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Record W1502745763 · doi:10.1002/cne.23790

Differential modification of cortical and thalamic projections to cat primary auditory cortex following early‐ and late‐onset deafness

2015· article· en· W1502745763 on OpenAlexafffund
Nicole Chabot, Blake E. Butler, Stephen G. Lomber

Bibliographic record

VenueThe Journal of Comparative Neurology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicTactile and Sensory Interactions
Canadian institutionsWestern University
FundersCanadian Institutes of Health Research
KeywordsBiologyAuditory cortexNeuroscienceThalamusCortex (anatomy)Cerebral cortexDifferential (mechanical device)AudiologyMedicine

Abstract

fetched live from OpenAlex

Following sensory deprivation, primary somatosensory and visual cortices undergo crossmodal plasticity, which subserves the remaining modalities. However, controversy remains regarding the neuroplastic potential of primary auditory cortex (A1). To examine this, we identified cortical and thalamic projections to A1 in hearing cats and those with early- and late-onset deafness. Following early deafness, inputs from second auditory cortex (A2) are amplified, whereas the number originating in the dorsal zone (DZ) decreases. In addition, inputs from the dorsal medial geniculate nucleus (dMGN) increase, whereas those from the ventral division (vMGN) are reduced. In late-deaf cats, projections from the anterior auditory field (AAF) are amplified, whereas those from the DZ decrease. Additionally, in a subset of early- and late-deaf cats, area 17 and the lateral posterior nucleus (LP) of the visual thalamus project concurrently to A1. These results demonstrate that patterns of projections to A1 are modified following deafness, with statistically significant changes occurring within the auditory thalamus and some cortical areas. Moreover, we provide anatomical evidence for small-scale crossmodal changes in projections to A1 that differ between early- and late-onset deaf animals, suggesting that potential crossmodal activation of primary auditory cortex differs depending on the age of deafness onset.

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 score0.925
Threshold uncertainty score0.261

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 head0.089
GPT teacher head0.340
Teacher spread0.251 · 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

Citations58
Published2015
Admission routes2
Has abstractyes

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