Version history

{
  "scope": "mouse PFC-MD circuit; biologically-constrained spiking/rate network modeling fit against electrophysiology of mice performing context-dependent decision tasks",
  "claim_text": "Biologically-constrained PFC-MD network models show that adding a feedforward MD module to a recurrent PFC increases robustness to low cue signal-to-noise, enhances working-memory persistence, and enables rapid context switching; incorporating genetically-identified thalamocortical projections and interneuron cell types reproduces key neurophysiological features in mice, providing a mechanistic and geometric account of MD-mediated regulation of cortical attractor stability for cognitive flexibility.",
  "raw_fields": {
    "n": 0,
    "doi": "10.1038/s41467-025-58011-1",
    "claim": "Biologically-constrained PFC-MD network models show that adding a feedforward MD module to a recurrent PFC increases robustness to low cue signal-to-noise, enhances working-memory persistence, and enables rapid context switching; incorporating genetically-identified thalamocortical projections and interneuron cell types reproduces key neurophysiological features in mice, providing a mechanistic and geometric account of MD-mediated regulation of cortical attractor stability for cognitive flexibility.",
    "cite_key": "Zhang2025c",
    "evidence": "Incorporating genetically identified thalamocortical connectivity and interneuron cell types into the model replicates key neurophysiological findings in task-performing animals. Our model reveals computational mechanisms and geometric interpretations of MD in regulating cue uncertainty and context switching to enable cognitive flexibility.",
    "effect_size": "",
    "text_access": "fulltext",
    "study_system": "mouse PFC-MD circuit; biologically-constrained spiking/rate network modeling fit against electrophysiology of mice performing context-dependent decision tasks",
    "argument_role": "supporting",
    "replication_status": "single_lab",
    "claim_source_sentence": "We show that the addition of a feedforward MD structure to the recurrent PFC increases robustness to low cueing signal-to-noise ratio, enhances working memory, and enables rapid context switching.",
    "source_provenance_status": "ok",
    "replication_evidence_dois": [],
    "effect_size_source_sentence": null
  },
  "section_id": "section_10",
  "source_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_10_evidence_package.json",
  "effect_size": "",
  "review_repo": "ComputationalReviewRecurrence",
  "section_ref": "wiki_page:computationalreviewrecurrence-10-persistent-activity",
  "source_kind": "review_finding",
  "source_path": "evidence/section_10_evidence_package.json",
  "source_refs": [
    "paper:paper-2603d6e67df4"
  ],
  "source_span": "We show that the addition of a feedforward MD structure to the recurrent PFC increases robustness to low cueing signal-to-noise ratio, enhances working memory, and enables rapid context switching.",
  "study_system": "mouse PFC-MD circuit; biologically-constrained spiking/rate network modeling fit against electrophysiology of mice performing context-dependent decision tasks",
  "evidence_refs": [
    {
      "ref": "paper:paper-2603d6e67df4"
    }
  ],
  "section_title": "10. Physiological signature II — persistent activity and attractor dynamics supported by E→E recurrence (delay-period activity in mouse PFC/ALM, working memory, head-direction)",
  "source_policy": {
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    "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": "Incorporating genetically identified thalamocortical connectivity and interneuron cell types into the model replicates key neurophysiological findings in task-performing animals. Our model reveals computational mechanisms and geometric interpretations of MD in regulating cue uncertainty and context switching to enable cognitive flexibility.",
  "review_bundle_ref": "analysis_bundle:ab-d9c479db9be9",
  "replication_status": "single_lab",
  "review_package_ref": "analysis_bundle:ab-d9c479db9be9",
  "source_artifact_ref": "wiki_page:computationalreviewrecurrence-10-persistent-activity",
  "origin_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence/blob/79ce062d54a924ce05953ec90aa9d26044d2b48f/evidence/section_10_evidence_package.json",
  "commit_sha": "79ce062d54a924ce05953ec90aa9d26044d2b48f",
  "created_by": "persona-jerome-lecoq-gbo-neuroscience",
  "repository_url": "https://github.com/AllenNeuralDynamics/ComputationalReviewRecurrence"
}