Modulation of Ventral Prefrontal Cortex Functional Connections Reflects the Interplay of Cognitive Processes and Stimulus Characteristics
Bibliographic record
Abstract
Emerging ideas of brain function emphasize the context-dependency of regional contributions to cognitive operations, where the function of a particular region is constrained by its pattern of functional connectivity. We used functional magnetic resonance imaging to examine how modality of input (auditory or visual) affects prefrontal cortex (PFC) functional connectivity for simple working memory tasks. The hypothesis was that PFC would show contextually dependent changes in functional connectivity in relation to the modality of input despite similar cognitive demands. Participants were presented with auditory or visual bandpass-filtered noise stimuli, and performed 2 simple short-term memory tasks. Brain activation patterns independently mapped onto modality and task demands. Analysis of right ventral PFC functional connectivity, however, suggested these activity patterns interact. One functional connectivity pattern showed task differences independent of stimulus modality and involved ventromedial and dorsolateral prefrontal and occipitoparietal cortices. A second pattern showed task differences that varied with modality, engaging superior temporal and occipital association regions. Importantly, these association regions showed nonzero functional connectivity in all conditions, rather than showing a zero connectivity in one modality and nonzero in the other. These results underscore the interactive nature of brain processing, where modality-specific and process-specific networks interact for normal cognitive operations.
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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) | 0.000 | 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".