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Neural Activity Is Modulated by Trial History: A Functional Magnetic Resonance Imaging Study of the Effects of a Previous Antisaccade

2007· article· en· W2025681343 on OpenAlexaff
Dara S. Manoach, Matthew S. Cain, Frida E. Polli, Jay A. Edelman, Bruce Fischl, Jason Barton

Bibliographic record

VenueJournal of Neuroscience · 2007
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsUniversity of British Columbia
FundersNational Center for Research ResourcesNational Institute of Biomedical Imaging and BioengineeringNational Institute of Neurological Disorders and StrokeNational Institute of Mental HealthU.S. Department of Energy
KeywordsAntisaccade taskFunctional magnetic resonance imagingSaccadic maskingNeuroimagingPsychologyNeuroscienceEye movementFrontal eye fieldsNeural activityFunctional neuroimagingAudiologyMedicineSaccade

Abstract

fetched live from OpenAlex

Saccadic latencies are influenced by what occurred during the previous trial. When the previous trial is an antisaccade, the latencies of both prosaccades and antisaccades are prolonged. The aim of this study was to identify neural correlates of this intertrial effect of antisaccades. Specifically, based on both monkey electrophysiology and human neuroimaging findings, we expected trials preceded by antisaccades to be associated with reduced frontal eye field (FEF) activity relative to those preceded by prosaccades. Twenty-one healthy participants performed pseudorandom sequences of prosaccade and antisaccade trials during functional magnetic resonance imaging (fMRI) with concurrent monitoring of eye position. We compared activity in trials preceded by an antisaccade with activity in trials preceded by a prosaccade. The primary result was that a previous antisaccade prolonged saccadic latency and reduced fMRI activity in the FEF and other regions. No regions showed increased activity. We interpret the reduced FEF activity and slower saccadic responses to reflect inhibitory influences on the response system as a consequence of performing an antisaccade in the previous trial. This demonstrates that neural activity is modulated by trial history, consistent with a rapid, dynamic form of learning. More generally, these results highlight the importance of trial history as a source of variability in both behavioral and neuroimaging studies.

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)0.001
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.712
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.034
GPT teacher head0.268
Teacher spread0.233 · 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.

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

Citations86
Published2007
Admission routes1
Has abstractyes

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