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Record W3196717433 · doi:10.1167/jov.21.9.2118

Dissociation between eye position and working memory signals during virtual reality tasks in the primate lateral prefrontal cortex

2021· article· en· W3196717433 on OpenAlexaff
Megan Roussy, Rogelio Luna, Benjamin Corrigan, Adam Sachs, Lena Palaniyappan, Julio Martínez-Trujillo

Bibliographic record

VenueJournal of Vision · 2021
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of OttawaRobarts Clinical TrialsWestern University
Fundersnot available
KeywordsSaccadeEye movementWorking memoryFixation (population genetics)Cued speechPopulationPrimateNeurosciencePrefrontal cortexPsychologyJoystickAudiologyCommunicationComputer scienceCognitionCognitive psychologyMedicineSimulation

Abstract

fetched live from OpenAlex

Neurons in the primate lateral prefrontal cortex (LPFC) maintain working memory (WM) representations of space. However, a proportion of LPFC neurons also encode signals related to eye position. Potential interference between eye related signals and WM representations has prompted strict control of eye position in traditional WM tasks. Therefore, it is unclear how unrestrained eye position may affect performance of a WM task and task related LPFC activity. To explore this, we trained two rhesus monkeys on a spatial WM task set in a naturalistic virtual environment. During task trials, a target was presented at 1 of 9 locations in the environment. The target then disappeared during a two second delay epoch, after which the animals were required to navigate to the cued target location using a joystick. Animals were permitted free visual exploration throughout the task. We recorded neuronal activity using two 96-channel Utah Arrays implanted in LPFC area 8ad/v. Even with unrestrained eye position, animals only spent 3.6% of total fixation time during the delay period looking at the target location. The duration in which animals looked at the target location did not influence trial outcome (Kruskal Wallis, p=0.151). We tested whether neuronal population activity during fixations could predict eye position on targets. Classifiers using neuronal population activity during fixation periods were unable to decode eye position above chance (T-Test, p=0.646). Moreover, we calculated the proportion of neurons tuned for saccade landing position in different reference frames. Only 2% of neurons were tuned for both target location and saccades in the retinocentric frame and 3% were tuned for target location and saccades in the spatiocentric frame. These results indicate that in a virtual environment, unrestricted eye position does not diminish performance on a spatial WM task. Results suggest a dissociation between eye position and WM signals within LPFC.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.003

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 studies0.0000.000
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 head0.044
GPT teacher head0.355
Teacher spread0.311 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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