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{ "kind": "infographic", "prompt": "Fraction of mouse V1 neurons suppressed by E-ensemble holographic stimulation", "provider": "other", "raw_fields": { "title": "Fraction of mouse V1 neurons suppressed by E-ensemble holographic stimulation", "values": [ { "study": "Sanzeni 2023 V1 ensemble - 2P imaging", "se_pct": 7, "n_animals": 3, "source_doi": "10.1016/j.neuron.2023.09.010", "fraction_suppressed_pct": 44 }, { "study": "Sanzeni 2023 V1 ensemble - electrophysiology", "se_pct": 8, "source_doi": "10.1016/j.neuron.2023.09.010", "fraction_suppressed_pct": 38 }, { "study": "Chettih & Harvey 2019 single-neuron stim - decoding decrease", "source_doi": "10.1038/s41586-019-0997-6", "decoding_decrease_pct": 2 }, { "study": "Dalgleish 2020 100/200-neuron ensemble - matched suppression preserves balance", "source_doi": "10.7554/eLife.58889" } ], "variable_x": "study / measurement modality", "variable_y": "fraction of neurons suppressed (%)", "audit_issues": [ { "dimension": "metric_definition", "description": "Rows 1–2 report 'fraction of neurons suppressed (%)' from population-level optogenetic stim. Row 3 (Chettih & Harvey 2019) reports a 'decoding decrease (%)' from single-neuron stim — a different quantity that is not a network-suppression fraction. Row 4 (Dalgleish 2020) has no plottable value (qualitative).", "entries_affected": [ "10.1016/j.neuron.2023.09.010", "10.1038/s41586-019-0997-6", "10.7554/eLife.58889" ] }, { "dimension": "scope_population", "description": "Population-level holographic stim (rows 1–2) drives many neurons simultaneously; single-neuron stim (row 3) drives one cell at a time. Suppression fractions are not the same response.", "entries_affected": [ "10.1016/j.neuron.2023.09.010", "10.1038/s41586-019-0997-6" ] }, { "dimension": "sample_size", "description": "Row 1: n_animals = 3. Other rows lack matching n-definitions.", "entries_affected": [ "10.1016/j.neuron.2023.09.010" ] } ], "audit_verdict": "REDESIGN", "interpretation": "Across mouse V1 ensemble-stimulation studies, a substantial fraction of network neurons (38–44% for population-level stim; ~2% net decoding effect for single-neuron stim) is suppressed by E-cell activation, consistent with strong recurrent inhibition stabilizing high E→E gain.", "data_source_doi": "10.1016/j.neuron.2023.09.010", "audit_fabrication_flag": "Label 'Sanzeni 2023' on DOI 10.1016/j.neuron.2023.09.010 does not match DOI authors (O'Rawe et al. 2023). The 'Sanzeni 2023' attribution may refer to the wrong paper or be a senior-author shortcut not present in the metadata; the cite-key 'ORawe2023' is what citation_key_map returns for this DOI.", "mandatory_caption_caveats": [ "Rows 1–2 (ensemble-stim suppression %) cannot share an axis with row 3 (single-neuron decoding decrease %).", "Verify the 'Sanzeni 2023' label on DOI 10.1016/j.neuron.2023.09.010: the DOI maps to O'Rawe, Zhou, Li, LaFosse, Goldbach and Histed (2023) — Sanzeni is not on the author list.", "Phase 7 writer: REDESIGN verdict — implement as: Restrict to ensemble-stim 'fraction suppressed' studies (Sanzeni 2023 2P/ephys; Dalgleish 2020 if a quantitative value can be extracted) and report Chettih & Harvey 2019 single-neuron effect in a separate panel or in caption text. Resolve the Sanzeni/O'Rawe author/DOI mismatch first." ] }, "section_id": "section_09", "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json", "target_ref": "wiki_page:computationalreviewrecurrence-09-amplification-isn", "review_repo": "ComputationalReviewRecurrence", "section_ref": "wiki_page:computationalreviewrecurrence-09-amplification-isn", "source_path": "evidence/section_09_evidence_package.json", "source_refs": [], "section_title": "9. Physiological signature I — recurrent amplification of weak inputs in mouse cortex; balanced-amplification regimes; ISN operation", "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_09_evidence_package.json", "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f", "created_by": "persona-jerome-lecoq-gbo-neuroscience", "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence" }