Details

kind
infographic
prompt
The nature of SST-mediated inhibition (divisive vs subtractive) is contested and appears to depend on experimental conditions, challenging the simple classification of SST as subtractive inhibitors.
provider
other
section_id
section_07_evidence_package
source_url
https://github.com/AllenNeuralDynamics/ComputationalReviewSST/blob/89b7e9787cd90e942b0adb531d549af3ddad30f1/evidence/section_07_evidence_package.json
target_ref
wiki_page:computationalreviewsst-07
review_repo
ComputationalReviewSST
section_ref
wiki_page:computationalreviewsst-07
source_path
evidence/section_07_evidence_package.json
section_title
Circuit Motifs and Dendritic Computation
generation_status
complete
review_bundle_ref
analysis_bundle:ab-8466d095488a
origin_url
https://github.com/AllenNeuralDynamics/ComputationalReviewSST/blob/89b7e9787cd90e942b0adb531d549af3ddad30f1/evidence/section_07_evidence_package.json
commit_sha
89b7e9787cd90e942b0adb531d549af3ddad30f1
created_by
persona-jerome-lecoq-gbo-neuroscience
repository_url
https://github.com/AllenNeuralDynamics/ComputationalReviewSST
Raw fields (3)
raw_fields
{
  "papers": [
    {
      "doi": "10.1038/nature11347",
      "value": "Subtractive (offset change)",
      "method": "in vivo optogenetics and electrophysiology",
      "metric": "Type of inhibition by SST activation",
      "cite_key": "Wilson2012",
      "condition": "SST activation alone",
      "study_system": "mouse V1",
      "value_source_sentence": "dendrite-targeting, somatostatin-expressing (SOM) neurons primarily change response offset"
    },
    {
      "doi": "10.3389/fncir.2019.00040",
      "value": "Divisive (gain change)",
      "method": "in vivo optogenetics",
      "metric": "Type of inhibition by simultaneous SST+PV activation",
      "cite_key": "Ingram2019",
      "condition": "SST + PV simultaneous activation",
      "study_system": "mouse V1",
      "value_source_sentence": "Divisive Inhibition Prevails During Simultaneous Optogenetic Activation of PV and SST interneurons"
    },
    {
      "doi": "10.1152/jn.00732.2015",
      "value": "Context-dependent (both possible)",
      "method": "recurrent network modeling",
      "metric": "Model prediction for SST inhibition type",
      "cite_key": "LitwinKumar2016",
      "condition": "varies with connectivity and tuning",
      "study_system": "computational model",
      "value_source_sentence": "study the roles of each interneuron subtype in disinhibition, surround suppression, and subtractive or divisive modulation of orientation tuning curves"
    },
    {
      "doi": "10.7554/elife.99808",
      "value": "Decoupled (multiple classes resolve trade-off)",
      "method": "analytical and simulation",
      "metric": "Stability-gain trade-off with multiple IN classes",
      "cite_key": "Bos2025",
      "condition": "multiple interneuron classes",
      "study_system": "computational model",
      "value_source_sentence": "In cortical models with a single inhibitory neuron class, network stabilization and gain control work in opposition to one another"
    }
  ],
  "comparison_id": "gain-control-type-across-studies",
  "comparison_name": "Divisive vs Subtractive Inhibition by SST Interneurons Across Studies",
  "comparison_type": "cross-study conflict",
  "what_it_reveals": "The nature of SST-mediated inhibition (divisive vs subtractive) is contested and appears to depend on experimental conditions, challenging the simple classification of SST as subtractive inhibitors.",
  "homogeneity_check": {
    "caveats": [
      "Mix of experimental and computational studies",
      "Different SST activation protocols",
      "Different metrics for divisive vs subtractive"
    ],
    "comparable": false
  },
  "suggested_plot_type": "grouped bar"
}
source_refs
[
  "paper:paper-00de1a2c593e",
  "paper:paper-0539949fe271",
  "paper:paper-8f25714ab7fe",
  "paper:paper-cf0d183b1c6d"
]
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": "89b7e9787cd90e942b0adb531d549af3ddad30f1",
  "source_repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewSST"
}

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