Alpha oscillation neurofeedback modulates amygdala complex connectivity and arousal in posttraumatic stress disorder
Bibliographic record
Abstract
OBJECTIVE: Electroencephalogram (EEG) neurofeedback aimed at reducing the amplitude of the alpha-rhythm has been shown to alter neural networks associated with posttraumatic stress disorder (PTSD), leading to symptom alleviation. Critically, the amygdala is thought to be one of the central brain regions mediating PTSD symptoms. In the current study, we compare directly patterns of amygdala complex connectivity using fMRI, before and after EEG neurofeedback, in order to observe subcortical mechanisms associated with behavioural and alpha oscillatory changes among patients. METHOD: We examined basolateral (BLA), centromedial (CMA), and superficial (SFA) amygdala complex resting-state functional connectivity using a seed-based approach via SPM Anatomy Toolbox. Amygdala complex connectivity was measured in twenty-one individuals with PTSD, before and after a 30-minute session of EEG neurofeedback targeting alpha desynchronization. RESULTS: EEG neurofeedback was associated with a shift in amygdala complex connectivity from areas implicated in defensive, emotional, and fear processing/memory retrieval (left BLA and left SFA to the periaqueductal gray, and left SFA to the left hippocampus) to prefrontal areas implicated in emotion regulation/modulation (right CMA to the medial prefrontal cortex). This shift in amygdala complex connectivity was associated with reduced arousal, greater resting alpha synchronization, and was negatively correlated to PTSD symptom severity. CONCLUSION: These findings have significant implications for developing targeted non-invasive treatment interventions for PTSD patients that utilize alpha oscillatory neurofeedback, showing evidence of neuronal reconfiguration between areas highly implicated in the disorder, in addition to acute symptom alleviation.
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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) | 0.001 | 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".