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Record W2084407515 · doi:10.1037/cjep2006029

Neural synchrony in stochastic resonance, attention, and consciousness.

2006· review· en· W2084407515 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.

Bibliographic record

VenueCanadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · 2006
Typereview
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsConsciousnessPerceptionPsychologyArtificial neural networkFunctional magnetic resonance imagingCognitionNoise (video)Neural activityCognitive scienceNeural correlates of consciousnessCognitive psychologyNeuroscienceArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

We describe briefly three of our lab's ongoing projects studying the role of neural synchrony in human perception and cognition. These projects arise from two main interests: the role of noise both in human perception and in neural synchrony, and neural synchrony as a basis for integration of functional modules in the brain. Our experimental work on these topics began with a study of the possibility that noise-influenced neural synchrony might be responsible for the fact that small amounts of noise added to weak signals can enhance their detectability (stochastic resonance). We are also studying the role of neural synchrony in attention and consciousness in several paradigms. On the basis of our own and related work by others, we conclude that (1) neural synchrony plays an important role in the integration of functional modules in the brain and (2) neural synchrony is profoundly affected and possibly regulated, in part, by the "noisiness" of the brain.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.854
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.061
GPT teacher head0.334
Teacher spread0.273 · 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