Functional dissociations between subregions of the medial prefrontal cortex on the rodent touchscreen continuous performance test (rCPT) of attention.
Bibliographic record
Abstract
Converging evidence in humans, monkeys, and rodents suggests a functional dissociation of cognitive function along the dorso-ventral axis of the prefrontal cortex (PFC). Previous studies of attention suggest that the anterior cingulate cortex (ACC) plays a role in target detection, whereas the prelimbic (PL) cortex is important for tests requiring the combined detection and discrimination of signals. We investigated the effect of discrete, quinolinic acid-induced lesions of subregions of the rat medial PFC (mPFC)-ACC, PL cortex, and infralimbic (IL) cortex-on attentional performance on the recently developed rodent touchscreen continuous performance test (rCPT). Rats were tested under a range of behavioral conditions involving stimulus duration (SD), flanker distraction, temporal predictability, and event rate. Rats with lesions of the PL cortex demonstrated the most persistent attentional impairment under conditions of reduced and variable SD and high event rate (lower discrimination sensitivity [d'] and hit rate), and flanker distraction (lower hit rate). Rats with lesions of the ACC exhibited a profound but transient attentional impairment (lower d' and hit rate) in the early stages of behavioral testing, which ameliorated with repeated testing. Rats with lesions of the IL cortex showed no impairments on response control measures. The PL cortex plays a greater role than the ACC in the detection and discrimination of a complex visual stimulus among multiple nontarget stimuli in the rCPT. The findings support evidence for a functional dissociation of attentional performance along the dorso-ventral axis of the mPFC. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".