Acquired self-control of insula cortex modulates emotion recognition and brain network connectivity in schizophrenia

Abstract

Real-time functional magnetic resonance imaging (rtfMRI) is a novel technique that has allowed subjects to achieve self-regulation of circumscribed brain regions. Despite its anticipated therapeutic benefits, there is no report on successful application of this technique in psychiatric populations. The objectives of the present study were to train schizophrenia patients to achieve volitional control of bilateral anterior insula cortex on multiple days, and to explore the effect of learned self-regulation on face emotion recognition (an extensively studied deficit in schizophrenia) and on brain network connectivity. Nine patients with schizophrenia were trained to regulate the hemodynamic response in bilateral anterior insula with contingent rtfMRI neurofeedback, through a 2-weeks training. At the end of the training stage, patients performed a face emotion recognition task to explore behavioral effects of learned self-regulation. A learning effect in self-regulation was found for bilateral anterior insula, which persisted through the training. Following successful self-regulation, patients recognized disgust faces more accurately and happy faces less accurately. Improvements in disgust recognition were correlated with levels of self-activation of right insula. RtfMRI training led to an increase in the number of the incoming and outgoing effective connections of the anterior insula. This study shows for the first time that patients with schizophrenia can learn volitional brain regulation by rtfMRI feedback training leading to changes in the perception of emotions and modulations of the brain network connectivity. These findings open the door for further studies of rtfMRI in severely ill psychiatric populations, and possible therapeutic applications.

Figure 1

Experimental protocol.

Figure 2

Posttraining face emotion recognition evaluation (Day 5). Experimental design for the evaluation of emotional faces displaying an upregulation and a baseline (nonregulation) test. Upregulation and baseline blocks were cued with red and blue backgrounds, respectively.

Figure 3

Group analysis of BOLD signal change in left and right anterior insula, across the 4 days of rtfMRI training and the emotion recognition evaluation. Blue bars represent the Fisher Score (and standard error) during training sessions. The black bars represent the transfer sessions, and the red bars represent the mean of the FS (and standard error) of the sessions of the emotion recognition evaluation. *P < 0.05, for the Wilcoxon signed‐rank test comparing the values of each session with the first session of training.

Figure 4

Percentage of correct identification (mean and standard error) for disgust and happy faces during the emotion recognition evaluation.

Figure 5

Group analysis of effective connectivity changes due to rtfMRI training using Granger causality modeling (GCM). MidFG: middle frontal gyrus (−50, 2, 42; MNI center coordinates x,y,z), MPFC: medial prefrontal cortex (−6, 48, 40), ACC: anterior cingulate cortex (−3,7,25), L Insula (−46,10,0), R Insula (46,0,0), Amygdala (−18,−10,−14), SMG: supra marginal gyrus (−66,−26,25), precuneus (−10,−49, 40). (A) Directed influences of the emotional network during upregulation, in the weakest and the strongest regulation sessions. Red arrows indicate bidirectional influences between ROIs. (B) Number of outgoing and incoming connections of each ROI of the emotional network during upregulation. Outflow: number of outgoing connections from each of the ROIs. Inflow: number of incoming connections to each of the ROIs.