Neural correlates of trait anxiety in sensory processing and distractor filtering
Bibliographic record
Abstract
Evidence suggests that trait anxiety relates to cognitive processing and behavior. However, the relationships between trait anxiety and sensory processing, goal-directed performance and sensorimotor function are unclear, particularly in a multimodal context. This study used electroencephalography to evaluate whether trait anxiety influenced visual and tactile event-related potentials (ERPs), as well as behavioral distractor cost, in a bimodal sensorimotor task. Twenty-nine healthy young adults completed the State-Trait Anxiety Inventory. Participants were directed to focus on either tactile or visual stimuli while disregarding the other modality, responding to target stimulus amplitude with a proportional grip. Previous research suggests that somatosensory N70 and visual P2 ERPs serve as markers of attentional relevance, with attention also impacting the visual P3 ERP. It was hypothesized that trait anxiety would modulate the ERPs susceptible to attentional modulation (tactile N70, visual P2 and P3) and not affect behavioral performance. Trait anxiety showed a large, significant interaction with attention for visual P3 latency in response to unimodal visual stimuli, with a positive relationship between P3 latencies and trait anxiety when attending toward the stimulus and negative when attending away. A large, positive main effect of trait anxiety on visual N1 amplitude for bimodal stimuli was also detected. As predicted, trait anxiety related to ERPs but not behavioral distractor cost. These findings suggest that trait anxiety modulates visual but not somatosensory processing correlates based on attention. The absence of overt behavioral performance effects suggests compensatory mechanisms may offset underlying differences in sensory 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 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".