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•Volitional control of ToM network observed.•Volitional control associated with thinking about social experiences.•Weak evidence that volitional control may impact behavior.•Potential applications to clinical groups with social difficulties. 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.

Social anhedonia is a well-established symptom of schizophrenia-spectrum disorders (SSDs), but its etiology remains unknown. Recent studies suggest that one’s ability to accurately predict future affect in social situations, or social affective forecasting (SAF) accuracy, is related to social anhedonia. Although existing studies have linked deficits in anticipatory social pleasure to social anhedonia, little is understood about the neural basis of this dysfunction. Over the past decade, however, the default mode network (DMN)—a network of brain regions responsible for self-relevant, future oriented thoughts—has been implicated in SSDs. Given that the DMN might differentially give rise to processes involved in anticipatory pleasure, deficits in the DMN could contribute to SAF accuracy, and consequently, social anhedonia. Using a sample of individuals with and without SSDs, I examined relationships between SAF, social anhedonia, and functional connectivity within the DMN. To measure SAF accuracy, participants completed a daily diary (Study 1), followed by fMRI scanning to assess functional connectivity within three predetermined subsystems of the DMN (Study 2). I found that individuals with SSD experience poorer SAF accuracy when predicting negative emotions for future social interactions, which was related to social anhedonia. Further, among the different DMN subsystems examined, individuals with SSDs showed hypoconnectivity within the midline core relative to those without SSDs. Across the entire sample, hypoconnectivity in the midline core was associated with poorer SAF accuracy of negative emotions. Taken together, reduced functional connectivity within specific regions of the DMN could serve as a neurobiological target for improving SAF accuracy, and ultimately ameliorating social anhedonia.

Abstract Individuals with a schizophrenia spectrum disorder (SSD) have difficulties with social information processing, including mental state attribution, or “theory of mind” (ToM). Prior work has shown that these difficulties are related to disruption to the neural network subserving ToM. However, few such studies utilize naturalistic stimuli that are more representative of daily social interaction. Here, SSD and non-SSD individuals underwent fMRI while watching The Office to better understand how the ToM network responds to dynamic and complex social information, such as socially awkward moments. We find that medial prefrontal cortex tracks less with moment-to-moment awkwardness in SSD individuals. We also find a broad decrease in functional connectivity in the ToM network in SSD. Furthermore, neural response during awkward moments and functional connectivity was associated with psychotic experiences and social functioning. These results suggest that during naturalistic, socially awkward moments where mental state attribution is critical, individuals with SSD fail to recruit key regions of the ToM network, possibly contributing to decreased social understanding and impaired functioning.

Social anhedonia (SA) is a trait-like phenomenon observed across schizophrenia-spectrum disorders (SSDs). While in-the-moment social pleasure experiences are intact in SSDs, anticipatory pleasure experiences may be disrupted. Thus, the prediction of future emotions in social situations, or social affective forecasting (SAF), may play a role in SA. Therefore, we utilized daily diary methods to examine SAF in SSD and the association between SAF and SA in 34 SSD and 43 non-SSD individuals. SAF was calculated as the absolute difference between anticipatory and consummatory ratings of 13 positive and negative emotions for daily social interactions reported across eight days. Results suggest that individuals with SSDs are less accurate in forecasting negative, but not positive emotions, for future social interactions. Further, poorer forecasting accuracy of negative emotions were associated with elevated levels of SA and lower social pleasure. Together, these data suggest that inaccuracies in forecasting negative emotions may be a worthwhile intervention target for reducing SA in SSDs.