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Role of the basal ganglia in switching a planned response

2009· article· en· W2158690787 on OpenAlexaff
Ian Cameron, Brian C. Coe, Masayuki Watanabe, Patrick W. Stroman, Douglas P. Munoz

Bibliographic record

VenueEuropean Journal of Neuroscience · 2009
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsAntisaccade taskBasal gangliaNeuroscienceTask switchingMechanism (biology)PsychologyFunction (biology)Frontal eye fieldsBasal (medicine)Frontal cortexEye movementBiologyCognitionCentral nervous systemPhysicsCell biologySaccadeEndocrinology

Abstract

fetched live from OpenAlex

The ability to perform an appropriate response in the presence of competing alternatives is a critical facet of human behavioral control. This is especially important if a response is prepared for execution but then has to be changed suddenly. A popular hypothesis of basal ganglia (BG) function suggests that its direct and indirect pathways could provide a neural mechanism to rapidly switch from one planned response to an alternative. However, if one response is more dominant or 'automatic' than the other, the BG might have a different role depending on switch direction. We built upon the pro- and antisaccade tasks, two models of automatic and voluntary behavior, respectively, and investigated whether the BG are important for switching any planned response in general, or if they are more important for switching from a more automatic response to a response that is more difficult to perform. Subjects prepared either a pro- or antisaccade but then had to switch it unexpectedly on a subset of trials. The results revealed increased striatal activation for switching from a pro- to an antisaccade but this did not occur for switching from an anti- to a prosaccade. This activation pattern depended on the relative difficulty in switching, and it was distinct from frontal eye fields, an area shown to be more active for antisaccade trials than for prosaccade trials. This suggests that the BG are important for compensating for differences in response difficulty, facilitating the rapid switching of one response for another.

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)0.001
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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.084
GPT teacher head0.332
Teacher spread0.248 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

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