Development of Posterior Medial Frontal Cortex Function in Pediatric Obsessive-Compulsive Disorder

Accepted Manuscript Development of Posterior Medial Frontal Cortex Function in Pediatric ObsessiveCompulsive Disorde Kate Dimond Fitzgerald, MD, Yanni Liu, PhD, Timothy Johnson, PhD, Jason Moser, PhD, Rachel Marsh, PhD, Gregory L. Hanna, MD, Stephan F. Taylor, MD PII:

S0890-8567(18)30167-9

DOI:

10.1016/j.jaac.2018.02.016

Reference:

JAAC 2094

To appear in:

Journal of the American Academy of Child & Adolescent Psychiatry

Received Date: 22 August 2017 Revised Date:

18 February 2018

Accepted Date: 25 February 2018

Please cite this article as: Fitzgerald KD, Liu Y, Johnson T, Moser J, Marsh R, Hanna GL, Taylor SF, Development of Posterior Medial Frontal Cortex Function in Pediatric Obsessive-Compulsive Disorde, Journal of the American Academy of Child & Adolescent Psychiatry (2018), doi: 10.1016/ j.jaac.2018.02.016. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Development of Posterior Medial Frontal Cortex Function in Pediatric Obsessive-Compulsive Disorder

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RH = pMFC in Pediatric OCD

Kate Dimond Fitzgerald, MD, Yanni Liu, PhD, Timothy Johnson, PhD, Jason Moser, PhD,

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Rachel Marsh, PhD, Gregory L. Hanna, MD, Stephan F. Taylor, MD

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Editorial Clinical Guidance Supplemental Content CME

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Accepted April 13, 2018

Drs. Fitzgerald, Liu, Johnson, Hanna, and Taylor are with the University of Michigan School of

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Public Health. Dr. Moser is with Michigan State, and Dr. Marsh is with Columbia University, NY.

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This research was supported by NIMH grants K23-MH082176 (KDF) and R01-MH102242 (KDF/SFT), the Dana Foundation (KDF), NARSAD (KDF), and the Todd Ouida Memorial Children’s Fund (KDF).

This study was presented in symposia at the American Academy of Child and Adolescent Psychiatry, New York, NY, Oct. 24-29, 2016; the American College of Neuropsychopharmacology, Hollywood, FL, Dec. 4-8, 2016; and the Society of Biological Psychiatry, San Diego, CA, May 18-20, 2017.

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Dr. Johnson served as the statistical expert for this research. Disclosure: Dr. Taylor has received research support through Otsuka/Vanguard Research

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Group and Boehringer-Ingelheim. Drs. Fitzgerald, Liu, Johnson, Moser, Marsh, and Hanna report no biomedical financial interests or potential conflicts of interest.

Correspondence to Kate D. Fitzgerald, MD, 4250 Plymouth Road, Ann Arbor, MI 48109; email:

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[email protected]

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Abstract Objective: Abnormal engagement of the posterior medial frontal cortex (pMFC) occurs during performance monitoring in obsessive-compulsive disorder (OCD), including in pediatric patients.

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Yet, the development of pMFC function in OCD-affected youth remains poorly understood. Method: Sixty-nine patients with pediatric OCD and 72 healthy controls (HC), 8 to 19 years, were scanned during the Multisource Interference Task (MSIT). The effects of group, age,

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performance and interactions on pMFC response to errors and interference were tested in

region of interest ROI) and whole brain analyses. Secondary analyses considered bilateral

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anterior insula/frontal operculum (aI/fO), given the contribution of these regions with pMFC to a cingulo-opercular network (CON) for task control (e.g., error- and interference-processing). Results: Error-related pMFC activity was greater for OCD than HC, increased with age in OCD, but decreased with age in HC. Greater pMFC activation associated with better performance in HC, but not OCD. In patients, greater pMFC activation to errors associated with lower OCD

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severity. Altered error-related activation and performance associations were also observed in right aI/fO in OCD, while left aI/fO response to interference associated with lower OCD severity. Conclusion: Atypical increase of error-related pMFC activation with age in pediatric OCD

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suggests altered development of pMFC function during the early course of illness. Greater pMFC activation with better performance in HC, and with age and lower symptom severity in

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patients suggests an adaptive function of heightened pMFC response to errors that could be further enhanced (e.g., via cognitive training) to improve outcomes in OCD from the early course of illness.

