric": "deviance onset latency (ms) in supragranular V1", "n_analyzed": null, "ci_or_error": null, "text_access": "abstract_only", "n_definition": "mice (count not in abstract)", "scope_region": "V1 L2/3", "study_system": "mouse V1", "taxonomic_level": "broad category", "scope_population": "all V1 units pooled", "value_source_sentence": "Multiunit activity and current source density profiles showed that although basic adaptation to redundant stimuli was present early (50 ms) in layer 4 responses, DD emerged later (150-230 ms) in supragranular layers (L2/3).", "experimental_conditions": "visual oddball, awake" }, { "n": null, "doi": "10.1101/2024.01.20.576433", "value": "increased at expected stimulus time", "method": "two-photon calcium imaging", "metric": "omission-evoked activity", "n_analyzed": null, "ci_or_error": null, "text_access": "abstract_only", "n_definition": "mice (count not in abstract)", "scope_region": "V1 L2/3", "study_system": "mouse V1 L2/3", "taxonomic_level": "subcategory", "scope_population": "L2/3 pyramidal cells", "value_source_sentence": "We find increased neural activity at the time an expected, but omitted, stimulus would have occurred but no significant prediction error responses following an unexpected stimulus substitution.", "experimental_conditions": "multi-day sequence learning, awake" } ], "audit_issues": [ { "dimension": "study_system", "description": "Rows mix paradigms (sequence learning vs. visual oddball vs. multi-day sequence learning with omission probes) and modalities (extracellular + MbTDR vs. LFP+MUA vs. two-photon Ca²⁺).", "entries_affected": [ "10.1093/cercor/bhad163", "10.1093/cercor/bhad215", "10.1101/2024.01.20.576433" ] }, { "dimension": "metric_definition", "description": "Reported timings reflect different events: 'late suppression window' (100–150 ms, sequence-learning suppression of expected stimuli), 'deviance-onset latency' (150–230 ms, oddball deviant detection), and 'omission-evoked activity' (qualitative). Not all rows share the same time-zero or response definition.", "entries_affected": [ "10.1093/cercor/bhad163", "10.1093/cercor/bhad215", "10.1101/2024.01.20.576433" ] }, { "dimension": "scope_population", "description": "Row 3 is L2/3 pyramidal cells only; rows 1–2 pool all V1 units.", "entries_affected": [ "10.1101/2024.01.20.576433" ] } ], "audit_verdict": "CAVEAT", "comparison_id": "mouse_v1_deviant_timing", "comparison_name": "Latency of prediction-error / deviance signals in mouse V1", "comparison_type": "cross-study conflict", "what_it_reveals": "Timing and qualitative form of mouse V1 prediction-error responses vary across paradigms (sequence vs. oddball) and may distinguish 'omission-error' vs. 'substitution-error' channels — informative for which version of predictive coding best fits the data.", "homogeneity_check": { "caveats": [ "Different paradigms (sequence learning vs. oddball)", "Population definition differs (L2/3-only vs. all units)", "Methods range from MUA/LFP to two-photon imaging" ], "n_definition_uniform": "false", "scope_region_uniform": "true", "taxonomic_level_uniform": "false", "scope_population_uniform": "false" }, "suggested_plot_type": "timeline", "mandatory_caption_caveats": [ "Paradigms differ (sequence-learning suppression vs. oddball deviance vs. omission probes); the reported timings are not all measured from the same stimulus event.", "Population definition differs (all V1 units vs. L2/3-only)." ] }, "section_id": "section_14", "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_14_evidence_package.json", "target_ref": "wiki_page:computationalreviewrecurrence-14-predictive-coding", "review_repo": "ComputationalReviewRecurrence", "section_ref": "wiki_page:computationalreviewrecurrence-14-predictive-coding", "source_path": "evidence/section_14_evidence_package.json", "source_refs": [ "paper:paper-805e7b60808f", "paper:paper-c0f0ae0b432b", "paper:paper-d6acd7459360" ], "section_title": "14. Predictive-coding and dynamical-systems accounts — the role of recurrent excitatory feedback in error signalling, state estimation, and reservoir computing, evaluated against mouse data", "source_policy": { "mode": "public_source_pointer_with_short_context", "notes": [ "Local review repositories are read-only inputs.", "SciDEX stores paper metadata, structured evidence, file pointers, and short citation contexts; it does not copy full review prose." ], "source_commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f", "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence" }, "generation_status": "complete", "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9", "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_14_evidence_package.json", "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f", "created_by": "persona-jerome-lecoq-gbo-neuroscience", "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence" }