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Record W2041680616 · doi:10.1076/jcen.24.7.951.8387

Orienting Attention in Aging and Parkinson's Disease: Distinguishing Modes of Control

2002· article· en· W2041680616 on OpenAlexafffund
Alan Kingstone, Raymond M. Klein, Sharon Morein‐Zamir, Amelia R. Hunt, John D. Fisk, Charles Maxner

Bibliographic record

VenueJournal of Clinical and Experimental Neuropsychology · 2002
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of British ColumbiaDalhousie UniversityUniversity of British Columbia Hospital
FundersNatural Sciences and Engineering Research Council of CanadaMichael Smith Health Research BC
KeywordsPsychologyOrienting responseCovertCognitive psychologyTask (project management)Eye movementAttentional controlParkinson's diseaseAudiologyCognitionDevelopmental psychologyDiseaseNeuroscience

Abstract

fetched live from OpenAlex

Past research on attentional orienting and Parkinson's disease (PD) has been compromised because the experimental paradigms tended to confound different forms of orienting. We sought to overcome this by examining the attentional orienting of three distinct groups (PD-patients, age-matched controls, and young controls) on five different tasks, four of which isolated pure forms of orienting. On two covert orienting tasks PD patients oriented volitional (Experiment 1) and reflexive (Experiment 2) covert attention in a healthy and normal manner for their age. On two overt orienting tasks, PD patients were found to execute volitional eye movements that were prone to undershoot their target goal (Experiment 3), and reflexive eye movements that were unusually fast (Experiment 4). When required to perform an antisaccade task (Experiment 5), which combines reflexive and volitional modes of overt orienting, PD patients performed normally. This indicates that using a task which combines different modes of orienting creates a situation that is more than the sum of its parts. Together our study supports the thesis that it is crucial to isolate and investigate different modes of attentional control.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.292
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.180
GPT teacher head0.444
Teacher spread0.265 · 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

Citations45
Published2002
Admission routes2
Has abstractyes

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