Details
- scope
- Mouse V1 multi-interneuron network model (theoretical, connectivity from experiment)
- section_id
- section_09
- source_url
- https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_09_evidence_package.json
- effect_size
- qualitative analytic conditions for stability and disinhibition; novel predictions for optogenetic manipulations
- review_repo
- ComputationalReviewRecurrence
- section_ref
- wiki_page:computationalreviewrecurrence-09-amplification-isn
- source_kind
- review_finding
- source_path
- evidence/section_09_evidence_package.json
- source_span
- Our theory describes conditions under which the activity of such networks is stable and how perturbations of distinct neuronal subtypes recruit changes in activity through recurrent synaptic projections.
- study_system
- Mouse V1 multi-interneuron network model (theoretical, connectivity from experiment)
- section_title
- 9. Physiological signature I — recurrent amplification of weak inputs in mouse cortex; balanced-amplification regimes; ISN operation
- evidence_summary
- Rate-network theory and simulations of cortical circuits with experimentally measured PV/SOM/VIP connectivity from mouse V1; analysis of stability, surround suppression, and tuning curve modulation.
- review_bundle_ref
- analysis_bundle:ab-d9c479db9be9
- replication_status
- independently_replicated
- review_package_ref
- analysis_bundle:ab-d9c479db9be9
- source_artifact_ref
- wiki_page:computationalreviewrecurrence-09-amplification-isn
- 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
Raw fields (5)
- claim_text
In multi-interneuron (PV, SOM, VIP) recurrent network models with mouse V1 connectivity, recurrent excitatory dynamics require inhibitory stabilization; perturbations of distinct interneuron subtypes recruit specific changes in network activity that reflect strong E→E recurrent coupling.
- raw_fields
{ "n": 0, "doi": "10.1152/jn.00732.2015", "claim": "In multi-interneuron (PV, SOM, VIP) recurrent network models with mouse V1 connectivity, recurrent excitatory dynamics require inhibitory stabilization; perturbations of distinct interneuron subtypes recruit specific changes in network activity that reflect strong E→E recurrent coupling.", "cite_key": "LitwinKumar2016", "evidence": "Rate-network theory and simulations of cortical circuits with experimentally measured PV/SOM/VIP connectivity from mouse V1; analysis of stability, surround suppression, and tuning curve modulation.", "effect_size": "qualitative analytic conditions for stability and disinhibition; novel predictions for optogenetic manipulations", "text_access": "abstract_only", "study_system": "Mouse V1 multi-interneuron network model (theoretical, connectivity from experiment)", "argument_role": "supporting", "replication_status": "independently_replicated", "claim_source_sentence": "Our theory describes conditions under which the activity of such networks is stable and how perturbations of distinct neuronal subtypes recruit changes in activity through recurrent synaptic projections.", "source_provenance_status": "non_substring_match", "replication_evidence_dois": [ "10.7554/eLife.49967", "10.7554/eLife.54875" ], "effect_size_source_sentence": null }- source_refs
[ "paper:paper-8f25714ab7fe" ]
- evidence_refs
[ { "ref": "paper:paper-8f25714ab7fe" } ]- 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" }