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Record W2168048252 · doi:10.1152/jn.00891.2011

Functional connectivity of the frontal eye fields in humans and macaque monkeys investigated with resting-state fMRI

2012· article· en· W2168048252 on OpenAlexafffund
R. Matthew Hutchison, Jason P. Gallivan, Jody C. Culham, Joseph S. Gati, Ravi S. Menon, Stefan Everling

Bibliographic record

VenueJournal of Neurophysiology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicFunctional Brain Connectivity Studies
Canadian institutionsRobarts Clinical TrialsWestern University
FundersCanadian Institutes of Health Research
KeywordsMacaqueFrontal eye fieldsNeuroscienceIntraparietal sulcusFunctional connectivityDorsolateral prefrontal cortexPrimateResting state fMRIPsychologyPosterior parietal cortexRhesus macaqueFrontal lobePrefrontal cortexSupplementary eye fieldParietal lobeEye movementBiologyCognitionSaccadic maskingSaccade

Abstract

fetched live from OpenAlex

Although the frontal eye field (FEF) has been identified in macaque monkeys and humans, practical constraints related to invasiveness and task demands have limited a direct cross-species comparison of its functional connectivity. In this study, we used resting-state functional MRI data collected from both awake humans and anesthetized macaque monkeys to examine and compare the functional connectivity of the FEF. A seed region analysis revealed consistent ipsilateral functional connections of the FEF with fronto-parietal cortical areas across both species. These included the intraparietal sulcus, dorsolateral prefrontal cortex, anterior cingulate cortex, and supplementary eye fields. The analysis also revealed greater lateralization of connectivity with the FEF in both hemispheres in humans than in monkeys. Cortical surface-based transformation of connectivity maps between species further corroborated the remarkably similar organization of the FEF functional connectivity. The results support an evolutionarily preserved fronto-parietal system and provide a bridge for linking data from monkey and human 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)0.000
metaresearch head score (Gemma)0.004
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 score0.847
Threshold uncertainty score0.442

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.038
GPT teacher head0.251
Teacher spread0.212 · 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

Citations128
Published2012
Admission routes2
Has abstractyes

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