Delineating Prefrontal Cortex Region Contributions to Crossmodal Object Recognition in Rats
Bibliographic record
Abstract
In the present study, we assessed the involvement of the prefrontal cortex (PFC) in the ability of rats to perform crossmodal (tactile-to-visual) object recognition tasks. We tested rats with 3 different types of bilateral excitotoxic lesions: (1) Large PFC lesions, including the medial PFC (mPFC) and ventral and lateral regions of the orbitofrontal cortex (OFC); (2) selective mPFC lesions; and (3) selective OFC lesions. Rats were tested on 2 versions of crossmodal object recognition (CMOR): (1) The original CMOR task, which uses a tactile-only sample phase and a visual-only choice phase; and (2) a "multimodal pre-exposure" version (PE/CMOR), in which simultaneous pre-exposure to the tactile and visual features of an object facilitates CMOR performance over longer memory delays. Inclusive PFC lesions disrupted performance on both versions of CMOR, whereas selective mPFC damage had no effect. Lesions limited to the OFC caused delay-dependent deficits on the CMOR task, but failed to reverse the enhancement produced by multimodal object pre-exposure. This pattern of functional dissociations suggests complex, multidimensional contributions of the PFC and its subregions to crossmodal cognition.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".