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Record W3162764539 · doi:10.31234/osf.io/av2by

Embryonic Brain’s Spontaneous Activity Promote Synesthesia?

2019· preprint· en· W3162764539 on OpenAlexaff
J. Shashi Kiran Reddy, Georg Northoff

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldNeuroscience
TopicOlfactory and Sensory Function Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsSensory systemNeuroscienceSynesthesiaEmbryonic stem cellPsychologyBrain activity and meditationMechanism (biology)BiologyElectroencephalographyPerception

Abstract

fetched live from OpenAlex

Antón-Bolaños et al. (2019) report a newly identified neural pathway mechanism, where the patterned spontaneous activity regulates the excitability of a neural network essential for the formation and maintenance of functional sensory maps in the brain. Findings from the study suggest that the patterned spontaneous activity prevalent during the embryonic development of the brain; at the early stages of innervation to the cortex, contributes to the formation of these sensory maps. Synesthesia is a neural phenomenon caused by the unusual links between sensory information, where synesthetic subjects demonstrate atypical functional and neural connectivity caused by the differences in cortical wiring during brain development. So, based on the findings from Antón-Bolaños et al. (2019), one can anticipate the role of spontaneous activity in promoting synesthetic condition. Thus, it will be interesting to study, if the intrinsic spontaneous activity influences the differential cortical wiring and the formation of sensory maps in synesthesia.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.120
GPT teacher head0.280
Teacher spread0.161 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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