Self-regulation of human brain activity using simultaneous real-time fMRI and EEG neurofeedback

Neuroimage. 2014 Jan 15:85 Pt 3:985-95. doi: 10.1016/j.neuroimage.2013.04.126. Epub 2013 May 11.

Abstract

Neurofeedback is a promising approach for non-invasive modulation of human brain activity with applications for treatment of mental disorders and enhancement of brain performance. Neurofeedback techniques are commonly based on either electroencephalography (EEG) or real-time functional magnetic resonance imaging (rtfMRI). Advances in simultaneous EEG-fMRI have made it possible to combine the two approaches. Here we report the first implementation of simultaneous multimodal rtfMRI and EEG neurofeedback (rtfMRI-EEG-nf). It is based on a novel system for real-time integration of simultaneous rtfMRI and EEG data streams. We applied the rtfMRI-EEG-nf to training of emotional self-regulation in healthy subjects performing a positive emotion induction task based on retrieval of happy autobiographical memories. The participants were able to simultaneously regulate their BOLD fMRI activation in the left amygdala and frontal EEG power asymmetry in the high-beta band using the rtfMRI-EEG-nf. Our proof-of-concept results demonstrate the feasibility of simultaneous self-regulation of both hemodynamic (rtfMRI) and electrophysiological (EEG) activities of the human brain. They suggest potential applications of rtfMRI-EEG-nf in the development of novel cognitive neuroscience research paradigms and enhanced cognitive therapeutic approaches for major neuropsychiatric disorders, particularly depression.

Keywords: Amygdala; EEG; EEG–fMRI; Emotion; Frontal EEG asymmetry; Neurofeedback; Real-time fMRI; rtfMRI–EEG neurofeedback.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brain / physiology*
  • Brain Mapping / methods
  • Electroencephalography*
  • Emotions / physiology
  • Female
  • Humans
  • Image Processing, Computer-Assisted
  • Magnetic Resonance Imaging*
  • Male
  • Neurofeedback / methods*
  • Signal Processing, Computer-Assisted
  • Young Adult