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Record W4200426599 · doi:10.1111/ejn.15573

Multisensory responses in a belt region of the dorsal auditory cortical pathway

2021· article· en· W4200426599 on OpenAlexafffund
Yaser Merrikhi, Melanie A. Kok, Andrés E. Carrasco, M. Alex Meredith, Stephen G. Lomber

Bibliographic record

VenueEuropean Journal of Neuroscience · 2021
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsWestern UniversityMcGill University
FundersCanadian Institutes of Health Research
KeywordsNeuroscienceMultisensory integrationSomatosensory systemAuditory cortexSensory systemPsychologyStimulus modalityInhibitory postsynaptic potentialSensory stimulation therapyStimulation

Abstract

fetched live from OpenAlex

A basic function of the cerebral cortex is to receive and integrate information from different sensory modalities into a comprehensive percept of the environment. Neurons that demonstrate multisensory convergence occur across the necortex but are especially prevalent in higher order association areas. However, a recent study of a cat higher order auditory area, the dorsal zone (DZ) of auditory cortex, did not observe any multisensory features. Therefore, the goal of the present investigation was to address this conflict using recording and testing methodologies that are established for exposing and studying multisensory neuronal processing. Among the 482 neurons studied, we found that 76.6% were influenced by non-auditory stimuli. Of these neurons, 99% were affected by visual stimulation, but only 11% by somatosensory. Furthermore, a large proportion of the multisensory neurons showed integrated responses to multisensory stimulation, constituted a majority of the excitatory and inhibitory neurons encountered (as identified by the duration of their waveshape) and exhibited a distinct spatial distribution within DZ. These findings demonstrate that the DZ of auditory cortex robustly exhibits multisensory properties and that the proportions of multisensory neurons encountered are consistent with those identified in other higher order cortices.

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 score0.984
Threshold uncertainty score0.237

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.095
GPT teacher head0.336
Teacher spread0.240 · 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

Citations9
Published2021
Admission routes2
Has abstractyes

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