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Activity in the superior colliculus reflects dynamic interactions between voluntary and involuntary influences on orienting behaviour

2008· article· en· W2110006427 on OpenAlexaff
Andrew H. Bell, Douglas P. Munoz

Bibliographic record

VenueEuropean Journal of Neuroscience · 2008
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsQueen's University
Fundersnot available
KeywordsSuperior colliculusCued speechPsychologyStimulus (psychology)CovertSaccadeSuperior ColliculiNeuroscienceCognitive psychologyEye movementAudiologyVisual systemVisual cortex

Abstract

fetched live from OpenAlex

Performance in a behavioural task can be influenced by both bottom-up and top-down processes such as stimulus modality and prior probability. Here, we exploited differences in behavioural strategy to explore the role of the intermediate and deep layers of the superior colliculus (dSC) in covert orienting. Two monkeys were trained on a predictive cued-saccade task in which the cue predicted the target's upcoming location with 80% validity. When the delay between cue and target onset was 250 ms, both monkeys showed faster responses to the uncued (Invalid) location. This was associated with a reduced target-aligned response in the dSC on Valid trials for both monkeys and is consistent with a bottom-up (i.e. involuntary) bias. When the delay was increased to 650 ms, one monkey continued to show faster responses to the Invalid location whereas the other monkey showed faster responses to the Valid location, consistent with a top-down (i.e. voluntary) bias. This latter behaviour was correlated with an increase in activity in dSC neurons preceding target onset that was absent in the other monkey. Thus, using the information provided by the cue shifted the emphasis towards top-down processing, while ignoring this information allowed bottom-up processing to continue to dominate. Regardless of the selected strategy, however, neurons in the dSC consistently reflected the current bias between the two processes, emphasizing its role in both the bottom-up and top-down control of orienting behaviour.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.963
Threshold uncertainty score0.508

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.098
GPT teacher head0.348
Teacher spread0.250 · 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 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

Citations20
Published2008
Admission routes1
Has abstractyes

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