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.
The hippocampus is known to play a vital role in learning and memory and was demonstrated as an early imaging marker for Alzheimer's disease (AD). However, its role as a predictor for mild cognitive impairment and dementia following stroke is unclear. The main purpose of this study was to examine the associations between hippocampal volume, mean diffusivity (MD) and connectivity and cognitive state following stroke. Eighty three consecutive first ever mild to moderate stroke or transient ischemic attack (TIA) survivors from our ongoing prospective TABASCO (Tel Aviv Brain Acute Stroke Cohort) study underwent magnetic resonance imaging scans within 7 days of stroke onset. Hippocampal volume was measured from T1 weighted images, hippocampal mean diffusivity was calculated from diffusion tensor imaging and connectivity was calculated from resting state fMRI. Global cognitive assessments were evaluated during hospitalization and 6 and 12 months later using a computerized neuropsychological battery. Multiple linear regression analysis was used to test which of the hippocampi measurements best predict cognitive state. All three imaging parameters were significantly correlated to each other (|r's| >0.3, P's < 0.005), and with cognitive state 6 and 12 months after the event. Multiple regression analyses demonstrated the predictive role of hippocampal mean diffusivity (β = -0.382, P = 0.026) on cognitive state, above and beyond that of volume and connectivity of this structure. To our knowledge, the combination of hippocampal volume, mean diffusivity and connectivity in first ever post stroke or TIA patients has not yet been considered in relation to cognitive state. The results demonstrate the predictive role of hippocampal mean diffusivity, suggesting that these changes may precede and contribute to volumetric and connectivity changes in the hippocampi, potentially serving as a marker for early identification of patients at risk of developing cognitive impairment or dementia.
This paper discusses the potential of Brain-Computer Interfaces based on neurofeedback methods to support emotional control and pursue the goal of emotional control as a mechanism for human augmentation in specific contexts. We illustrate this discussion through two proof-ofconcept, fully-implemented experiments: one controlling disposition towards virtual characters using pre-frontal alpha asymmetry, and the other aimed at controlling arousal through activity of the amygdala. In the first instance, these systems are intended to explore augmentation technologies that would be incorporated into various media-based systems rather than permanently affect user behaviour.
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