Affectively biased competition: sustained attention is tuned to rewarding expressions and is not modulated by norepinephrine receptor gene variant
Bibliographic record
Abstract
Abstract It is well established that emotionally salient stimuli evoke greater visual cortex activation than neutral ones, and can distract attention from competing tasks. Yet less is known about underlying neurobiological processes. As a proxy of population level biased competition , EEG steady-state visual evoked potentials are sensitive to competition effects from salient stimuli. Here we wished to examine whether individual differences in norepinephrine activity play a role in emotionally-biased competition. Our previous research has found robust effects of a common variation in the ADRA2B gene, coding for alpha2B norepinephrine (NE) receptors, on emotional modulation of attention and memory. In the present study, EEG was collected while 87 carriers of the ADRA2B deletion variant and 95 non-carriers (final sample) performed a change detection task in which target gratings (gabor patches) were superimposed directly over angry, happy, and neutral faces. Participants indicated the number of phase changes (0-3) in the target. Overlapping targets and distractors were flickered at a distinct driving frequencies. Relative EEG power for faces vs. targets at the driving frequency served as an index of cortical resources allocated to each of the competing stimuli. Deletion carriers and non-carriers were randomly assigned to Discovery and Replication samples and reliability of results across samples was assessed before the groups were combined for greater power. Overall happy faces evoked higher competition than angry or neutral faces; however, we observed no hypothesized effects of ADRA2B . Increased competition from happy faces was not due to the effect of low-level visual features or individuals low in social anxiety. Our results indicate that emotionally biased competition during sustained attention, while reliably observed in young adults, is not influenced by commonly observed individual differences linked to NE receptor function. They further indicate an overall pattern of affectively-biased competition for happy faces, which we interpret in relation to previously observed boundary conditions.
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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 | 0.001 |
| 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".