Keywords: pediatric obsessive-compulsive disorder, performance monitoring, task control, cingulo-opercular network, development

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Introduction: Abnormal brain response to performance monitoring in obsessive compulsive disorder (OCD) is elicited by simple cognitive tasks not intended to provoke symptoms, suggesting a

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core process in the pathophysiology of illness.1 Performance monitoring involves detection of errors and interference between competing response options to enable behavioral

adjustments,2 and abnormalities of this process could underlie the repetitive thoughts and

behaviors of OCD.1 OCD often emerges in childhood or adolescence,3 a period in which neural

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networks for performance monitoring mature in healthy youth4 and performance monitoring

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abnormalities can be observed in those affected by OCD.5-7 Yet, despite important implications for early treatment, the development of performance monitoring dysfunction in OCD remains poorly understood.1

In healthy adults, performance monitoring engages posterior medial frontal cortex (pMFC, encompassing dorsal anterior cingulate and pre-supplementary motor area) and

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bilateral anterior insula/frontal operculum (aI/fO).8 These regions co-activate during cognitively demanding tasks and remain functionally connected at rest, defining a “cingulo-opercular network” (CON) for task control.8 The CON is widely held to mediate selection of salient

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information from internal and external inputs to guide ongoing behavior, including detection of errors and interference for performance monitoring.8,9 In adults with OCD, several fMRI studies

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have shown pMFC hyperactivation (dorsal anterior cingulate, dACC and/or pre-supplementary motor area, pre-SMA) during performance monitoring10-15 and electrophysiologic research has consistently demonstrated increased error-related negativity, generated by the dACC (amongst other regions).16 Hyperactivation of the aI/fO to errors also occurs in adult patients,17 implicating broader CON function in OCD. Neuroimaging studies of performance monitoring in pediatric OCD suggest abnormal pMFC engagement, but are inconsistent regarding the direction of the abnormality, with one study reporting increased activation,5 and another reporting the reverse in patients compared to 2

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healthy youth.18 Other studies report no group differences.6,19 These inconsistencies may relate to small sample sizes (n’s < 25 per group), which increase variability and reduce experimental power.20 In addition, pediatric (and adult) OCD cohorts often include patients

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taking selective serotonin reuptake inhibitors, which impact neural engagement during performance monitoring21 and may alter neurofunctional maturation.22

Overall, this literature implicates atypical engagement of the CON, particularly pMFC,

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during performance monitoring in OCD. However, no fMRI study has investigated whether the relation of age with CON response to performance monitoring differs between patients with

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pediatric OCD and healthy youth. Thus, the aim of this study was to test effects of group and group-by-age interactions on activation of the pMFC (primary regions of interest, ROI) and aI/fO (secondary ROIs) during performance monitoring in youth with OCD compared to matched controls. Group-by-performance interactions were assessed to test for differences in the relation of activation with behavioral output. In addition, we sought to clarify whether

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performance monitoring function relates to symptom severity in young patients, as this has not been the case in adults.10,11,13,17 Finally, we capitalized on our large sample of youth with OCD

Method: Participants:

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to explore the effects of medication status on activation.

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Seventy-five patients with pediatric OCD (13.8 ± 2.8 years) and 75 healthy controls (HC, 13.8 ± 3.4 years) were assessed by structured interview with the Kiddie-Schedule for Affective Disorders-Present and Lifetime Version23 and, in patients, the Children’s Yale-Brown Obsessive Compulsive Scale (CY-BOCS).24 Nine participants failed to provide useable data (Supplement 1, available online), yielding 69 patients and 72 HCs for interference analyses (i.e., correct resolution of response competition). For error analyses, at least 5 errors per subject were required,25 leaving 51 patients and 51 HCs. OCD was the primary source of impairment; of the 69 patients, 49 had one to three less severe comorbid diagnoses including anxiety (n = 27), tic 3

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(n = 18), and/or attentional (n = 9) disorders or subclinical depressive symptoms (n = 13) (Table S1, available online), consistent with previously described clinical samples.26 Major depressive, autism spectrum, psychotic, or substance use disorders were excluded. HCs had no current or

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prior history of psychiatric illness and no first degree relatives with OCD. Among patients, thirtyfour were medicated, primarily with selective serotonin reuptake inhibitors (see Supplement 1, available online). Task:

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Participants performed an event-related version of the MSIT5 (Figure S1, available online).

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They identified the unique number among three numbers, “1”, “2” and “3” by pressing a button with the first (index), second (middle) and third (ring) fingers, respectively. On incongruent trials (Inc, e.g., “331”), the unique number was positioned incongruently (i.e., “1” in the 3rd position), flanked by distracting numbers (“33”). On congruent trials (Con, e.g., “100”), the unique number was positioned congruently (“1” in the first position), flanked by zeroes. To ensure task

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understanding and minimize performance variability, participants were trained to achieve 7090% accuracy on incongruent trials. During scanning, 300 trials (3000 msec/each) were presented over 5 runs for a total of 15 minutes (120 Inc, 120 Con, 60 Fixation) in fixed order.

