Amygdala real-time functional magnetic resonance imaging neurofeedback for major depressive disorder: A review

Abstract

Advances in imaging technologies have allowed for the analysis of functional magnetic resonance imaging data in real-time (rtfMRI), leading to the development of neurofeedback (nf) training. This rtfMRI-nf training utilizes functional magnetic resonance imaging (fMRI) tomographic localization capacity to allow a person to see and regulate the localized hemodynamic signal from his or her own brain. In this review, we summarize the results of several studies that have developed and applied neurofeedback training to healthy and depressed individuals with the amygdala as the neurofeedback target and the goal to increase the hemodynamic response during positive autobiographical memory recall. We review these studies and highlight some of the challenges and advances in developing an rtfMRI-nf paradigm for broader use in psychiatric populations. The work described focuses on our line of research aiming to develop the rtfMRI-nf into an intervention, and includes a discussion of the selection of a region of interest for feedback, selecting a control condition, behavioral and cognitive effects of training, and predicting which participants are most likely to respond well to training. While the results of these studies are encouraging and suggest the clinical potential of amygdala rtfMRI-nf in alleviating symptoms of major depressive disorder, larger studies are warranted to confirm its efficacy.

Keywords: amygdala; autobiographical memory; emotional processing; functional magnetic resonance imaging neurofeedback; major depressive disorder.

Figure 1. Design of the rtfMRI neurofeedback experiment

a) Regions of Interest for the rtfMRI neurofeedback procedure: left amygdala (red, centered at −21, −5, −16) and left horizontal segment of the intraparietal sulcus (green, centered at −42, −48, 48). Placements are illustrated on T1-weighted coronal human brain sections in Talairach space. Following radiological notation, the left side (L) of the brain is shown on the right, and the right side (R) of the brain on the left. b) Real-time display screen for the rtfMRI neurofeedback procedure. During the Happy condition, the word “Happy,” two color bars, and a number indicating the neurofeedback signal were displayed on the screen. Participants were instructed to recall happy autobiographical memories to make themselves feel happy while trying to increase the level of the red bar representing the feedback signal from the target region to a given target level indicated by the fixed height of the blue bar. c) Protocol for the rtfMRI neurofeedback experiment. The experimental protocol consisted of eight runs each lasting 8min 40sec. Neurofeedback training consisted of alternating blocs of Rest (R, pink block), Happy (H, red block), and Count (C, green block, instructed to count backwards from 300 by a given integer), each lasting 40sec.

Figure 2. Learned Enhancement of Control over Amygdala BOLD fMRI Activation

Average percent signal change for the Happy-Rest condition for each run and group in a) the initial feasibility study in healthy controls (11) b) the proof-of-concept study in MDD participantsp (15) and c) the randomized clinical trial of rtfMRI-nf (64). In figure 2b, * indicates a significant difference from 0 and # a significant difference from the experimental group at p<0.05. In Figure 2c, b indicates a significant difference from 0 and c indicates a significant difference from the experimental group at p<0.05 a) Figure 4 from Zotev V, Krueger F, Phillips R, Alvarez RP, Simmons WK, et al. (2011) Self-Regulation of Amygdala Activation Using Real-Time fMRI Neurofeedback. PLOS ONE 6(9): e24522. b) Figure 2 from Young KD, Zotev V, Phillips R, Misaki M, Yuan H, et al. (2014) Real-Time fMRI Neurofeedback Training of Amygdala Activity in Patients with Major Depressive Disorder. PLOS ONE 9(2): e88785. c) Figure 1 from Young KD, Siegle, GJ, Zotev V, Phillips R, Misaki M, Yuan H, et al. (2017) Randomized Clinical Trial of Real-Time fMRI Amygdala Neurofeedback for Major Depressive Disorder: Effects on Symptoms and Autobiographical Memory Recall American Journal of Psychiatry 174(8):748–755.

