Version history

{
  "scope": "Distinct recruitment of feedforward and recurrent pathways across higher-order areas of mouse visual cortex.",
  "claim_text": "Mouse HVAs (V1, LM, AL, PM, AM) — area-specific E↔I but excitatory inputs into interneurons differ by recruitment, not unitary E synaptic properties.",
  "raw_fields": {
    "n": null,
    "doi": "10.1016/j.cub.2021.09.042",
    "claim": "Mouse HVAs (V1, LM, AL, PM, AM) — area-specific E↔I but excitatory inputs into interneurons differ by recruitment, not unitary E synaptic properties.",
    "cite_key": "Li2021a",
    "evidence": "Cortical visual processing transforms features of the external world into increasingly complex and specialized neuronal representations. These transformations arise in part through target-specific routing of information; however, within-area computations may also contribute to area-specific function. Here, we sought to determine whether higher order visual cortical areas lateromedial (LM), anterolateral (AL), posteromedial (PM), and anteromedial (AM) have specialized anatomical and physiological properties by using a combination of whole-cell recordings and optogenetic stimulation of primary visual cortex (V1) axons in vitro. We discovered area-specific differences in the strength of recruitment of interneurons through feedforward and recurrent pathways, as well as differences in cell-intrinsic properties and interneuron densities. These differences were most striking when comparing across medial and lateral areas, suggesting that these areas have distinct profiles for net excitability and integration of V1 inputs. Thus, cortical areas are not defined simply by the information they receive but also by area-specific circuit properties that enable specialized filtering of these",
    "effect_size": null,
    "text_access": "fulltext",
    "study_system": "Distinct recruitment of feedforward and recurrent pathways across higher-order areas of mouse visual cortex.",
    "argument_role": "supporting",
    "replication_status": null,
    "claim_source_sentence": "When we quantified the probability of connection between pyramidal cells and interneurons across mouse higher visual areas, we found significant differences across areas — but differences in strength and short-term plasticity of connectivity between pyramidal cells and interneurons cannot explain differences in local excitatory inputs onto interneurons across different HVAs.",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": null
  },
  "section_id": "section_03",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_03_evidence_package.json",
  "effect_size": null,
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-03-paired-recording",
  "source_kind": "review_finding",
  "source_path": "evidence/section_03_evidence_package.json",
  "source_refs": [
    "paper:paper-21937e5a070f"
  ],
  "source_span": "When we quantified the probability of connection between pyramidal cells and interneurons across mouse higher visual areas, we found significant differences across areas — but differences in strength and short-term plasticity of connectivity between pyramidal cells and interneurons cannot explain differences in local excitatory inputs onto interneurons across different HVAs.",
  "study_system": "Distinct recruitment of feedforward and recurrent pathways across higher-order areas of mouse visual cortex.",
  "evidence_refs": [
    {
      "ref": "paper:paper-21937e5a070f"
    }
  ],
  "section_title": "3. Paired-recording evidence in mouse — connection probabilities and synaptic strengths between pyramidal cells within a column, layer-by-layer (Lefort, Petersen, Adesnik, Feldmeyer, Markram-style work in mouse)",
  "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"
  },
  "evidence_summary": "Cortical visual processing transforms features of the external world into increasingly complex and specialized neuronal representations. These transformations arise in part through target-specific routing of information; however, within-area computations may also contribute to area-specific function. Here, we sought to determine whether higher order visual cortical areas lateromedial (LM), anterolateral (AL), posteromedial (PM), and anteromedial (AM) have specialized anatomical and physiological properties by using a combination of whole-cell recordings and optogenetic stimulation of primary visual cortex (V1) axons in vitro. We discovered area-specific differences in the strength of recruitment of interneurons through feedforward and recurrent pathways, as well as differences in cell-intrinsic properties and interneuron densities. These differences were most striking when comparing across medial and lateral areas, suggesting that these areas have distinct profiles for net excitability and integration of V1 inputs. Thus, cortical areas are not defined simply by the information they receive but also by area-specific circuit properties that enable specialized filtering of these",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "unevaluated",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-03-paired-recording",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_03_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}