- claim_text
Most L6 excitatory neurons form rare connections to other L6 excitatory neurons, while the dominant output of an L6 sublamina is translaminar inhibition via parvalbumin interneurons projecting toward the pia — calling for revision of the canonical six-layer microcircuit.
- raw_fields
{
"n": 0,
"doi": "10.1016/j.celrep.2019.08.048",
"claim": "Most L6 excitatory neurons form rare connections to other L6 excitatory neurons, while the dominant output of an L6 sublamina is translaminar inhibition via parvalbumin interneurons projecting toward the pia — calling for revision of the canonical six-layer microcircuit.",
"cite_key": "Frandolig2019",
"evidence": "Synaptic-connectivity mapping in mouse L6; identification of interlaminar PV interneurons receiving thalamocortical and local L6 input.",
"effect_size": "Rare E→E L6 connections; dominant L6 inhibitory translaminar output.",
"text_access": "abstract_only",
"study_system": "mouse neocortex layer 6; circuit mapping and paired recordings",
"argument_role": "supporting",
"replication_status": "replication_unknown",
"claim_source_sentence": "However, excitatory neurons in layer 6 (L6), a layer whose functional organization is poorly understood, form relatively rare synaptic connections with other cortical excitatory neurons. Here, we show that the vast majority of parvalbumin inhibitory neurons in a sublamina within L6 send axons through the cortical layers toward the pia.",
"source_provenance_status": "non_substring_match",
"replication_evidence_dois": [],
"effect_size_source_sentence": null
}- source_refs
[
"paper:paper-ab9407c26ea7"
]
- source_span
However, excitatory neurons in layer 6 (L6), a layer whose functional organization is poorly understood, form relatively rare synaptic connections with other cortical excitatory neurons. Here, we show that the vast majority of parvalbumin inhibitory neurons in a sublamina within L6 send axons through the cortical layers toward the pia.
- evidence_refs
[
{
"ref": "paper:paper-ab9407c26ea7"
}
]- 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"
}