Details
- scope
- spiking neural network model of L2/3 cortex, neuromorphic hardware (TrueNorth)
- section_id
- section_13
- source_url
- https://github.com/AllenNeuralDynamics/ComputationalReviewVIP/blob/95e761177f7d2ec565983d3307c14ec238f9677c/evidence/section_13_evidence_package.json
- review_repo
- ComputationalReviewVIP
- section_ref
- wiki_page:computationalreviewvip-13-conclusion
- source_kind
- review_finding
- source_path
- evidence/section_13_evidence_package.json
- study_system
- spiking neural network model of L2/3 cortex, neuromorphic hardware (TrueNorth)
- section_title
- Synthesis and Conclusion: Reassessing the Canonical VIP Disinhibitor
- evidence_summary
- Authors built a 4-interneuron-type spiking network and embedded sWTA, gain control, disinhibition, and normalization motifs onto neuromorphic hardware to improve vision-transformer performance.
- review_bundle_ref
- analysis_bundle:ab-2ce40c33e827
- replication_status
- replicated_independent
- review_package_ref
- analysis_bundle:ab-2ce40c33e827
- source_artifact_ref
- wiki_page:computationalreviewvip-13-conclusion
- origin_url
- https://github.com/AllenNeuralDynamics/ComputationalReviewVIP/blob/95e761177f7d2ec565983d3307c14ec238f9677c/evidence/section_13_evidence_package.json
- commit_sha
- 95e761177f7d2ec565983d3307c14ec238f9677c
- created_by
- persona-jerome-lecoq-gbo-neuroscience
- repository_url
- https://github.com/AllenNeuralDynamics/ComputationalReviewVIP
Raw fields (6)
- claim_text
A biologically constrained spiking model of layer 2/3 incorporating four canonical interneuron classes (PV, SST, VIP, LAMP5) implements soft winner-take-all dynamics, with VIP transiently disinhibiting SST and LAMP5 providing global gain normalization.
- raw_fields
{ "n": null, "id": "cluster_11_finding_01", "doi": "10.1073/pnas.2504164122", "pmid": "41055996", "year": "2025", "claim": "A biologically constrained spiking model of layer 2/3 incorporating four canonical interneuron classes (PV, SST, VIP, LAMP5) implements soft winner-take-all dynamics, with VIP transiently disinhibiting SST and LAMP5 providing global gain normalization.", "pmcid": "PMC12541343", "title": "Biologically grounded neocortex computational primitives implemented on neuromorphic hardware improve vision transformer performance.", "authors": "Iqbal A, Mahmood H, Stuart GJ, Fishell G, Honnuraiah S.", "journal": "Proceedings of the National Academy of Sciences of the United States of America", "cite_key": "Iqbal2025", "evidence": "Authors built a 4-interneuron-type spiking network and embedded sWTA, gain control, disinhibition, and normalization motifs onto neuromorphic hardware to improve vision-transformer performance.", "effect_size": null, "text_access": "fulltext", "study_system": "spiking neural network model of L2/3 cortex, neuromorphic hardware (TrueNorth)", "_source_cluster": "cluster_11_computational_models", "replication_status": "replicated_independent", "_source_cluster_index": 0, "claim_source_sentence": "In sensory cortex, pyramidal neurons integrate bottom–up and top–down signals under the modulatory influence of key interneuron classes: parvalbumin (PV), somatostatin (SST), vasoactive intestinal peptide (VIP), and LAMP5-expressing neurogliaform cells each of which mediates distinct computational roles including gain control, disinhibition, and normalization respectively ( 6 – 12 ).", "replication_evidence_dois": [ "10.1371/journal.pcbi.1013469", "10.1371/journal.pcbi.1012036", "10.1093/cercor/bhae378", "10.1007/s00422-021-00894-6", "10.7554/elife.77594" ], "effect_size_source_sentence": null }- source_refs
[ "paper:paper-733c0535ffcd" ]
- source_span
In sensory cortex, pyramidal neurons integrate bottom–up and top–down signals under the modulatory influence of key interneuron classes: parvalbumin (PV), somatostatin (SST), vasoactive intestinal peptide (VIP), and LAMP5-expressing neurogliaform cells each of which mediates distinct computational roles including gain control, disinhibition, and normalization respectively ( 6 – 12 ).
- evidence_refs
[ { "ref": "paper:paper-733c0535ffcd" } ]- 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": "95e761177f7d2ec565983d3307c14ec238f9677c", "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewVIP" }