Figure 2. Learned Enhancement of Control over Amygdala BOLD fMRI Activation

Average percent signal change for the Happy-Rest condition for each run and group in a) the initial feasibility study in healthy controls (11) b) the proof-of-concept study in MDD participantsp (15) and c) the randomized clinical trial of rtfMRI-nf (64). In figure 2b, * indicates a significant difference from 0 and # a significant difference from the experimental group at p<0.05. In Figure 2c, b indicates a significant difference from 0 and c indicates a significant difference from the experimental group at p<0.05 a) Figure 4 from Zotev V, Krueger F, Phillips R, Alvarez RP, Simmons WK, et al. (2011) Self-Regulation of Amygdala Activation Using Real-Time fMRI Neurofeedback. PLOS ONE 6(9): e24522. b) Figure 2 from Young KD, Zotev V, Phillips R, Misaki M, Yuan H, et al. (2014) Real-Time fMRI Neurofeedback Training of Amygdala Activity in Patients with Major Depressive Disorder. PLOS ONE 9(2): e88785. c) Figure 1 from Young KD, Siegle, GJ, Zotev V, Phillips R, Misaki M, Yuan H, et al. (2017) Randomized Clinical Trial of Real-Time fMRI Amygdala Neurofeedback for Major Depressive Disorder: Effects on Symptoms and Autobiographical Memory Recall American Journal of Psychiatry 174(8):748–755.

Figure 2. Learned Enhancement of Control over Amygdala BOLD fMRI Activation

Average percent signal change for the Happy-Rest condition for each run and group in a) the initial feasibility study in healthy controls (11) b) the proof-of-concept study in MDD participantsp (15) and c) the randomized clinical trial of rtfMRI-nf (64). In figure 2b, * indicates a significant difference from 0 and # a significant difference from the experimental group at p<0.05. In Figure 2c, b indicates a significant difference from 0 and c indicates a significant difference from the experimental group at p<0.05 a) Figure 4 from Zotev V, Krueger F, Phillips R, Alvarez RP, Simmons WK, et al. (2011) Self-Regulation of Amygdala Activation Using Real-Time fMRI Neurofeedback. PLOS ONE 6(9): e24522. b) Figure 2 from Young KD, Zotev V, Phillips R, Misaki M, Yuan H, et al. (2014) Real-Time fMRI Neurofeedback Training of Amygdala Activity in Patients with Major Depressive Disorder. PLOS ONE 9(2): e88785. c) Figure 1 from Young KD, Siegle, GJ, Zotev V, Phillips R, Misaki M, Yuan H, et al. (2017) Randomized Clinical Trial of Real-Time fMRI Amygdala Neurofeedback for Major Depressive Disorder: Effects on Symptoms and Autobiographical Memory Recall American Journal of Psychiatry 174(8):748–755.

Figure 2. Learned Enhancement of Control over Amygdala BOLD fMRI Activation

Average percent signal change for the Happy-Rest condition for each run and group in a) the initial feasibility study in healthy controls (11) b) the proof-of-concept study in MDD participantsp (15) and c) the randomized clinical trial of rtfMRI-nf (64). In figure 2b, * indicates a significant difference from 0 and # a significant difference from the experimental group at p<0.05. In Figure 2c, b indicates a significant difference from 0 and c indicates a significant difference from the experimental group at p<0.05 a) Figure 4 from Zotev V, Krueger F, Phillips R, Alvarez RP, Simmons WK, et al. (2011) Self-Regulation of Amygdala Activation Using Real-Time fMRI Neurofeedback. PLOS ONE 6(9): e24522. b) Figure 2 from Young KD, Zotev V, Phillips R, Misaki M, Yuan H, et al. (2014) Real-Time fMRI Neurofeedback Training of Amygdala Activity in Patients with Major Depressive Disorder. PLOS ONE 9(2): e88785. c) Figure 1 from Young KD, Siegle, GJ, Zotev V, Phillips R, Misaki M, Yuan H, et al. (2017) Randomized Clinical Trial of Real-Time fMRI Amygdala Neurofeedback for Major Depressive Disorder: Effects on Symptoms and Autobiographical Memory Recall American Journal of Psychiatry 174(8):748–755.