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MRI acquisition and pre-processing:

A 3.0 T GE Signa scanner (GE Healthcare, Waukesha, WI) was used to collect T2* reverse

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spiral images and a low resolution axial T1 for coregistration.27 A high resolution T1-weighted SPGR was acquired for anatomic normalization.27 Functional data were pre-processed in SPM8 (Statistical Parametric Mapping, Wellcome Trust Centre, London, United Kingdom). Raw data were slice-time corrected and realigned to the tenth image acquired. Realignment parameters were retained for inclusion as regressors in first-level analyses and to calculate mean framewise displacement, a summary of subject motion.28 Once coregistered, the highresolution SPGR was segmented using the VBM8 toolbox {http://dbm.neuro.uni-jena.de/vbm}, normalized using high dimensional DARTEL normalization29, and used to warp functional 4

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images into common stereotactic space (Montreal Neurological Institute; MNI). Normalized functional data were smoothed with a 5-mm Gaussian kernel. Analysis:

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Behavioral: Linear regression was used to test effects of age, group (OCD, HC), and age-by-group interactions on performance. Separate models were run for incongruent and congruent response times (RT) and accuracy.

Functional MRI: Functional data were analyzed using a standard random effects

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analysis30 in SPM8. At the first level, incongruent correct, congruent correct, incongruent

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incorrect and congruent incorrect trials were modeled against fixation trials as implicit baseline; omission errors were regressed from the model. Six realignment parameters and their first derivatives were regressed to remove motion effects. Contrast maps were constructed of incongruent versus congruent correct trials for interference, and incorrect versus correct incongruent trials for errors. Single subject contrasts were entered into second-order random

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effects analyses31 to test main effects of errors and interference, across subjects at a height threshold of p < 0.05, corrected for family-wise error (FWE) rates (see Table S2, available online, for main effects).

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Region of interest (ROI) analyses included pMFC as primary ROI, and aI/fO ROIs as secondary. Primary pMFC ROIs were defined by conjunction of main effects for each contrast

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(errors, interference across subjects) with a meta-analysis-based medial frontal cortex ROI (Neurosynth MFC, Supplement 1, available online)32; secondary aI/fO ROIs were defined by contrast-specific main effects (Figures 1A, errors; 2A, interference). Secondary ROIs included pMFC subregions, preSMA and dACC, defined by conjunction of primary pMFC ROIs with Neurosynth posterior and middle MFC zones32 (Supplement 1, Figure S2, available online). Parameter estimates were extracted from ROIs for inclusion in stepwise linear regressions, using backwards elimination, to select predictor variables (group, age, performance, and interactions) --- an unbiased method since voxels of interest were orthogonal to predictors.33 5

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Performance variables were incongruent accuracy and response times for error analyses, and overall accuracy and response times (across conditions) for interference. Framewise displacement (FD) was regressed to control for motion effects.28 Continuous variables were

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mean-centered. Separate analyses tested effects of present symptom severity, as measured by C-YBOCS, in patients. For the primary pMFC ROI, findings were considered significant at p < .05; for the four secondary ROIS (bilateral aI/fO, dACC, preSMA), a more stringent significance threshold was used (p < .013) to correct for multiple comparisons. Finally, given possible

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medication effects,21,22 exploratory analyses considered unmedicated OCD (uOCD), medicated

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OCD (mOCD) and the interactions of these patient sub-groups with age and performance, relative to HC. All analyses were carried out in R, version 3.2.5. Partial residual plots were constructed to show the relationship between a given predictor and response variable given that other predictor variables were also in the model.34

In addition, whole brain analyses were conducted in SPM8, including the same

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regressors as ROI analyses. Contrasts were displayed at a peak threshold of p < .001 (uncorrected) and clusters were considered significant at p < .05, corrected for family wise error (FWE) across whole brain and within pMFC, right and left aI/fO ROIs.

Subjects

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Results:

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There were no significant differences between groups on demographics, performance or in-scanner motion (FD) (Table 1). Comparison of uOCD and mOCD (Table S3, available online) showed a trend towards higher present disease severity in uOCD (p = 0.07); nominally but not significantly greater lifetime severity in mOCD; and, greater reduction from lifetime to present severity in mOCD (p = 0.007). Behavioral Performance There were no differences between OCD and healthy youth in performance (Table 1). Older age associated with faster RT on both trial types (p’s < .001), and with higher accuracy, at 6

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trend-level, on congruent (p =0.07) but not incongruent (p = 0.23) trials. There were no differences in the effect of age on RT or accuracy between groups (p’s > .16). Imaging Analyses

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Error-processing: Primary pMFC ROI Analysis: ROI-based linear regression analyses showed that errorrelated activation of the pMFC was greater for OCD relative to HC (β = .98, p = .02); decreased

