Effects of ketamine on frontoparietal interactions during working memory in macaque monkeys
Bibliographic record
Abstract
ABSTRACT Schizophrenia is known as a syndrome of dysconnection among brain regions. As a model for this syndrome, low doses of N-methyl-D-aspartate (NMDA) receptor antagonists, such as ketamine, produce schizophrenia-like symptoms and cognitive deficits in healthy humans and animals. One of such deficits is impaired working memory, a process that engages an extended network of both frontal and parietal areas. While ketamine is known to disrupt working memory by altering both spiking and oscillatory activities in the lateral prefrontal cortex (lPFC), it remains unknown whether NMDA receptor antagonists also produce frontoparietal dysconnection during working memory processes. Here, we simultaneously recorded both single unit activities and local field potentials from lPFC and posterior parietal cortex (PPC) in macaque monkeys during a rule-based working memory task. Like previous work in the lPFC alone, we found that ketamine compromised delay-period rule coding in single neurons and reduced low-frequency oscillations in the PPC. Furthermore, ketamine reduced task-related connectivity in both fronto-parietal and parieto-frontal directions. Consistent with this, ketamine also weakened interareal coherence between spiking and low-frequency oscillatory activities. Our findings demonstrate the utility of acute NMDA receptor antagonist in simulating a syndrome of dysconnection and support this model in its potential for the exploration of novel treatment strategies for schizophrenia.
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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".