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Record W2951061214

Cerebellar Lesions Impair Reflexive but not Voluntary Covert Attention: Preliminary Findings

2017· article· en· W2951061214 on OpenAlexaff
Brandon T. Craig

Bibliographic record

VenueStudent Research Proceedings · 2017
Typearticle
Languageen
FieldNeuroscience
TopicVestibular and auditory disorders
Canadian institutionsMacEwan University
Fundersnot available
KeywordsCovertCerebellumReflexivityPsychologyNeuroimagingNeuroscienceCognitive psychologyCognitionLinguisticsSociologyPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

Recent research has revealed that the cerebellum is involved in much more than just motor output. Interestingly, functional neuroimaging studies and human lesion studies have discovered that the cerebellum has been reported to be involved in various cognitive roles such as language, emotion, and attention. Specifically, our lab is interested in aspects of attention such as reflexive and voluntary covert attention. Previously, a neuroimaging study from our lab showed increased activity in the left cerebellum for covert reflexive attention compared to covert voluntary attention. However, this idea has not been directly tested behaviorally in patients with cerebellar lesions. Therefore, the current study examined how 10 patients with cerebellar lesions performed on reflexive and voluntary covert attention tasks. The results indicated that the cerebellar patients have a slowed onset of inhibition of return compared healthy-age matched controls (n=10). In addition, deficits in reflexive covert attention appeared to be linked with damage to the lateral cerebellum. In contrast, there were no differences between the patients and controls in the voluntary attention task. The current study provides converging evidence that the cerebellum may be more involved for reflexive covert attention compared to voluntary covert attention. Discipline: Psychology Honours Faculty Mentor: Dr. Christopher Striemer

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
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 score0.546
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0040.001
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.177
GPT teacher head0.447
Teacher spread0.270 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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