- raw_fields
{
"n": null,
"doi": "10.1101/2025.11.20.689599",
"claim": "Applied to electrophysiological recordings from the anterior lateral motor cortex (ALM) and motor thalamus in mice performing a delayed response task, our model demonstrates that perturbations of res…",
"cite_key": "PereiraObilinovic2025",
"evidence": "Most behaviors involve neural dynamics in high-dimensional activity spaces. A common approach is to extract dimensions that capture task-related variability, such as those separating stimuli or choices, yielding low-dimensional, task-aligned neural activity subspaces (\"coding dimensions\"). However, whether these dimensions actively drive decisions or merely reflect underlying computations remains unclear. Moreover, neural activity outside these coding subspaces (\"residual dimensions\") is often i...",
"effect_size": "Adding these dimensions yielded only a modest increase in explained variance, from 90% to 97% as the total dimensionality increased from 3 to 12 (), but this small variance gain was accompanied by a substantial improvement in alignment with the empirical task axes (and).",
"text_access": "fulltext",
"study_system": "mouse; motor cortex, ALM; computational model; bioRxiv : the preprint server for biology",
"argument_role": "supporting",
"replication_status": "single_study",
"claim_source_sentence": "Applied to electrophysiological recordings from the anterior lateral motor cortex (ALM) and motor thalamus in mice performing a delayed response task, our model demonstrates that perturbations of residual dimensions reliably alter behavioral choices, whereas perturbations of the choice dimension, which strongly encodes the animal's upcoming decision, are largely ineffective.",
"source_provenance_status": "ok",
"replication_evidence_dois": [],
"claim_rewritten_from_source": true,
"effect_size_source_sentence": "Adding these dimensions yielded only a modest increase in explained variance, from 90% to 97% as the total dimensionality increased from 3 to 12 (), but this small variance gain was accompanied by a substantial improvement in alignment with the empirical task axes (and)."
}- effect_size
Adding these dimensions yielded only a modest increase in explained variance, from 90% to 97% as the total dimensionality increased from 3 to 12 (), but this small variance gain was accompanied by a substantial improvement in alignment with the empirical task axes (and).
- source_refs
[
"paper:1fb5c98a-58de-4c04-8245-dec7bc6fa359"
]
- source_span
Applied to electrophysiological recordings from the anterior lateral motor cortex (ALM) and motor thalamus in mice performing a delayed response task, our model demonstrates that perturbations of residual dimensions reliably alter behavioral choices, whereas perturbations of the choice dimension, which strongly encodes the animal's upcoming decision, are largely ineffective.
- evidence_refs
[
{
"ref": "paper:1fb5c98a-58de-4c04-8245-dec7bc6fa359"
}
]- 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
Most behaviors involve neural dynamics in high-dimensional activity spaces. A common approach is to extract dimensions that capture task-related variability, such as those separating stimuli or choices, yielding low-dimensional, task-aligned neural activity subspaces ("coding dimensions"). However, whether these dimensions actively drive decisions or merely reflect underlying computations remains unclear. Moreover, neural activity outside these coding subspaces ("residual dimensions") is often i...