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Record W4400273353 · doi:10.1016/j.ynirp.2024.100213

Cortical thickness differences between hearing and perinatally deaf cats using ultra-high field MRI

2024· article· en· W4400273353 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueNeuroimage Reports · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAnimal Vocal Communication and Behavior
Canadian institutionsMcGill University Health CentreMcGill University
FundersCanadian Institutes of Health Research
KeywordsCrossmodalSensory systemAuditory cortexNeuroplasticityAudiologyNeuroscienceStimulus modalityPsychologyCerebral cortexCATSMedicinePerceptionVisual perception

Abstract

fetched live from OpenAlex

In the absence of hearing, the plastic nature of the cerebral cortex allows select regions to be repurposed to serve the processing of remaining sensory modalities. This plasticity can be observed in many ways, including measuring the thickness differences of cortical gray matter between hearing and deaf populations to detect regional adaptations. In this study, T1-weighted images were acquired for hearing (n = 38) and perinatally-deafened (n = 31) cats using an ultra-high field 7T MRI scanner to identify normative feline cortical thickness, as well as areas of differing thickness between groups. Most significant changes to sensory-related regions demonstrated thicker cortices in the deaf compared to the hearing group, while specific non-sensory regions were found to be thinner. Furthermore, there was a modest lateralized component, finding that the gray matter of the left hemisphere was more susceptible to thickness changes following auditory deprivation. These results suggest distinct factors driving the adaptations in sensory versus non-sensory cortices in the brain following deafness, and reinforces the task-retainment model of crossmodal plasticity.

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.

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 score0.640
Threshold uncertainty score0.441

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 head0.048
GPT teacher head0.323
Teacher spread0.274 · 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