Abstract
The amygdala has a pivotal role in processing traumatic stress; hence, gaining control over its activity could facilitate adaptive mechanism and recovery. To date, amygdala volitional regulation could be obtained only via real-time functional magnetic resonance imaging (fMRI), a highly inaccessible procedure. The current article presents high-impact neurobehavioral implications of a novel imaging approach that enables bedside monitoring of amygdala activity using fMRI-inspired electroencephalography (EEG), hereafter termed amygdala-electrical fingerprint (amyg-EFP). Simultaneous EEG/fMRI indicated that the amyg-EFP reliably predicts amygdala-blood oxygen level–dependent activity. Implementing the amyg-EFP in neurofeedback demonstrated that learned downregulation of the amyg-EFP facilitated volitional downregulation of amygdala-blood oxygen level–dependent activity via real-time fMRI and manifested as reduced amygdala reactivity to visual stimuli. Behavioral evidence further emphasized the therapeutic potential of this approach by showing improved implicit emotion regulation following amyg-EFP neurofeedback. Additional EFP models denoting different brain regions could provide a library of localized activity for low-cost and highly accessible brain-based diagnosis and treatment.
Original language | English |
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Pages (from-to) | 490-496 |
Number of pages | 7 |
Journal | Biological Psychiatry |
Volume | 80 |
Issue number | 6 |
DOIs | |
State | Published - 15 Sep 2016 |
Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2016 Society of Biological Psychiatry
Keywords
- Amygdala
- Brain-computer interface
- EEG neurofeedback
- Machine learning
- Real-time fMRI
- Stress