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Record W3045086389 · doi:10.1093/cercor/bhaa186

Distributed Motor Control of Limb Movements in Rat Motor and Somatosensory Cortex: The Sensorimotor Amalgam Revisited

2020· article· en· W3045086389 on OpenAlexaff
Andrew C Halley, Mary K. L. Baldwin, Dylan F. Cooke, Mackenzie Englund, Leah Krubitzer

Bibliographic record

VenueCerebral Cortex · 2020
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsSimon Fraser University
FundersNational Institutes of HealthNational Eye InstituteJames S. McDonnell Foundation
KeywordsForelimbSomatosensory systemHindlimbNeuroscienceMotor cortexNeocortexMicrostimulationMotor controlStimulationAnatomyPsychologyBiology

Abstract

fetched live from OpenAlex

Which areas of the neocortex are involved in the control of movement, and how is motor cortex organized across species? Recent studies using long-train intracortical microstimulation demonstrate that in addition to M1, movements can be elicited from somatosensory regions in multiple species. In the rat, M1 hindlimb and forelimb movement representations have long been thought to overlap with somatosensory representations of the hindlimb and forelimb in S1, forming a partial sensorimotor amalgam. Here we use long-train intracortical microstimulation to characterize the movements elicited across frontal and parietal cortex. We found that movements of the hindlimb, forelimb, and face can be elicited from both M1 and histologically defined S1 and that representations of limb movement types are different in these two areas. Stimulation of S1 generates retraction of the contralateral forelimb, while stimulation of M1 evokes forelimb elevation movements that are often bilateral, including a rostral region of digit grasping. Hindlimb movement representations include distinct regions of hip flexion and hindlimb retraction evoked from S1 and hip extension evoked from M1. Our data indicate that both S1 and M1 are involved in the generation of movement types exhibited during natural behavior. We draw on these results to reconsider how sensorimotor cortex evolved.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.922
Threshold uncertainty score0.710

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.228
Teacher spread0.209 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations67
Published2020
Admission routes1
Has abstractyes

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