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Record W2802836380 · doi:10.1093/cercor/bhy104

Independent Early and Late Sensory Processes for Proprioceptive Integration When Planning a Step

2018· article· en· W2802836380 on OpenAlexaff
Anahid H. Saradjian, Normand Teasdale, Jean Blouin, Laurence Mouchnino

Bibliographic record

VenueCerebral Cortex · 2018
Typearticle
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversité LavalHôpital du Saint-Sacrement
FundersCentre National d’Etudes Spatiales
KeywordsSomatosensory systemSensory systemStimulus (psychology)Somatosensory evoked potentialNeurosciencePosterior parietal cortexSensory processingPsychologyProprioceptionCognitive psychology

Abstract

fetched live from OpenAlex

Somatosensory inputs to the cortex undergo an early and a later stage of processing which are characterized by an early and a late somatosensory evoked potentials (SEP). The early response is highly representative of the stimulus characteristics whereas the late response reflects a more integrative, task specific, stage of sensory processing. We hypothesized that the later processing stage is independent of the early processing stage. We tested the prediction that a reduction of the first volley of input to the cortex should not prevent the increase of the late SEP. Using the sensory interference phenomenon, we halved the amplitude of the early response to somatosensory input of the ankle joints (evoked by vibration) when participants either planned a step forward or remained still. Despite the initial cortical response to the vibration being massively decreased in both tasks, the late response was still enhanced during step planning. Source localization indicated the posterior parietal cortex (PPC) as the likely origin of the late response modulation. Overall these results support the dissociation between the processes underlying the early and late SEP. The later processing stage could involve both direct and indirect thalamic connections to PPC which bypass the postcentral somatosensory cortex.

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)0.000
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 score0.564
Threshold uncertainty score0.406

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.276
Teacher spread0.234 · 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

Citations14
Published2018
Admission routes1
Has abstractyes

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