A Pilot Study of Electrocortical Activity in Dysfunctional Anger: Decreased Frontocortical Activation, Impaired Attention Control, and Diminished Behavioral Inhibition
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Bibliographic record
Abstract
Dysfunctional anger, though not a primary clinical diagnosis per se, does present clinically as a pathological mood for which treatment is sought. Few studies have probed the neurocortical correlates of dysfunctional anger or assessed if cognitive processes, such as attention, are altered in dysfunctional anger. Though dysfunctional and high trait anger appears to be associated with biased processing of anger-eliciting information, few studies have examined if dysfunctional anger modulates attention more generally. This is a notable gap as volitional attention control is associated with effective emotive regulation, which is impaired in dysfunctional anger and in associated acts of aggression. In this pilot study, we examined performance and electroencephalographic (EEG) profiles during a 12-min continuous performance task (CPT) of sustained attention in 15 adults with dysfunctional anger (Anger group) and 14 controls (control group). The Anger group had fewer hits at the end of the CPT, which correlated with decreased frontocortical activation, suggesting decreased engagement of frontal circuits when attention is taxed. The Anger group had more false alarms overall indicating impaired response inhibition. Increased right cortical activation during the initial portion of CPT existed in the Anger group, perhaps reflecting greater engagement of frontal circuits (i.e. effort) during initial stages of the task compared to controls. Finally, increased overall beta₁ power, suggesting increased cortical activation, was noted in the Anger group. These EEG patterns suggest a hypervigilant state in dysfunctional anger, which may interfere with effective attention control and decrease inhibition. Such impairments likely extend beyond the laboratory setting, and may associate with aggressive acts in real life.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it