Limbic Activity Modulation Guided by Functional Magnetic Resonance Imaging-Inspired Electroencephalography Improves Implicit Emotion Regulation

作者：Keynan Jackob N; Meir Hasson Yehudit; Gilam Gadi; Cohen Avihay; Jackont Gilan; Kinreich Sivan; Ikar Limor; Or Borichev Ayelet; Etkin Amit; Gyurak Anett; Klovatch Ilana; Intrator Nathan; Hendler Talma^*

来源：Biological Psychiatry, 2016, 80(6): 490-496.

DOI：10.1016/j.biopsych.2015.12.024

• Amygdala
• Brain-computer interface
• EEG neurofeedback
• Machine learning
• Real-time fMRI
• Stress

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.

• 出版日期2016-9-15