Training volitional control of the theory of mind network with real-time fMRI neurofeedback.

Is there a way improve our ability to understand the minds of others? Towards addressing this question, here, we conducted a single-arm, proof-of-concept study to evaluate whether real-time fMRI neurofeedback (rtfMRI-NF) from the temporo-parietal junction (TPJ) leads to volitional control of the neural network subserving theory of mind (ToM; the process by which we attribute and reason about the mental states of others). As additional aims, we evaluated the strategies used to self-regulate the network and whether volitional control of the ToM network was moderated by participant characteristics and associated with improved performance on behavioral measures. Sixteen participants underwent fMRI while completing a task designed to individually-localize the TPJ, and then three separate rtfMRI-NF scans during which they completed multiple runs of a training task while receiving intermittent, activation-based feedback from the TPJ, and one run of a transfer task in which no neurofeedback was provided. Region-of-interest analyses demonstrated volitional control in most regions during the training tasks and during the transfer task, although the effects were smaller in magnitude and not observed in one of the neurofeedback targets for the transfer task. Text analysis demonstrated that volitional control was most strongly associated with thinking about prior social experiences when up-regulating the neural signal. Analysis of behavioral performance and brain-behavior associations largely did not reveal behavior changes except for a positive association between volitional control in RTPJ and changes in performance on one ToM task. Exploratory analysis suggested neurofeedback-related learning occurred, although some degree of volitional control appeared to be conferred with the initial self-regulation strategy provided to participants (i.e., without the neurofeedback signal). Critical study limitations include the lack of a control group and pre-rtfMRI transfer scan, which prevents a more direct assessment of neurofeedback-induced volitional control, and a small sample size, which may have led to an overestimate and/or unreliable estimate of study effects. Nonetheless, together, this study demonstrates the feasibility of training volitional control of a social cognitive brain network, which may have important clinical applications. Given the study's limitations, findings from this study should be replicated with more robust experimental designs.

Features of dissociation differentially predict antidepressant response to ketamine in treatment-resistant depression.

BACKGROUND: Ketamine induces rapid and robust antidepressant effects, and many patients also describe dissociation, which is associated with antidepressant response. This follow-up study investigated whether antidepressant efficacy is uniquely related to dissociative symptom clusters. METHODS: Treatment-resistant patients with major depressive disorder (MDD) or bipolar disorder (BD) (n = 126) drawn from three studies received a single subanesthetic (0.5 mg/kg) ketamine infusion. Dissociative effects were measured using the Clinician-Administered Dissociative States Scale (CADSS). Antidepressant response was measured using the 17-item Hamilton Depression Rating Scale (HAM-D). A confirmatory factor analysis established the validity of CADSS subscales (derealization, depersonalization, amnesia), and a general linear model with repeated measures was fitted to test whether subscale scores were associated with antidepressant response. RESULTS: Factor validity was supported, with a root mean square error of approximation of .06, a comparative fit index of .97, and a Tucker-Lewis index of .96. Across all studies and timepoints, the depersonalization subscale was positively related to HAM-D percent change. A significant effect of derealization on HAM-D percent change was observed at one timepoint (Day 7) in one study. The amnesia subscale was unrelated to HAM-D percent change. LIMITATIONS: Possible inadequate blinding; combined MDD/BD datasets might have underrepresented ketamine's antidepressant efficacy; the possibility of Type I errors in secondary analyses. CONCLUSIONS: From a psychometric perspective, researchers may elect to administer only the CADSS depersonalization subscale, given that it was most closely related to antidepressant response. From a neurobiological perspective, mechanistic similarities may exist between ketamine-induced depersonalization and antidepressant response, although off-target effects cannot be excluded.