Increased intensity perception of aversive taste following right anteromedial temporal lobe removal in humans
Bibliographic record
Abstract
We used a modified version of the Spatial Taste Test to assess taste intensity perception in patients with either left or right temporal resection from the anteromedial temporal lobe (AMTL), and a group of control subjects. Sweet, sour, salty and bitter solutions were applied onto discrete locations of the tongue to stimulate either left or right fungiform, or left or right foliate papillae. Intensity ratings were assessed with the Labeled Magnitude Scale. Subjects also sipped 5 ml of each solution for whole mouth stimulation. Genetically based determinants of taste sensitivity were assessed with ratings of 6-n-propylthiouracil, and covaried from all analyses. As in previous studies, analysis of covariance indicated that the subjects in the right temporal group rated an aversive bitter taste as more intense than did subjects in the control group. In contrast, there were no group differences for sucrose ratings, suggesting that the AMTL may be involved preferentially in processing aversive compared with hedonic tastes. No group x side, or group x location effects were present. These results confirm that removal of the right AMTL in humans results in increased taste intensity/aversiveness perception. This finding complements existing literature indicating that the AMTL is important for processing aversive taste, and suggests that inhibitory mechanisms may play an important role in such processing.
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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) | 0.000 | 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) | 0.001 | 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".