Hand position-dependent modulation of errors in vibrotactile temporal order judgments: the effects of transcranial magnetic stimulation to the human posterior parietal cortex
Bibliographic record
Abstract
The ability to decide which of the two stimuli is presented first can be probed using a temporal order judgment (TOJ) task. When the stimuli are delivered to the fingers, TOJ decisions can be confounded by the fact that the hands can be moved to different locations in space. How and where this confounded information is processed in the brain is poorly understood. In the present set of experiments, we addressed this knowledge gap by using single-pulse transcranial magnetic stimulation (TMS) to disrupt processing in the right or left posterior parietal cortex (PPC) during a vibrotactile TOJ task with stimuli applied to the right and left index fingers. In the first experiment, participants held their hands in an uncrossed configuration, and we found that when the index finger contralateral to the site of TMS was stimulated first, there was a significant increase in TOJ errors. This increase did not occur when stimuli were delivered to the ipsilateral finger first. In the second experiment, participants held their hands in a crossed configuration and the pattern of errors was reversed relative to the first experiment. In both the first two experiments, significant increases in TOJ error were present with TMS over either hemisphere, regardless of arm configuration; however, they were larger overall following TMS over the right PPC. Control experiments using sham TMS indicated the systematic modulation in error was not due to nonspecific effects of the stimulation. Additionally, we showed that these TMS-induced changes in TOJ errors were not due to a reduced ability to detect the timing of the vibrotactile stimuli. Taken together, these results demonstrate that both the right and left PPC contribute to the processing underlying vibrotactile TOJs by integrating vibrotactile information and proprioceptive information related to arm position in space.
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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 | 0.003 |
| 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".