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Objective Exposure therapy is an effective treatment for posttraumatic stress disorder (PTSD), but a comprehensive, emotion-focused perspective on how psychotherapy impacts brain function is lacking. Here, we assess changes in brain function following prolonged exposure therapy across three emotional reactivity and regulation paradigms. Methods Individuals with PTSD underwent functional magnetic resonance imaging (fMRI) at rest and while completing three tasks assessing emotional reactivity and regulation. Individuals were then randomized to prolonged exposure treatment (N=36) or waitlist (N=30) and underwent a second scan approximately four weeks following the last treatment session or a comparable waiting period, respectively. Results Treatment-specific changes were observed only during cognitive reappraisal of negative images. Psychotherapy increased lateral frontopolar cortex activity and its connectivity with the ventromedial prefrontal cortex/ventral striatum. Greater increases in frontopolar activation were associated with improvement in hyperarousal symptoms and psychological well-being. The frontopolar cortex also displayed a greater variety of temporal resting state signal pattern changes following treatment. Using concurrent transcranial magnetic stimulation and fMRI in healthy participants, we demonstrate the lateral frontopolar cortex exerts downstream influence on the ventromedial prefrontal cortex/ventral striatum. Conclusions Changes in frontopolar function during deliberate regulation of negative affect is one key mechanism of adaptive psychotherapeutic change in PTSD. Given that: a) frontopolar connectivity with ventromedial regions during emotion regulation is enhanced by psychotherapy; and b) frontopolar cortex exerts downstream influence on ventromedial regions in healthy individuals, these findings inform a novel conceptualization of how psychotherapy works and identify a promising target for stimulation-based therapeutics.

BackgroundBoth major depressive disorder (MDD) and post-traumatic stress disorder (PTSD) are characterized by alterations in intrinsic functional connectivity. Here we investigated changes in intrinsic functional connectivity across these disorders as a function of cognitive behavioral therapy (CBT), an effective treatment in both disorders.Methods53 unmedicated right-handed participants were included in a longitudinal study. Patients were diagnosed with PTSD (n = 18) and MDD (n = 17) with a structured diagnostic interview and treated with 12 sessions of manualized CBT over a 12-week period. Patients received an MRI scan (Siemens 3 T Trio) before and after treatment. Longitudinal functional principal components analysis (LFPCA) was performed on functional connectivity of the bilateral amygdala with the fronto-parietal network. A matched healthy control group (n = 18) was also scanned twice for comparison.ResultsLFPCA identified four eigenimages or principal components (PCs) that contributed significantly to the longitudinal change in connectivity. The second PC differentiated CBT-treated patients from controls in having significantly increased connectivity of the amygdala with the fronto-parietal network following CBT.LimitationsAnalysis of CBT-induced amygdala connectivity changes was restricted to the a priori determined fronto-parietal network. Future studies are needed to determine the generalizability of these findings, given the small and predominantly female sample.ConclusionWe found evidence for the hypothesis that CBT treatment is associated with changes in connectivity between the amygdala and the fronto-parietal network. CBT may work by strengthening connections between the amygdala and brain regions that are involved in cognitive control, potentially providing enhanced top-down control of affective processes that are dysregulated in both MDD and PTSD.

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Many individuals in need of mental health services do not currently receive care. Scalable programs are needed to reduce the burden of mental illness among those without access to existing providers. Digital interventions present an avenue for increasing the reach of mental health services. These interventions often rely on paraprofessionals, or coaches, to support the treatment. Although existing programs hold immense promise, providers must ensure that treatments are delivered with high fidelity and adherence to the treatment model. In this paper, we first highlight the tension between the scalability and fidelity of mental health services. We then describe the design and implementation of a peer-to-peer coach training program to support a digital mental health intervention for undergraduate students within a university setting. We specifically note strategies for emphasizing fidelity within our scalable framework, including principles of learning theory and competency-based supervision. Finally, we discuss future applications of this work, including the potential adaptability of our model for use within other contexts.

Brain stimulation is used clinically to treat a variety of neurological and psychiatric conditions. The mechanisms of the clinical effects of these brain-based therapies are presumably dependent on their effects on brain networks. It has been hypothesized that using individualized brain network maps is an optimal strategy for defining network boundaries and topologies. Traditional non-invasive imaging can determine correlations between structural or functional time series.However, they cannot easily establish hierarchies in communication flow as done in non-human animals using invasive methods. In the present study, we interleaved functional MRI recordings with non-invasive transcranial magnetic stimulation in the attempt to map causal communication between the prefrontal cortex and two subcortical structures thought to contribute to affective dysregulation: the subgenual anterior cingulate cortex (sgACC) and the amygdala. In both cases, we found evidence that these brain areas were engaged when TMS was applied to prefrontal sites determined from each participant's previous fMRI scan. Specifically, after transforming individual participant images to within-scan quantiles of evoked TMS response, we modeled the average quantile response within a given region across stimulation sites and individuals to demonstrate that the targets were differentially influenced by TMS. Furthermore, we found that the sgACC distributed brain network, estimated in a separate cohort, was engaged in response to sgACC focused TMS and was partially separable from the proximal default mode network response. The amygdala, but not its distributed network, responded to TMS. Our findings indicate that individual targeting and brain response measurements usefully capture causal circuit mapping to the sgACC and amygdala in humans, setting the stage for approaches to noninvasively modulate subcortical nodes of distributed brain networks in clinical interventions and mechanistic human neuroscience studies.important step forward that capitalizes on recent work suggesting that network representations in the brain are highly individual, as well as evidence that different networks may exist at the same anatomical location across subjects (23).There is justification for looking at the sgACC and amygdala regions individually, though both of these regions communicate with distributed networks likely relevant to complex mental operations subserving emotion and its dysregulation in affective illness. Therefore, we generated network masks for the sgACC and amygdala individually using our processing pipeline applied to a large independent healthy cohort from a publicly available source.Among sites accessible to TMS while participants laid on their backs in the scanner, we considered areas of left hemisphere prefrontal cortex with high resting connectivity to the subcortical target of interest as stimulation sites. There were multiple sites for each participant for each target (each at least 1.47cm apart and none within 2cm of another target immediately preced...

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Prior research has shown that during development, there is increased segregation between, and increased integration within, prototypical resting-state functional brain networks. Functional networks are typically defined by static functional connectivity over extended periods of rest. However, little is known about how time-varying properties of functional networks change with age. Likewise, a comparison of standard approaches to functional connectivity may provide a nuanced view of how network integration and segregation are reflected across the lifespan. Therefore, this exploratory study evaluated common approaches to static and dynamic functional network connectivity in a publicly available dataset of subjects ranging from 8 to 75 years of age. Analyses evaluated relationships between age and static resting-state functional connectivity, variability (standard deviation) of connectivity, and mean dwell time of functional network states defined by recurring patterns of whole-brain connectivity. Results showed that older age was associated with decreased static connectivity between nodes of different canonical networks, particularly between the visual system and nodes in other networks. Age was not significantly related to variability of connectivity. Mean dwell time of a network state reflecting high connectivity between visual regions decreased with age, but older age was also associated with increased mean dwell time of a network state reflecting high connectivity within and between canonical sensorimotor and visual networks. Results support a model of increased network segregation over the lifespan and also highlight potential pathways of top-down regulation among networks.