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with age in HC, while increasing with age in OCD (β = .39, p =.03, Figure 1B); and, increased with faster RT in HC, but not OCD (β = .005, p = .03, Figure 1C) (Table 2). Exploratory

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analyses showed that greater pMFC activation in patients was driven by mOCD (Table S4, available online). By contrast, altered associations of pMFC activation with age and RT were present in uOCD, but not mOCD, relative to HC (Figure S3A-B; Table S4, available online). Secondary Left and Right aI/fO ROI Analyses: As with pMFC, the typical increase of right aI/fO activation with faster RT was attenuated in OCD relative to HC (β = .006, p = .01,

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Table 2). Exploratory analyses showed this attenuation in uOCD, but not mOCD, relative to HC; in addition, right aI/fO activation was greater in mOCD, but not uOCD, compared to HC (Table S4, available online).

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Secondary dACC and preSMA ROI Analyses: Analysis of pMFC sub-regions suggested several trend-level effects that did not reach significance after correction (Table S5, available

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online). Exploratory analyses showed greater activation in dACC (p = .002) and in pre-SMA at trend level (p = .029) in mOCD, but not uOCD, relative to HC, but suggested altered age (trend: p = .031) and RT (p = .011) - activation associations in the pMFC may have been driven by dACC voxels in uOCD (Table S6, available online). Wholebrain Analyses: Consistent with the ROI analysis, OCD patients compared to HC showed greater error-related activation in the pMFC at the preSMA-dACC border (“preSMAdACC”, Figure 1E); atypical increase in dACC activation with age (Figure 1F); and, reversal of the typical relation of faster RT with activation in a cluster encompassing dACC, rostral ACC 7

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and left caudate (Figure 1G, Table S7, available online). There were no areas in which HC showed greater activation than OCD. Exploratory analyses comparing uOCD and mOCD with HC (Figure 1E-G insets; Table S8, available online) showed greater activation in dACC and, at

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trend-level, in preSMA in mOCD, and atypical association of age and RT with dACC activation in uOCD. Interference-processing

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Primary pMFC ROI Analysis: There were no group differences in pMFC response to interference, but there was a reversal of the typical relation of greater interference-related pMFC

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activation with faster RT and greater accuracy in OCD relative to HC (β = .001 ± .001, p = .03; β = -5.17 ± 2.51, p = .04; Figure 2B-C; Table 2). Exploratory analyses suggested that uOCD predominantly contributed to this effect (Table S4, available online). Secondary Left and Right aI/fO ROI Analyses: The typical relation of greater left aI/fO activation with greater accuracy was attenuated in OCD (β = -7.83 ± 2.9, p = .008, Table 2).

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Exploratory analyses suggested this effect may have been driven by uOCD, albeit at a level of significance that fell just below threshold for multiple comparison correction (p = .014, Table S4, available online).

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Secondary dACC and preSMA ROI Analyses: Analysis of pMFC sub-regions suggested several trend-level effects across both dACC and pre-SMA that did not reach significance after

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correction (Tables S5, S6, available online). Wholebrain Analyses: There were no group or interaction effects on interference-related

activation; however, exploratory analyses attenuation of normative increase in preSMA-dACC activation with younger age, faster RT and higher accuracy in uOCD compared to HC (Figure 2E-G; Table S9, available online). OCD severity: Correlations brain activation to errors and interference ROI analyses: Lower OCD severity predicted greater activation to errors in pMFC (β = 0.08, p =0.02; Figure 1D) and interference in left aI/fO (β = -0.03, p =0.009; Figure 2D) (Table 8

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3). Exploratory analyses suggested severity associations were driven by uOCD for error-related pMFC activation (Figure S3C, available online), by both patient groups for interference-related aI/fO activation (Figure S4A, available online), and that these associations increased with age

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(Table S10, available online). In addition, an association between lower OCD severity and greater interference-related pMFC activation at older ages emerged across uOCD and mOCD (Figure S4B available online, Table S10, available online). Analysis of pMFC subregions

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showed an association between lower OCD severity and greater error-related activation of dACC in uOCD (p = .012, Tables S11 and S12, available online). Associations of OCD severity

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with CON activation remained after covarying illness duration.

