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Corticofugal Modulation of Initial Sound Processing in the Brain

2008· article· en· W1997623519 on OpenAlexafffund
Feng Luo, Qianzhou Wang, Alireza Kashani, Jun Yan

Bibliographic record

VenueJournal of Neuroscience · 2008
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsUniversity of Calgary
FundersFondation pour la Recherche MédicaleFondation Pour l'AuditionUniversity of Calgary
KeywordsNeuroscienceAuditory cortexCortex (anatomy)Cerebral cortexCochlear nucleusElectrophysiologyModulation (music)PsychologyNucleusPhysicsAcoustics

Abstract

fetched live from OpenAlex

The brain selectively extracts the most relevant information in top-down processing manner. Does the corticofugal system, a "back projection system," constitute the neural basis of such top-down selection? Here, we show how focal activation of the auditory cortex with 500 nA electrical pulses influences the auditory information processing in the cochlear nucleus (CN) that receives almost unprocessed information directly from the ear. We found that cortical activation increased the response magnitudes and shortened response latencies of physiologically matched CN neurons, whereas decreased response magnitudes and lengthened response latencies of unmatched CN neurons. In addition, cortical activation shifted the frequency tunings of unmatched CN neurons toward those of the activated cortical neurons. Our data suggest that cortical activation selectively enhances the neural processing of particular auditory information and attenuates others at the first processing level in the brain based on sound frequencies encoded in the auditory cortex. The auditory cortex apparently implements a long-range feedback mechanism to select or filter incoming signals from the ear.

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)0.002
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 score0.939
Threshold uncertainty score0.261

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.123
GPT teacher head0.365
Teacher spread0.242 · 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

Citations127
Published2008
Admission routes2
Has abstractyes

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