Resting EEG in alpha and beta bands predicts individual differences in attentional blink magnitude
Bibliographic record
Abstract
Accuracy for a second target is reduced when it is presented within 500 ms of a first target in a rapid serial visual presentation – an attentional blink (AB). There are reliable individual differences in the magnitude of the deficit observed in the AB. Recent evidence has shown that the attentional mode that an individual typically adopts during a task or in anticipation of a task, as indicated by various measures, predicts individual differences in the AB. It has yet to be observed whether indices of attentional mode when not engaged in a goal-directed task are also relevant to individual differences in the AB. Using an individual differences approach, we investigated the relationship between the AB and attention at rest as assessed with quantitative measures of EEG. Greater levels of alpha at rest, thought to represent an idling or inhibited cortex, were associated with larger AB magnitudes, where greater levels of beta at rest were associated with smaller AB magnitudes. Furthermore, individuals with more alpha than beta at rest demonstrated larger AB magnitudes than individuals with more beta than alpha at rest. This pattern of results was observed in two different studies, with different samples, different AB tasks, and using different procedures and recording systems. Our results suggest that less attentional engagement at rest, when not engaged in a goal-directed task, is associated with larger AB magnitudes. It is possible that high levels of alpha and low levels of beta at rest are representative of an internally oriented mode of attention that impairs perception of externally generated information as is required by the AB task. An alternative hypothesis is that high levels of alpha and low levels of beta at rest are representative of an anticipatory mode of attention that results in detrimental overinvestment in the AB task. Meeting abstract presented at VSS 2012
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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".