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Record W1982007422 · doi:10.1152/jn.00921.2006

Long-Lasting, Context-Dependent Modification of Stepping in the Cat After Repeated Stumbling-Corrective Responses

2006· article· en· W1982007422 on OpenAlexaff
David A. McVea, K. G. Pearson

Bibliographic record

VenueJournal of Neurophysiology · 2006
Typearticle
Languageen
FieldNeuroscience
TopicMotor Control and Adaptation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsContext (archaeology)NeurosciencePsychologyCommunicationCognitive psychologyBiology

Abstract

fetched live from OpenAlex

A consistent feature of animal locomotion is the capacity to maintain stable movements in changing environments. Here we describe long-term modification of the swing movement of the hind leg in cats in response to repeatedly impeding the movement of the leg. While studying phase transitions in the hind legs, we discovered that repetitively evoking the stumbling-corrective reaction led to long-lasting increases in knee flexion and step height during swing to avoid the impediment. These increases were apparent after nearly 20 stimuli and maximal after about 120 stimuli and, in some animals, they persisted for > or =24 h after presentation of the stimuli. Furthermore, these long-lasting changes were context dependent and did not generalize to other environments; when walking was observed in an environment distinct from that used in training, the hind-limb kinematics returned to normal. To gain insight into what regions of the nervous system might be involved in this long-term modification, we examined the changes in stepping in decerebrate cats after multiple perturbed steps. In this situation, there was a short-term increase in step height, although this increase was smaller than that evoked in intact animals and persisted for <1 min after termination of the stimuli. Thus induction of the long-term increase in step height requires the forebrain. We propose that the conditioned change in leg movement is related to a general ability of animals to adapt locomotor movements to new features of the environment.

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 score0.960
Threshold uncertainty score0.262

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 head0.042
GPT teacher head0.282
Teacher spread0.240 · 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

Citations39
Published2006
Admission routes1
Has abstractyes

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