Resting-State Connectivity and Response to Psychotherapy Treatment in Adolescents and Adults With OCD: A Randomized Clinical Trial

A total of 116 patients (68 female; 54 adolescents; 60 medicated) with OCD and usable resting-state functional MRI (fMRI) and OCD symptom assessment data and 63 healthy control volunteers (40 female; 32 adolescents) were included in the present analyses. Approximately 52% of the patients were taking a serotonergic medication. Other clinical and demographic details are provided in Table 1 and in Tables S1 and S2 in the online supplement. Participants were recruited from outpatient psychiatry programs and an online research registry at the University of Michigan Health System, social media and community advertisements, and referrals from community clinicians. Patients in the adolescent subgroup were required to be 12–17 years old, and those in the adult subgroup were required to be 24–45 years old; these age ranges were selected to represent more plastic (adolescent) relative to more stable (adult) periods of brain development. Patients were required to have experienced symptom onset before age 16 and to be experiencing at least a moderate level of symptom severity at baseline (i.e., ≥16 on the child or standard version of the Yale-Brown Obsessive Compulsive Scale [Y-BOCS] [33, 34]). Healthy control subjects had no lifetime history of any psychiatric disorder except simple phobias and had no family history of OCD. Written informed consent or assent was obtained from all patients or legal guardians, in accordance with procedures reviewed and approved by the Institutional Review Board of the University of Michigan. Full details on exclusionary criteria and noncompleters are provided in a CONSORT chart in the online supplement. We previously reported an analysis of task-based fMRI data in a subset of this sample (26). The present report is the first analysis of the resting-state fMRI data.

Patients were randomized using an in-house block randomization procedure to receive either 12 weeks of individual ERP or 12 weeks of individual SMT that focused on coping skills. This assignment was stratified based on medication status, gender, and age group. Full details of the treatment protocols are provided in the online supplement. Assessments of OCD symptom severity were performed at baseline (mean=1 week of treatment, SD=2 days), midtreatment (mean=6 weeks of treatment, SD=5 days), and posttreatment (mean=12 weeks of treatment, SD=5 days) by an independent rater who was blind to treatment group assignment. Prior to randomization, patients underwent MRI scanning, on average within 12 days (SD=7 days) of beginning therapy.

In order to define regions of interest (ROIs) for the resting-state analysis, we used an incentive flanker task, which is a stimulus-response compatibility task, that robustly activates the FPN and CON and deactivates the DMN (26). Striato-thalamic regions were selected based on published coordinates (35, 36). The full details of data acquisition, processing, and ROI selection are provided in Table S3 in the online supplement. For each region, a sphere with a 4.35-mm radius was placed around central coordinates based on either activations during task-based fMRI in the same subjects (cognitive-control and DMN regions) or published studies (striato-thalamic regions). Mean blood-oxygen-level-dependent time series were then extracted for each ROI and correlated to create an ROI-ROI connectivity matrix for each subject. Diagonal and duplicate cells were removed, and Fisher’s r-to-z transformation was applied to the Pearson correlation coefficients at each remaining cell of the resultant matrices. Repeated-measures linear mixed-effects models with restricted maximum likelihood were used to examine the effects of ROI connectivity on symptom improvement. All models were implemented in the nlme package for R (37), included a random intercept for participant, and controlled for motion (mean framewise displacement), gender, treatment adherence (see the online supplement), and medication status (on vs. off medication). Results for all analyses were the same when covarying for maximum framewise displacement and number of frames removed due to motion scrubbing. Corrections for multiple comparisons were performed using the Benjamini-Hochberg false discovery rate (FDR) based on the number of ROI-ROI connections (N=190).