Wholebrain Analyses: There were no significant effects of CYBOCS on activation to error or interference in primary analyses (i.e., medication status not modelled). However, when medication status was modelled, lower OCD severity was found to associate with greater errorrelated preSMA-dACC activation in uOCD (Figure1H, Table S13, available online) and greater

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interference-related activation at older ages in left aI/fO across uOCD and mOCD (Figure 2H; Table S14, available online). Discussion:

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Aberrant maturation of pMFC-based performance monitoring function has been posited to underlie the early course of OCD, but pMFC development remains to be characterized in

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young patients. In a large sample of OCD-affected compared to healthy youth, patients exhibited greater error-related activation of the pMFC and atypical increase of pMFC activation to errors with age. These findings provide new evidence of atypical development of pMFCbased error-processing function in pediatric OCD. Importantly, greater pMFC activation to errors associated with better performance in HC and lower OCD severity in patients. Collectively, these findings raise the possibility that ”hyperactive” pMFC response to errors may represent an adaptive response that normally facilitates task performance and, in pediatric OCD, develops with age to help patients control symptoms. 9

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The notion that heightened error-related pMFC activation could serve a compensatory role in pediatric OCD is consistent with the function of this region in signaling for cognitive control to facilitate the flexible adjustment of behavior.2 In the context of OCD, increased pMFC

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signaling could serve to improve patients’ ability to detect and dismiss obsessive thoughts and compulsive urges as irrelevant (i.e., false alarms or ‘thinking errors’) to move on to other, more appropriate behaviors. Greater interference-related activation in pMFC correlated with better

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performance in HC and, in left aI/fO, with lower OCD severity in patients, implicating more

general performance monitoring function (i.e., errors and interference) of the broader CON (i.e.,

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pMFC and aI/fO). Indeed, recent work suggests that greater engagement of the CON and related networks for task control may enhance performance on cognitive tasks in adults at familial risk of OCD and protect against OCD expression.35,36 Other recent models suggest that increased pMFC signaling may serve to compensate for attentional demands of anxiety during task performance, enabling patients to maintain normal performance but not necessarily

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reducing anxiety or OCD symptoms.16 These possibilities represent alternatives to prior work in which increased CON response to errors in OCD was interpreted to reflect excessive emotional sensitivity to and/or detection of mistakes that could drive symptoms.10,17

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Exploratory analyses showed greater pMFC and right aI/fO response to errors in mOCD than HC or uOCD, raising the possibility that medication, rather than illness, may be responsible

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for CON hyperactivity. However, prior work in adult OCD shows no effect of SSRIs on CON hyperactivity to errors.17 In our pediatric sample, mOCD were characterized by greater decrease from most severe past to less severe present CY-BOCS, suggesting that medication could induce CON engagement to support symptom suppression. The possibility that medication may help to resolve CON dysfunction aligns with normal association of greater errorand interference-related pMFC and right aI/fO activation with faster RT in mOCD, but attenuation of this relationship in uOCD. Similarly, the normative association of greater pMFC activation to errors (and, at trend level, interference) at younger ages was observed in mOCD, 10

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but reversed in uOCD. These findings raise the possibility that medication may normalize developmental trajectories in mOCD. By contrast, in uOCD, greater pMFC response to errors and interference at older ages and with lower OCD severity suggest that pMFC activation could

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increase naturalistically, with development, to help patients suppress symptoms. The presence of age-related change in pMFC-based performance monitoring function in pediatric OCD suggests a still-developing system that could be modulated to improve outcomes

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in affected youth. Performance monitoring capabilities improve dramatically in typically

developing adolescents, alongside age-related change in brain activation to performance

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monitoring demands.37 During adolescence, before CON connectivity reaches maturity,38 the pMFC may be considered less efficient, leading to greater dynamic range in task-related activity. In this light, the association of OCD-related hyperactivity with lower OCD severity may reflect a dynamic pMFC with relevance for improving illness outcomes. Given that pMFC function appears to stabilize in adulthood,39 adolescence may be a critical developmental

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window during which targeting pMFC is most likely to be successful. Should one try to augment function of the pMFC in pediatric OCD? Findings from the present study cannot answer this question, but justify longitudinal work to determine whether increases in pMFC-based capacity

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for task monitoring and control associate with reduction in OCD symptoms. In the long term, such work could pave the way for cognitive training to ‘exercise’ pMFC as augmentation and/or

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an alternative to currently available treatments. Atypical age-related increase of pMFC (and right aI/fO) response to errors has been

previously reported in a smaller sample of OCD compared to health youth.19 However, in contrast to our findings, the prior study showed no association of activation with OCD severity.19 Further, controls from the prior study showed no relation between activation and age,19 contrasting with the age-related decrease in activation observed in our sample of healthy youth. These inconsistencies may relate to smaller sample size19 or different analytic techniques. For example, the prior study assessed correlations of activation with OCD severity without co11

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varying age or performance which, as shown by our results, significantly impact CON-based performance monitoring function. On the other hand, the prior study found pre- to postcognitive behavioral therapy (CBT) increase in interference-related pMFC activation associated

performance monitoring may index an adaptive response in OCD.

