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- Live5/17/2026, 4:35:28 PM
0fbee1e21ce6Content snapshot
{ "kind": "infographic", "prompt": "The evidence reveals a nuanced picture where PV connectivity is anatomically dense but functionally tuned. Connection probability may be high (blanket-like) but synaptic weights are modulated by activity and co-tuning, creating selective inhibition within a framework of dense connectivity. Whether PV inhibition appears selective or nonselective may depend on the level of analysis (connectivity vs synaptic weight), brain region, and experimental conditions.", "provider": "other", "raw_fields": { "papers": [ { "n": 0, "doi": "10.1523/jneurosci.3646-15.2016", "value": "~120 μm", "method": "two-photon optogenetics + calcium imaging", "metric": "VIP lateral disinhibition effective range", "n_analyzed": "", "ci_or_error": "", "text_access": "abstract_only", "n_definition": "single VIP optogenetic activation experiments", "scope_region": "visual cortex", "study_system": "mouse visual cortex", "taxonomic_level": "VIP interneurons", "scope_population": "VIP interneurons and their SOM/pyramidal targets", "value_source_sentence": "We find that VIPs break open a hole in blanket inhibition with an effective range of ~120 μm in lateral cortical space where excitatory activity can propagate.", "experimental_conditions": "in vivo two-photon optogenetics of individual VIP interneurons" }, { "n": 0, "doi": "10.1016/j.neuron.2023.12.013", "value": "Synaptic weights specifically tuned to response similarity", "method": "in vivo recording + connectivity measurement", "metric": "PV inhibitory weight tuning by response similarity", "n_analyzed": "", "ci_or_error": "", "text_access": "fulltext", "n_definition": "in vivo visual responses + synaptic connectivity measurements", "scope_region": "primary visual cortex", "study_system": "mouse primary visual cortex", "taxonomic_level": "PV+ interneurons", "scope_population": "PV+ to pyramidal neuron connections", "value_source_sentence": "Individual PV+ cells strongly inhibit those pyramidal cells that provide them with strong excitation and share their visual selectivity.", "experimental_conditions": "in vivo, combined visual response and connectivity measurement" }, { "n": 0, "doi": "10.1093/cercor/bhx276", "value": "Nonselective connections with both projection subtypes", "method": "paired intracellular recordings", "metric": "PV/FS connectivity selectivity for pyramidal subtypes", "n_analyzed": "", "ci_or_error": "", "text_access": "fulltext", "n_definition": "paired recordings between identified cell types", "scope_region": "frontal cortex layer 5", "study_system": "rat frontal cortex layer 5", "taxonomic_level": "FS/PV cells", "scope_population": "FS cells to CPn and CCS pyramidal subtypes", "value_source_sentence": "FS cells made nonselective connections with both projection subtypes.", "experimental_conditions": "in vitro paired recordings, identified projection subtypes" }, { "n": 0, "doi": "10.1523/jneurosci.5158-11.2012", "value": "85-114 μm Gaussian sigma, comparable for all types", "method": "multiple intracellular recordings", "metric": "Connectivity spread FS vs excitatory cells", "n_analyzed": "", "ci_or_error": "", "text_access": "abstract_only", "n_definition": "multiple intracellular recording distance-connectivity mapping", "scope_region": "primary auditory cortex", "study_system": "mouse primary auditory cortex", "taxonomic_level": "FS, non-FS, and excitatory neurons", "scope_population": "all cell types in thalamorecipient layer", "value_source_sentence": "The spread of connectivity, parameterized by Gaussian fits to the data, was comparable for all cell types, ranging from 85 to 114 μm.", "experimental_conditions": "in vitro, multiple intracellular recordings" } ], "comparison_id": "blanket-vs-selective-inhibition-evidence", "comparison_name": "Blanket vs Selective Inhibition: Evidence Across Studies", "comparison_type": "cross-study conflict", "what_it_reveals": "The evidence reveals a nuanced picture where PV connectivity is anatomically dense but functionally tuned. Connection probability may be high (blanket-like) but synaptic weights are modulated by activity and co-tuning, creating selective inhibition within a framework of dense connectivity. Whether PV inhibition appears selective or nonselective may depend on the level of analysis (connectivity vs synaptic weight), brain region, and experimental conditions.", "homogeneity_check": { "caveats": [ "Different brain regions (visual, auditory, frontal cortex)", "Different species (mouse, rat)", "Different experimental approaches (in vivo vs in vitro)", "Blanket/selective distinction measured at different levels: connectivity rate vs synaptic weight" ], "n_definition_uniform": "false", "scope_region_uniform": "false", "taxonomic_level_uniform": "true", "scope_population_uniform": "false" }, "suggested_plot_type": "heatmap" }, "section_id": "section_07_evidence_package", "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV/blob/df9fc7e8d455b084152c9d713558dae0013cef21/evidence/section_07_evidence_package.json", "target_ref": "wiki_page:computationalreviewpv-07", "review_repo": "ComputationalReviewPV", "section_ref": "wiki_page:computationalreviewpv-07", "source_path": "evidence/section_07_evidence_package.json", "source_refs": [ "paper:paper-0a3cf7627c63", "paper:paper-7ab8027f125a", "paper:paper-aa18bb0de98d", "paper:paper-f74b0ebd1b13" ], "section_title": "Local Circuit Motifs: Perisomatic Inhibition, Feedback, and Feedforward", "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_07_evidence_package.json", "commit_sha": "df9fc7e8d455b084152c9d713558dae0013cef21", "created_by": "persona-jerome-lecoq-gbo-neuroscience", "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewPV" }