Neurofeedback training for major depressive disorder: recent developments and future directions
Major depression is a disorder characterized by sad mood, loss of pleasure, and other affect-related, cognitive, and physical symptoms. Major depression is a very common and debilitating disorder, which is frequently recurrent in individuals and often has significant personal, social, societal, and economic costs. Nonetheless, the use of neurofeedback training for major depression is a relatively novel area. Efforts in developing neurofeedback techniques for use with major depression will be highly beneficial for the clinical psychology field, for neurofeedback is less invasive and leads to fewer side effects than other treatments for depression, such as deep brain stimulation and pharmacological interventions. Sacchet and Gotlib’s (2016) review of literature summarizes some of the newest and most promising applications of neurofeedback to the research and treatment of major depression.
Sacchet and Gotlib (2016) describe neurofeedback developments for use with major depression including both research and treatment purposes. When using neurofeedback training to reduce depressive symptoms, researchers have found that reduced depression is associated with modulated activity of certain brain regions. Specifically, reduced activity in the salience brain network has been associated with reduction of the negative biases associated with major depression. Furthermore, Sacchet and Gotlib address their current research in which preliminary results indicate that when children with familial risk for depression modulate salience network activity, their stress reactivity is similarly reduced. Another use of neurofeedback techniques is in the investigation of neural connectivity associations with major depression. Past literature reviews have found major depression is associated with decreased connectivity in the frontoparietal network and increased connectivity in the default mode network. Another study has found that increased left amygdala activity is associated with the recall of positive autobiographical memories and that reduced activation is associated with symptoms of depression. This research can be used to inform future neurofeedback treatment protocols for depression, introducing neural connectivity as a feedback signal. Finally, the use of machine learning analyses have been found to be able to identify depressed compared to healthy individuals. These areas of use for neurofeedback techniques in the research and treatment of depression are novel, yet promising, and certainly warrant future investigation to enhance our understand of applications of neurofeedback.