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with decreasing OCD severity. Consistent is the premise that greater pMFC activation during

Within the pMFC, motor-cognitive compared to cognitive-affective processes have been described as localizing along a neuroanatomical continuum from posterior-dorsal to anterior-

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rostral areas,32 leading us to consider preSMA and dACC subregions in secondary ROI

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analyses. Many of the ROI results indicated trend-level effects that generalized across both areas and most results from the wholebrain analysis --- a more precise method for functional neuroanatomic localization --- were observed in an area spanning preSMA and dACC. These findings are consistent with a recent meta-analysis of nearly 10,000 fMRI studies showing task control processes (including errors and interference) to preferentially associate with preSMA

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and dACC.32 Consequently, we use the term “pMFC” to link to the broader literature on overlapping task control functions in the midline frontal area that encompasses these subregions,32 while also noting instances --- specifically altered associations of age and RT with

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error-related activation in uOCD --- in which findings may localize to dACC, not preSMA. Strengths of this work include large sample size, replication of findings across ROI and

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wholebrain analyses, and consideration of performance and medication effects; however, several important limitations should be noted. OCD was the primary diagnosis but, in line with the clinical presentation of OCD, some subjects had comorbid diagnoses (e.g., anxiety, attentional problems) which may have contributed variance. Due to insufficient errors (< 5), 28% of subjects were excluded from error analyses; nonetheless, the percentage of excluded subjects was nearly the same across OCD (26%) and HC (25%) groups, meaning that observed group differences should not have been biased. In addition, patient age and illness duration were correlated such that persistent illness, rather than developmental effects, may have driven 12

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greater pMFC response to errors in older OCD subjects; disentangling age and illness duration will require the recruitment of same-aged patients who vary in OCD chronicity. Finally, we acknowledge that our study was not designed to test medication-induced change in CON

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function and other factors, including higher rates of CBT exposure in mOCD than uOCD, could have contributed to effects observed in exploratory analyses. Future, longitudinal work should examine CON function in patients, at different ages, before and after treatment with medication,

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CBT and the combination.

In summary, our study shows reversal of age-related decrease of pMFC response to

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errors in pediatric OCD compared to healthy youth, suggesting atypical development of neural substrate for performance monitoring during the early course of illness. In addition, error-related pMFC activity was greater in patients than controls, increased with better performance in controls and lower OCD severity in patients. Collectively, we have interpreted findings to suggest that greater pMFC engagement may serve a compensatory role in pediatric OCD.

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Future studies using longitudinal designs are needed to characterize maturational trajectories of pMFC and broader CON function in pediatric OCD and to determine whether increases in

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activation lead to reduction in illness severity after treatment and/or naturalistically over time.

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Figure Legends Figure 1. Error-processing in pediatric obsessive-compulsive disorder (OCD).

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Note: Error-processing activated posterior medial frontal cortex (pMFC) and bilateral anterior insula (aI/fO) (A). ROI analyses showed greater pMFC activation associated with younger age in HC, but older age in OCD (B); faster response time (RT) in HC, but not OCD (C); and, lower OCD severity (C-YBOCS, Child Yale-Brown Obsessive Compulsive Scale) in patients (D). Whole brain analyses showed greater pMFC activation in OCD than HC (E) and, as with ROI analyses, altered associations of pMFC activation with age (F) and RT (G) in OCD compared to HC. Exploratory analyses suggested the effect of group on pMFC activation was driven by medicated patients (E inset, mOCD > HC), whereas unmedicated patients (uOCD) drove atypical age- (F inset, uOCDage > HCage), altered RT- (G inset, OCD_RT > HC_RT) and inverse OCD severity associations (H) with pMFC activation. Color bars show t-scores, reflecting relative strength of brain activation. Montreal Neurologic Institute coordinates shown (x, y, z). aI/fO = anterior insula/frontal operculum, C-YBOCS = Child Yale-Brown Obsessive Compulsive Scale, FWE = familywise error, HC = healthy controls, MFC = medial frontal cortex, mOCD = medicated obsessive-compulsive disorder, pMFC = posterior medial frontal cortex, ROIs = regions of interest, RT = response time, uOCD = unmedicated obsessive-compulsive disorder

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Figure 2. Interference-processing in left anterior insula/frontal operculum (aI/fO) and posterior medial frontal cortex (pMFC): Effects of symptom severity in unmedicated patients with pediatric obsessive-compulsive disorder (OCD).

