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Updating neural representations of objects during walking

2010· article· en· W1612931264 on OpenAlexafffund
K. G. Pearson, Rod Gramlich

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2010
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsNeurosciencePosterior parietal cortexEfference copySensory systemProprioceptionComputer scienceBody schemaPsychologyPerception

Abstract

fetched live from OpenAlex

In quadrupeds, a unique form of memory is used to guide the hind legs over barriers that have already been stepped over by the forelegs. This memory is very long-lasting (many minutes), incorporates precise information about the size and position of the barrier relative to the hind legs, and is updated as the animal steps sequentially across a barrier. Recent findings from electrophysiological and lesion studies have revealed that neuronal systems in the parietal cortex are necessary for establishing the long-lasting feature of the memory and may be involved in representing the current position of the barrier relative to the moving body. We hypothesize that the latter involves the modulation of activity in neuronal systems in the posterior parietal cortex by efference copy signals of motor commands for stepping and by sensory signals from muscle proprioceptors. We propose that motor pattern generation for walking occurs within a framework of a body schema that constantly informs pattern generating networks about the geometry of the body and the location of near objects relative to the body.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.073
Threshold uncertainty score0.208

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.095
GPT teacher head0.348
Teacher spread0.252 · 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

Citations26
Published2010
Admission routes2
Has abstractyes

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