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- Live5/17/2026, 4:35:28 PM
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{ "kind": "infographic", "prompt": "The debate over ISN detection reveals that two-population models vs four-population models make fundamentally different predictions about what paradoxical effects mean for cortical architecture. Layer-specific analysis further complicates the picture, suggesting ISN may not be a uniform property of cortex.", "provider": "other", "raw_fields": { "papers": [ { "n": 0, "doi": "10.7554/elife.54875", "value": "3", "method": "two-population ISN model fit to optogenetic data", "metric": "Cortical areas showing ISN operation", "n_analyzed": null, "ci_or_error": null, "text_access": "fulltext", "n_definition": "cortical areas tested", "scope_region": "V1, S1, motor cortex", "study_system": "mouse cortex in vivo", "taxonomic_level": "PV interneurons", "scope_population": "PV+ interneurons and pyramidal cells", "value_source_sentence": "We find clear evidence for ISN operation in mouse visual, somatosensory, and motor cortex.", "experimental_conditions": "optogenetic perturbation of PV+ neurons, transgenic expression" }, { "n": 0, "doi": "10.1523/JNEUROSCI.0963-17.2017", "value": "large proportion", "method": "multi-neuron network simulation", "metric": "Fraction of inhibitory population needed for ISN detection", "n_analyzed": null, "ci_or_error": null, "text_access": "fulltext", "n_definition": "model neurons perturbed", "scope_region": "neocortex (generic)", "study_system": "computational cortical networks", "taxonomic_level": "all inhibitory neurons", "scope_population": "inhibitory neurons", "value_source_sentence": "Our models predict that a large proportion of the inhibitory network must be perturbed to reliably detect an ISN regime robustly in cortex.", "experimental_conditions": "simulated optogenetic perturbations" }, { "n": 0, "doi": "10.1016/j.neunet.2023.07.020", "value": "2 of 3 layers (L4, L5 but not L2/3)", "method": "neural mass model with layer-specific connectivity", "metric": "Cortical layers in ISN regime", "n_analyzed": null, "ci_or_error": null, "text_access": "fulltext", "n_definition": "cortical layers modeled", "scope_region": "cortical column (all layers)", "study_system": "multi-layer cortical column model", "taxonomic_level": "inhibitory populations (not PV-specific)", "scope_population": "excitatory and inhibitory populations per layer", "value_source_sentence": "The results show that layer 2/3 in the model does not operate in the ISN regime but layers 4 and 5 do operate in the ISN regime.", "experimental_conditions": "Allen Institute-derived connectivity" }, { "n": 0, "doi": "10.7554/elife.49967", "value": "not evidence for ISN", "method": "four-population analytical model and simulations", "metric": "Interpretation of paradoxical response", "n_analyzed": null, "ci_or_error": null, "text_access": "fulltext", "n_definition": "network model populations", "scope_region": "ALM L2/3 and L5, S1", "study_system": "mouse ALM and S1 cortex", "taxonomic_level": "PV, SOM, VIP subtypes", "scope_population": "PV, SOM, VIP interneurons and pyramidal cells", "value_source_sentence": "In both four-population models, the paradoxical effect implies not too strong recurrent excitation. It is not evidence for stabilization by inhibition.", "experimental_conditions": "PV photostimulation in vivo" } ], "comparison_id": "isn-detection-methods-predictions", "comparison_name": "ISN Detection: Model Predictions vs Experimental Evidence Across Cortical Areas", "comparison_type": "cross-study conflict", "what_it_reveals": "The debate over ISN detection reveals that two-population models vs four-population models make fundamentally different predictions about what paradoxical effects mean for cortical architecture. Layer-specific analysis further complicates the picture, suggesting ISN may not be a uniform property of cortex.", "homogeneity_check": { "caveats": [ "Mix of experimental and purely computational studies", "Different cortical areas and layers compared", "Two-population vs four-population models make fundamentally different assumptions", "Paper D's 'not evidence for ISN' is a qualitative interpretation, not a quantitative metric" ], "n_definition_uniform": "false", "scope_region_uniform": "false", "taxonomic_level_uniform": "false", "scope_population_uniform": "false" }, "suggested_plot_type": "grouped bar" }, "section_id": "section_12_evidence_package", "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV/blob/df9fc7e8d455b084152c9d713558dae0013cef21/evidence/section_12_evidence_package.json", "target_ref": "wiki_page:computationalreviewpv-12", "review_repo": "ComputationalReviewPV", "section_ref": "wiki_page:computationalreviewpv-12", "source_path": "evidence/section_12_evidence_package.json", "source_refs": [ "paper:paper-0f05fb84ee59", "paper:paper-38fe71bdf9b6", "paper:paper-5135d667ceac", "paper:paper-d6edd2b57842" ], "section_title": "Computational Models of PV Circuit Function", "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": "df9fc7e8d455b084152c9d713558dae0013cef21", "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV" }, "generation_status": "complete", "review_bundle_ref": "analysis_bundle:ab-e6261c8263e7", "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV/blob/df9fc7e8d455b084152c9d713558dae0013cef21/evidence/section_12_evidence_package.json", "commit_sha": "df9fc7e8d455b084152c9d713558dae0013cef21", "created_by": "persona-jerome-lecoq-gbo-neuroscience", "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV" }