In model 1, we examined whether the effect of baseline connectivity on Y-BOCS scores differed across psychotherapy groups. Here, a week-by-connectivity-by-psychotherapy group interaction term, controlling for age group, was the predictor of interest. In each model, week was entered as the exact therapy week when the assessment took place (e.g., week 1, 6, or 12), such that the resulting beta values can be interpreted as predicted change in the Y-BOCS score per week, although participants underwent only three assessments. In model 2, we examined whether baseline connectivity was associated with symptom improvement across psychotherapy groups; here, the predictor of interest was the interaction of treatment week and connectivity, controlling for psychotherapy group and age group. Effects of age group were explored in models 3 and 4. Model 3 examined whether the association between baseline connectivity and Y-BOCS scores changed as a function of age group, controlling for psychotherapy group. Model 4 examined the four-way interaction between week, baseline connectivity, psychotherapy group, and age group. Significant interactions were explored using simple slope analyses. Full model syntax and equations are provided in the online supplement. Finally, the ROI-ROI connections associated with significant symptom improvement (i.e., those showing a significant negative slope associated with Y-BOCS scores from week 1 to week 12) were compared with the same connections in the healthy control group to examine connectivity differences as a function of OCD diagnosis (see the online supplement).

The primary clinical outcomes are presented in Table 1. Patients treated with ERP showed a significantly larger decrease in symptoms than those treated with SMT (η_p²=0.18, 95% CI=0.11, 0.25). Both psychotherapy groups showed a significant decrease in symptoms over time, although the change was clinically significant (38, 39) only in the ERP group (ERP group: η_p²=0.69, 95% CI=0.61, 0.74; SMT group: η_p²=0.21, 95% CI=0.11, 0.31). There were no effects of age on symptom improvement in either group.

Knowing, prior to treatment initiation, what factors are associated with a greater symptom improvement could enhance the development of treatments and therapeutic outcomes (e.g., through priming interventions that are delivered before ERP to maximize the likelihood of treatment response). Previous fMRI studies have been unable to identify treatment-specific predictors because of the lack of an active control treatment. In our study, ERP was associated with greater symptom improvement in patients with weak connectivity rather than strong positive connectivity of the vmPFC to the thalamus and caudate, whereas SMT was associated with a greater symptom improvement if the patients showed the reverse pattern—strong positive connectivity rather than weak connectivity. We had expected that aberrant network connections would be important for predicting treatment response, but the absence of differences in the connectivity of our selected network nodes between the treatment and healthy control groups provides potentially important information. While it is difficult to draw firm conclusions from negative results, our findings suggest that network connections involved in treatment response may not be the same network connections related to the psychopathology. One implication may be that enhancing target network function, for example, through brain stimulation or neurofeedback training, might not focus on the regions that exhibit differences from the normative signal. Instead, it may be more advantageous to boost activity in “healthy circuits” to optimize treatment response.

Our findings suggest that ERP and SMT may rely on differences in the organization of vmPFC-subcortical connectivity, which might suggest two different approaches to treatment. SMT seeks to lower anxiety levels in general, whereas in ERP, a therapist guides a patient to tolerate progressively greater levels of anxiety-inducing situations. This vmPFC-striato-thalamic circuit is thought to be involved in affectively coding certain behavioral programs, and if circuit strength reflects the “attachment” to compulsive behaviors, patients with relatively lower vmPFC-subcortical connectivity may have better chances of engaging with the extinction-generating exercises of ERP. On the other hand, those with stronger affective attachment to their compulsive behaviors may respond well to simple relaxation strategies. While speculative and in need of replication, the findings point to potentially different mechanisms underlying the two types of treatment.

Contrary to our hypotheses, connections of cingulo-opercular and frontoparietal regions were associated with symptom improvement with both ERP and SMT. Greater connectivity between cognitive-control regions and between these regions and the putamen predicted a steeper reduction in OCD symptoms irrespective of treatment modality. Regions of the CON, such as the medial SMA and right anterior insula, are proposed to orchestrate recruitment of FPN regions in a flexible manner in line with ongoing task demands (40). Previous task-based fMRI studies suggest that inefficiency of CON-based signaling to recruit FPN regions during cognitive tasks in patients with OCD may lead to the impaired cognitive control observed in those with the disorder (31). Greater connectivity of CON and FPN regions could therefore represent greater functioning in these networks, which in turn may support self-regulatory abilities in patients who respond well to psychotherapy. Given the involvement of the putamen in motor control, action selection, and habit formation (41, 42), greater connectivity of cognitive-control regions with the putamen could indicate better functioning of networks involved in top-down control over habitual patterns, which would facilitate the ability to resist compulsions during treatment and engage in goal-directed behavior (43); in the absence of relevant task data, this interpretation is speculative.