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Note: Interference-processing activated posterior medial frontal cortex (pMFC) and bilateral anterior insula (aI/fO) (A). ROI analyses showed associations of greater pMFC activation with better performance (faster response time, RT; higher accuracy, Acc) in HC, but worse performance in OCD (B-C) and greater left aI/fO activation with lower OCD severity (C-YBOCS, Child Yale Brown Obsessive Compulsive Scale) in patients (D). Exploratory wholebrain analyses showed altered associations of pMFC activation with age (E), RT (F) and Acc (G) in unmedicated patients (uOCD) compared to HC. In patients, there was a CY-BOCs-by-age interaction driven by the association of greater left aI/fO activation with lower OCD severity at older ages across uOCD and medicated (mOCD) patients (H). Color bars show t-scores, reflecting relative strength of brain activation. Montreal Neurologic Institute coordinates shown (x, y, z). Acc = accuracy, C-YBOCS = Child Yale-Brown Obsessive Compulsive Scale, FWE = familywise error, HC = healthy controls, MFC = medial frontal cortex, mOCD = medicated obsessive-compulsive disorder, ROIs = regions of interest, RT = response time, uOCD = unmedicated obsessive-compulsive disorder

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Table 1. Participant characteristics. Error Analysis HC Test Statistic (N = 51) (p-value) 14.1 ± 3.2 t(100) = -.14 (.88) 23F (45%) χ2(102) =.63 (.43) 2.3 ± .53 t(97) = .66 (.51) na na

OCD (N = 69) 13.9 ± 2.8 39F (56%) 2.2 ± .48 18.6 ± 7.7

Interference Analysis HC Test Statistic (N = 72) (p-value) 14.0 ± 3.5 t(139) = .11 (.91) 33F (46%) χ2(141) = .34 (.56) 2.26 ± .53 t(136) = .51 (.61) na na

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OCD (N = 51) 14.2 ± 2.8 28F (55%) 2.2 ± .45 17.8 ± 7.4

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Age Gender SESa CY-BOCS, Present CY-BOCS, na na 27.9 ± 6.5 na na 27.1 ± 6.6 Lifetime CY-BOCS, 9.3 ± 7.9 na na 9.3 ± 7.9 na na Change Illness 6.4 ± 4.3 na na 6.5 ± 4.0 na na Duration AAO 7.7 ± 3.3 na na 7.5 ± 3.0 na na Inc RT 1094 ± 249 1060 ± 238 t(100)= -.71 (.48) 1114 ± 258 1071 ± 220 t(139) = -1.07 (.29) Con RT 770 ± 176 738 ± 171 t(100)= -.95 (.35) 789 ± 192 759 ± 162 t(139) = -.99 (.32) Inc Acc .87 ± .07 .88 ± .07 t(100)= 1.15 (.25) .89 ± .07 .91 ± .07 t(139) = 1.31 (.19) Con Acc .99 ± .02 .98 ± .02 t(100)= -.67 (.50) .99 ± .02 .99 ± .02 t(139) = -.76 (.49) Motion .20 ± .08 .19 ± .13 t(100) = -.11 (.91) .21 ± .11 .19 ± .13 t(139) = -.96 (.34) Note: AAO = age of onset, Acc = accuracy, Con = congruent, CY-BOCS = Child Yale-Brown Obsessive Compulsive Scale, HC = Healthy, Inc = incongruent, OCD = Obsessive Compulsive Disorder Control, RT = response time Motion = mean framewise displacement 28. Age, AAO, illness duration in years. a SES missing for 2 HC, 1 OCD.

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Table 2. Cingulo-opercular network function in pediatric obsessive-compulsive disorder (OCD) compared to healthy controls ERRORS pMFC Left aI/fO Right aI/fO Intercept 1.10 ± .28 <.001 1.48 ± .25 <.001 1.42 ± .28 <.001 Group .98 ± .41 .018 0.50 ± .36 .175 .58 ± .39 .139 Age -.25 ± .13 .063 --------------.12 ± .13 .342 Inc RT -.006 ± .002 .001 --------------0.004 ± .002 .025 Inc Acc 10.06 ± 3.07 .002 1.70 ± 3.91 .665 7.1 ± 2.97 .019 Group x Age .39 ± .18 .029 -------------.28 ± .17 .098 Group x Inc RT .005 ± .002 .026 -------------.006 ± .002 .010* Group x Inc Acc -------------8.13 ± 5.41 .136 -------------Motion --------------3.38 ± 1.60 .037 -------------Adjusted R-Square 0.17 0.08 0.08 Model ANOVA F(6,95)=4.4 (p<.001) F(4,97)=3.2 (p=.016) F (6,95) = 2.5 (p=.03) INTERFERENCE pMFC Left aI/fO Right aI/fO Intercept .60 ± .07 <.001 .45 ± .08 <.001 .52 ± .08 <.001 Group -.02 ± .10 .847 -.08 ± .12 .492 -.10 ± .12 .413 Age ------------------------------------------Overall RT -.001 ± .0004 .055 -.001 ±.0004 .053 -.001 ± .0003 .001* Overall Acc 1.41 ± 1.76 .425 4.93 ± 2.04 .017* 1.77 ± 2.06 .393 Group x Age ------------------------------------------Group x overall RT .001 ± .0005 .028 .001 ± .0006 .100 --------------Group x overall Acc -5.17 ± 2.51 .042 -7.83 ± 2.9 .008* -4.90 ± 2.95 .099 Motion ---------------------------------------Adjusted R-Square 0.03 0.05 0.08 Model ANOVA* F(5,135)= 2.0 (p=.086) F(5,135)=2.4 (p=.039) F(4,136)=4.2 (p=.003) Note: Motion refers to framewise displacement 28. Dashed lines represent predictor variables eliminated during backwards stepwise regression.

