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Record W2978438249 · doi:10.1101/792010

Cortico-cortical feedback from V2 exerts a powerful influence over the visually evoked local field potential and associated spike timing in V1

2019· preprint· en· W2978438249 on OpenAlexaff
Till S. Hartmann, Sruti Raja, Stephen G. Lomber, Richard T. Born

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldNeuroscience
TopicNeural dynamics and brain function
Canadian institutionsMcGill University
Fundersnot available
KeywordsLocal field potentialNeuroscienceVisual cortexRhythmStimulus (psychology)PhysicsElectrophysiologyElectroencephalographyAmplitudeCoincidence detection in neurobiologyPsychologyOpticsMedicineCoincidenceAcousticsCognitive psychology

Abstract

fetched live from OpenAlex

Abstract The local field potential (LFP) is generally thought to be dominated by synaptic activity within a few hundred microns of the recording electrode. The sudden onset of a visual stimulus causes a large downward deflection of the LFP recorded in primary visual cortex, known as a visually evoked potential (VEP), followed by rhythmic oscillations in the gamma range (30-80 Hz) that are often in phase with action potentials of nearby neurons. By inactivating higher visual areas that send feedback projections to V1, we produced a large decrease in amplitude of the VEP, and a strong attenuation of gamma rhythms in both the LFP and multi-unit activity, despite an overall increase in neuronal spike rates. Our results argue that much of the recurrent, rhythmic activity measured in V1 is strongly gated by feed-back from higher areas, consistent with models of coincidence detection that result in burst firing by layer 5 pyramidal neurons.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.009

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 integrity0.0000.000
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 head0.012
GPT teacher head0.228
Teacher spread0.217 · 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

Citations9
Published2019
Admission routes1
Has abstractyes

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