Differential Influence of Ventromedial Prefrontal Cortex Lesions on Neural Representations of Schema and Semantic Category Knowledge
Bibliographic record
Abstract
Prior knowledge, such as schemas or semantic categories, influences our interpretation of stimulus information. For this to transpire, prior knowledge must first be reinstated and then instantiated by being applied to incoming stimuli. Previous neuropsychological models implicate the ventromedial prefrontal cortex (vmPFC) in mediating these functions for schemas and the anterior/lateral temporal lobes and related structures for categories. vmPFC, however, may also affect processing of semantic category information. Here, the putative differential role of the vmPFC in the reinstatement and instantiation of schemas and semantic categories was examined by probing network-level oscillatory dynamics. Patients with vmPFC damage (n = 11) and healthy controls (n = 13) were instructed to classify words according to a given schema or category, while electroencephalography was recorded. As reinstatement is a preparatory process, we focused on oscillations occurring 500 msec prior to stimulus presentation. As instantiation occurs at stimulus presentation, we focused on oscillations occurring between stimulus presentation and 1000 msec poststimulus. We found that reinstatement was associated with prestimulus, theta and alpha desynchrony between vmPFC and the posterior parietal cortex for schemas, and between lateral temporal lobe and inferotemporal cortex for categories. Damage to the vmPFC influenced both schemas and categories, but patients with damage to the subcallosal vmPFC showed schema-specific deficits. Instantiation showed similar oscillatory patterns in the poststimulus time frame, but in the alpha and beta frequency bands. Taken together, these findings highlight distinct but partially overlapping neural mechanisms implicated in schema- and category-mediated processing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".