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Record W2086599900 · doi:10.1152/jn.00611.2012

Threshold mechanism for saccade initiation in frontal eye field and superior colliculus

2013· article· en· W2086599900 on OpenAlexafffund
Jay Jantz, Masayuki Watanabe, Stefan Everling, Douglas P. Munoz

Bibliographic record

VenueJournal of Neurophysiology · 2013
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsWestern UniversityQueen's University
FundersCanadian Institutes of Health ResearchStryker
KeywordsSaccadeSaccadic maskingSuperior colliculusNeuroscienceStimulus (psychology)PopulationFrontal eye fieldsEye movementPsychologySupplementary eye fieldInhibitory postsynaptic potentialSuperior ColliculiAntisaccade taskVisual cortexVisual systemCognitive psychologyMedicine

Abstract

fetched live from OpenAlex

In an influential model of frontal eye field (FEF) and superior colliculus (SC) activity, saccade initiation occurs when the discharge rate of either single neurons or a population of neurons encoding a saccade motor plan reaches a threshold level of activity. Conflicting evidence exists for whether this threshold is fixed or can change under different conditions. We tested the fixed-threshold hypothesis at the single-neuron and population levels to help resolve the inconsistency between previous studies. Two rhesus monkeys performed a randomly interleaved pro- and antisaccade task in which they had to look either toward (pro) or 180° away (anti) from a peripheral visual stimulus. We isolated visuomotor (VM) and motor (M) neurons in the FEF and SC and tested three specific predictions of a fixed-threshold hypothesis. We found little support for fixed thresholds. First, correlations were never totally absent between presaccadic discharge rate and saccadic reaction time when examining a larger (plausible) temporal period. Second, presaccadic discharge rates varied markedly between saccade tasks. Third, visual responses exceeded presaccadic motor discharges for FEF and SC VM neurons. We calculated that only a remarkably strong bias for M neurons in downstream projections could render the fixed-threshold hypothesis plausible at the population level. Also, comparisons of gap vs. overlap conditions indicate that increased inhibitory tone may be associated with stability of thresholds. We propose that fixed thresholds are the exception rather than the rule in FEF and SC, and that stabilization of an otherwise variable threshold depends on task-related, inhibitory modulation.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.109
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.044
GPT teacher head0.313
Teacher spread0.269 · 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

Citations58
Published2013
Admission routes2
Has abstractyes

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