Unilateral deactivation of macaque dorsolateral prefrontal cortex induces biases in stimulus selection
Bibliographic record
Abstract
Following unilateral brain injury, patients are often unable to detect a stimulus presented in the contralesional field when another is presented simultaneously ipsilesionally. This phenomenon has been referred to as extinction and has been conceptualized as a deficit in selective attention. Although most commonly observed following damage to posterior parietal areas, extinction has been observed following lesions of prefrontal cortex (PFC) in both humans and nonhuman primates. To date, most studies in nonhuman primates have examined lesions of multiple PFC subregions, including the frontal eye fields (FEF). Theoretical accounts of attentional disturbances from human patients, however, also implicate other PFC areas, including the middle frontal gyrus. Here, we investigated the effects of deactivating PFC areas anterior to the FEF on stimulus selection using a free-choice task. Macaque monkeys were presented with two peripheral stimuli appearing either simultaneously, or at varying stimulus onset asynchronies, and their performance was evaluated during unilateral cryogenic deactivation of part of dorsolateral prefrontal cortex or the cortex lining the caudal principal sulcus, the likely homologue of the human middle frontal gyrus. A decreased proportion of saccades was made to stimuli presented in the hemifield contralateral to the deactivated PFC. We also observed increases in reaction times to contralateral stimuli and decreases for stimuli presented in the hemifield ipsilateral to the deactivated hemisphere. In both cases, these results were greatest when both PFC subregions were deactivated. These findings demonstrate that selection biases result from PFC deactivation and support a role of dorsolateral prefrontal subregions anterior to FEF in stimulus selection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".