An Event-Related fMRI Study of Visual and Auditory Oddball Tasks
Bibliographic record
Abstract
Abstract Whole brain event-related functional magnetic resonance imaging (fMRI) techniques were employed to elucidate the cerebral sites involved in processing rare target and novel visual stimuli during an oddball discrimination task. The analyses of the hemodynamic response to the visual target stimuli revealed a distributed network of neural sources in anterior and posterior cingulate, inferior and middle frontal gyrus, bilateral parietal lobules, anterior superior temporal gyrus, amygdala, and thalamus. The analyses of the hemodynamic response for the visual novel stimuli revealed an extensive network of neural activations in occipital lobes and posterior temporal lobes, bilateral parietal lobules, and lateral frontal cortex. The hemodynamic response associated with processing target and novel stimuli in the visual modality were also compared with data from an analogous study in the auditory modality ( Kiehl et al., 2001 ). Similar patterns of activation were observed for target and novel stimuli in both modalities, but there were some significant differences. The results support the hypothesis that target detection and novelty processing are associated with neural activation in widespread neural areas, suggesting that the brain seems to adopt a strategy of activating many potentially useful brain regions despite the low probability that these brain regions are necessary for task performance.
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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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".