Electrical fingerprint of the amygdala guides neurofeedback training for stress resilience

Abstract

Real-time functional magnetic resonance imaging (rt-fMRI) has revived the translational perspective of neurofeedback (NF). Particularly for stress management, targeting deeply located limbic areas involved in stress processing has paved new paths for brain-guided interventions. However, the high cost and immobility of fMRI constitute a challenging drawback for the scalability (accessibility and costeffectiveness) of the approach, particularly for clinical purposes. The current study aimed to overcome the limited applicability of rt-fMRI by using an electroencephalography (EEG) model endowed with improved spatial resolution, derived from simultaneous EEG-fMRI, to target amygdala activity (termed amygdala electrical fingerprint (Amyg-EFP). Healthy individuals (n = 180) undergoing a stressful military training programme were randomly assigned to six Amyg-EFP-NF sessions or one of two controls (control-EEG-NF or NoNF), taking place at the military training base. The training results demonstrated specificity of NF learning to the targeted Amyg-EFP signal, which led to reduced alexithymia and faster emotional Stroop indicating better stress coping following Amyg-EFP-NF relative to controls. Neural target engagement was demonstrated in a follow-up fMRI-NF, showing greater amygdala blood-oxygen-level-dependent activity downregulation and amygdala-ventromedial prefrontal cortex functional connectivity following Amyg-EFP-NF relative to NoNF. Together, these results demonstrate limbic specificity and efficacy of Amyg-EFP-NF during a stressful period, pointing to a scalable nonpharmacological yet neuroscience-based training to prevent stress-induced psychopathology.

Neuroimaging resilience to trauma: convergent evidence and challenges for future research

“…Despite these challenges, interventions derived from neuroscientific studies of resilience are starting to be implemented in real-world settings (Greenberg, 2006;Waugh and Koster, 2015;Keynan et al, 2019). A complementary research stream examining the neural correlates of treatment response to existing therapies may give further insight into neural resilience mechanisms that may be 'activated' by successful engagement with treatment (e.g., increased ability to assimilate or reappraise trauma memories following psychotherapy).…”

“…From an interventional perspective, a recent trial of electro-encephalography (EEG)-guided neurofeedback in individuals recruited from a pre-deployment military training program (N=180, all male), found that amygdala electrical fingerprint-guided neurofeedback training (i.e., training to volitionally downregulate EEG-derived amygdala signal), but not non-amygdala targeted training, improved 'emotional regulation' performance as measured by response times on an emotional Stroop task and alexithymia questionnaire (but did not affect self-reported state anxiety; Keynan et al, 2019). Post-intervention fMRI neurofeedback sessions confirmed this improvement was related to ability to volitionally downregulate amygdala BOLD signal, and that the active treatment was associated with greater amygdala-mPFC functional connectivity estimates than control conditions.…”

Fostering students’ creative thinking skills by means of a one-year creativity training program

“…The neural headsets visualize the brainwaves of a student in real time and so, the student can monitor the level of attention or relaxation. By playing with the headsets, the students are challenged to smoothly rotate between a state of focused and defocused attention-a process that is vital for creativity and a skill that can be learned [53].…”

Reducing the Noise of Reality

“…This latter technique has already proven its potential in investigating fundamental neuroscientific questions, like the trainability of brain plasticity (Ros, Munneke, Ruge, Gruzelier, & Rothwell, 2010), EEG biomarker's connection to psychopathological symptoms (Ros, Baars, Lanius, & Vuilleumier, 2014), the normalization of scale-free dynamics in EEG in (Ros et al, 2016) and research on stroke patients rehabilitation (Ros et al, 2017). Moreover, the spatial resolution of EEG neurofeedback has recently been extended by using machine learning to extract deeper, non-cortical, signals like those from the amygdala (as elegantly shown by Keynan et al, 2019). Specific brain activity could therefore be modulated either endogenously with neurofeedback or externally with brain-stimulation techniques, in controlled SRD setups.…”