Dissociable Effects of Reward on P300 and EEG Spectra Under Conditions of High vs. Low Vigilance During a Selective Visual Attention Task
Bibliographic record
Abstract
The influence of motivation on selective visual attention in states of high vs. low vigilance is poorly understood. To explore the possible differences in the influence of motivation on behavioral performance and neural activity in high and low vigilance levels, we conducted a prolonged 2 h 20 min flanker task and provided monetary rewards during the 20- to 40- and 100- to 120-min intervals of task performance. Both the behavioral and electrophysiological measures were modulated by prolonged task engagement. Moreover, the effect of reward was different in high vs. low vigilance states. The monetary reward increased accuracy and decreased the reaction time (RT) and number of omitted responses in the low but not in the high vigilance state. The fatigue-related decrease in P300 amplitude recovered to its level in the high vigilance state by manipulating motivation, whereas the fatigue-related increase in P300 latency was not modulated by reward. Additionally, the fatigue-related increase in event-related spectral power at 1-4 Hz was sensitive to vigilance decrement and reward. However, the spectral power at 4-8 Hz was only affected by the decrease in vigilance. These electrophysiological measures were not influenced by motivation in the state of high vigilance. Our results suggest that neural processing capacity, but not the timing of processing, is sensitive to motivation. These findings also imply that the fatigue-related impairments in behavioral performance and neural activity underlying selective visual attention only partly recover after manipulating motivation. Furthermore, our results provide evidence for the dissociable neural mechanisms underlying the fatigue-related decrease vs. reward-related increase in attentional resources.
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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 | 0.001 |
| 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) | 0.000 | 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".