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A Cellular Mechanism for the Transformation of a Sensory Input into a Motor Command

2000· article· en· W2117720530 on OpenAlexaff
Gonzalo Viana Di Prisco, Édouard Pearlstein, D. Le Ray, Richard Robitaille, Réjean Dubuc

Bibliographic record

VenueJournal of Neuroscience · 2000
Typearticle
Languageen
FieldNeuroscience
TopicNeurobiology and Insect Physiology Research
Canadian institutionsUniversité du Québec à MontréalUniversité de Montréal
FundersMedical Research Council
KeywordsDepolarizationNeuroscienceSensory systemBAPTAStimulationNMDA receptorIntracellularChemistryNeuronBiophysicsReceptorBiologyCell biology

Abstract

fetched live from OpenAlex

The initiation and control of locomotion largely depend on processing of sensory inputs. The cellular bases of locomotion have been extensively studied in lampreys where reticulospinal (RS) neurons constitute the main descending system activating and controlling the spinal locomotor networks. Ca(2+) imaging and intracellular recordings were used to study the pattern of activation of RS neurons in response to cutaneous stimulation. Pressure applied to the skin evoked a linear input/output relationship in RS neurons until a threshold level, at which a depolarizing plateau was induced, the occurrence of which was associated with the onset of swimming activity in a semi-intact preparation. The occurrence of a depolarizing plateau was abolished by blocking the NMDA receptors that are located on RS cells. Moreover, the depolarizing plateaus were accompanied by a rise in [Ca(2+)](i), and an intracellular injection of the Ca(2+) chelator BAPTA into single RS cells abolished the plateaus, suggesting that the latter are Ca(2+) dependent and rely on intrinsic properties of RS cells. The plateaus were shown to result from the activation of a Ca(2+)-activated nonselective cation current that maintains the cell in a depolarized state. It is concluded that this intrinsic property of the RS neuron is then responsible for the transformation of an incoming sensory signal into a motor command that is then forwarded to the spinal locomotor networks.

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)0.001
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 score0.011
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.048
GPT teacher head0.303
Teacher spread0.255 · 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

Citations116
Published2000
Admission routes1
Has abstractyes

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