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Record W2887026033 · doi:10.1016/j.dcn.2018.07.002

The origins of cortical multisensory dynamics: Evidence from human infants

2018· article· en· W2887026033 on OpenAlexfundno aff
Denise M. Werchan, Heidi A. Baumgartner, David J. Lewkowicz, Dima Amso

Bibliographic record

VenueDevelopmental Cognitive Neuroscience · 2018
Typearticle
Languageen
FieldPsychology
TopicMultisensory perception and integration
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Mental HealthRyerson UniversityBrown UniversityNational Science Foundation
KeywordsSensory systemPsychologyNeuroscienceNeuroimagingCortex (anatomy)Multisensory integrationSensory processingAsynchronous communicationAdaptation (eye)Cerebral cortexCognitive scienceCognitive psychologyComputer science

Abstract

fetched live from OpenAlex

Classic views of multisensory processing suggest that cortical sensory regions are specialized. More recent views argue that cortical sensory regions are inherently multisensory. To date, there are no published neuroimaging data that directly test these claims in infancy. Here we used fNIRS to show that temporal and occipital cortex are functionally coupled in 3.5-5-month-old infants (N = 65), and that the extent of this coupling during a synchronous, but not an asynchronous, audiovisual event predicted whether occipital cortex would subsequently respond to sound-only information. These data suggest that multisensory experience may shape cortical dynamics to adapt to the ubiquity of synchronous multisensory information in the environment, and invoke the possibility that adaptation to the environment can also reflect broadening of the computational range of sensory systems.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.118
GPT teacher head0.404
Teacher spread0.286 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations48
Published2018
Admission routes1
Has abstractyes

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