Importantly, we report additional predictors of symptom improvement that were developmentally sensitive and not treatment specific. These predictors predominantly involved connectivity between FPN regions (e.g., the dlPFC and parietal lobes) and the nucleus accumbens, which were more positively associated with symptom improvement in adolescents than in adults across both types of therapy. The NAc is widely recognized as a key node of the reward system (44). Additionally, ventral striatal connectivity with the prefrontal cortex is associated with better cognitive control and decision making in healthy adolescents (45, 46). This connectivity also plays a regulatory role during cognitive reappraisal in healthy young adults (47). Thus, while speculative, enhanced FPN-NAc communication may promote motivation and cognitive control functions that are necessary to make positive behavioral changes in adolescents with OCD. In contrast, in adults, responses to both ERP and SMT were predicted by greater connectivity within the FPN and between FPN regions and the dorsal putamen. Connectivity within the FPN increases during healthy adolescence to support improved cognitive control function (48), while a greater influence of FPN regions, particularly the dlPFC, over putamen-instantiated motor output has been theorized as protective in OCD (49). Together, these findings support the notion that NAc connectivity is particularly important for adaptive functioning during adolescence compared with other age ranges, while the neural substrates underlying cognitive control and motor output may be more closely tied to adaptive outcomes in adulthood (45, 48).

Several limitations should be kept in mind. The network nodes that were selected for the connectivity analyses were defined by a task that engages cognitive control and by published studies, which were used to identify nodes thought to be important for OCD based on the tripartite and CSTC models. As we examined only connectivity, not task-evoked activation, the functional significance of the connections might be different in the context of activated, engaged networks. Indeed, in an interim analysis of a partial data set drawn from that presented here, we found additional task-evoked predictors of treatment response (26). Furthermore, the absence of baseline differences from our normative sample does not preclude the existence of other connections that may differ between the groups outside of the selected ROIs. Another limitation of our study is the absence of a waiting list condition to demonstrate that the findings common to both ERP and SMT are due to an intervention and not just time. Future studies could investigate differences between other OCD treatments (e.g., medications) to determine whether our findings are specific to psychotherapy. Future studies could also examine baseline symptom severity as a treatment moderator, which could not be examined in the context of the present mixed model with three time points.

With regard to our developmental findings, those in the adolescent group showed more movement during the resting-state scan than those in the adult group. However, we controlled for motion in all analyses, and motion was unrelated to treatment outcomes. To compare across groups, it was necessary to use the same brain template for normalization. While total brain volume remains relatively stable from adolescence to young adulthood, the use of an adult brain template could have contributed to age-related findings. Additionally, as all participants were required to have a childhood onset of symptoms, based on research demonstrating potential phenomenological differences between childhood- and adult-onset OCD, longer illness duration in the adult group could have partially contributed to our findings. Furthermore, we did not explore pubertal status in the adolescent group, which may be a more sensitive measure than chronological age, and future work could examine the period of emerging adulthood. Additionally, our sample was predominantly Caucasian, and future studies would benefit from examining racial minorities. Antidepressant medications may affect connectivity within CSTC loops; however, medication status was controlled for in all analyses, and post hoc analyses (see Tables S8–S11 in the online supplement) demonstrated no significant brain-by-medication status interactions or any relationship between medication status and baseline rsFC. Lastly, preregistration is an important tool for improving reproducibility in the neuroimaging sciences; the analyses reported here were not preregistered, and follow-up work with preregistered analyses is required to confirm the present results.

We examined rsFC predictors of symptom improvement in response to ERP for OCD in adolescents and adults. Our design included an active control therapy, namely, SMT, which allowed us to examine the specificity of neural predictors of response to ERP. Across age groups, we found that vmPFC-striato-thalamic circuitry was uniquely associated with symptom improvement with ERP, while connectivity of cognitive control regions was associated with symptom improvement irrespective of treatment type. Additionally, ventral striatal connectivity distinguished treatment response in adolescents compared with adults. Our findings help delineate the neural circuitry that supports response to psychotherapy based on treatment modality and suggest that developmental differences are an important factor to consider when examining the neural mechanisms of psychotherapy.