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Significance levels were p < .05 for pMFC (primary region of interest, bolded) and p < .013 for secondary ROIs (asterisked). aI/fO = anterior insula/frontal operculum, Acc = accuracy, Inc = incongruent, HC = healthy controls, pMFC = posterior medial frontal cortex, RT = response time

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Table 3. Cingulo-opercular network function and obsessive-compulsive disorder (OCD) severity ERRORS pMFC Left aI/fO Right aI/fO Intercept 1.70 ± .34 <.001 1.91 ± .23 <.001 1.99 ± .25 <.001 CYBOCS -.08 ± .04 .025 -.05 ± .03 .124 -------------Age .14 ± .09 .139 .12 ± .08 .142 .29 ± .11 .013* Inc RT ---------------------------------------Inc Acc 12.66 ± 3.65 .001* 10.09 ± 3.40 .005* 7.68 ± 3.59 .038 CY-BOCS x Age -.02 ± .01 .079 --------------------------Motion --------------------------9.91 ± 3.44 .006* Adjusted R-Square .30 .18 .18 Model ANOVA F(4,46)=6.3 (p<.001) F(3,47)=4.8 (p=.005) F (3,47) = 4.6 (.006) INTERFERENCE pMFC Left aI/fO Right aI/fO Intercept .57 ± .07 <.001 .35 ± .08 <.001 .42 ± .09 <.001 CY-BOCS -.007 ± .01 .478 -.03 ± .01 .009* -------------Age .02 ± .03 .504 .01 ± .03 .798 .07 ± .03 .043 Overall RT ---------------------------------------Overall Acc -3.69 ± 1.81 .045 --------------------------CY-BOCS x Age -.006 ± .004 .097 -.008 ± .004 .055 -------------Motion 1.43 ± .76 .065 --------------------------Adjusted R-Square 0.09 0.15 0.05 Model ANOVA F(5,63)=2.3 (p=.048) F(3,65)=4.0 (p=.012) F(1,67)=4.3 (p=.043) Note: Motion refers to framewise displacement 28. Dashed lines represent predictor variables eliminated during backwards stepwise regression.

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Development of Posterior Medial Frontal Cortex Function in Pediatric ObsessiveCompulsive Disorder

Kate Dimond Fitzgerald, MD; Yanni Liu, PhD; Timothy Johnson, PhD; Jason Moser, PhD;

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Rachel Marsh, PhD; Gregory L. Hanna, MD, Stephan F. Taylor, MD

Funding: This research was supported by the National Institute of Mental Health (NIMH) grants

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K23-MH082176 (K.D.F.) and R01-MH102242 (K.D.F./S.F.T.), the Dana Foundation (K.D.F.),

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NARSAD (K.D.F.), and the Todd Ouida Memorial Children’s Fund (K.D.F.).

This study was presented in symposia at the American Academy of Child and Adolescent Psychiatry’s 63rd Annual Meeting in New York, NY, October 24-29, 2016; the American College of Neuropsychopharmacology’s 55th Annual Meeting in Hollywood, FL, December 4-8, 2016; and the Society of Biological Psychiatry’s 72nd Annual Meeting in San Diego, CA, May

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18-20, 2017.

Dr. Johnson served as the statistical expert for this research.

Disclosures:

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Acknowledgments: None

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Dr. Taylor has received research support through Otsuka/Vanguard Research Group and Boehringer-Ingelheim.

Drs. Fitzgerald, Liu, Johnson, Moser, Marsh, and Hanna report no biomedical financial interests or potential conflicts of interest.

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Supplement 1

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Excluded data: Of 150 participants scanned, data from three were excluded due to technical problems (no high resolution scan collected, n=2; behavioral data loss, n = 1) and six due to excessive motion (≥ 1TR exceeding 3 mm translation or rotation in ≥ 3 runs). Subjects excluded due to excessive motion were four unmedicated obsessive-compulsive disorder (uOCD) (3 female, ages 11.1, 11.7, 15.1 and 1 male, 11.0 years) and two healthy youth (1 female, 8.5 and 1 male, 9.0 years). Several subjects exhibited excessive motion in 1-2 runs, and thus contributed only 3-4 runs of data for analysis: 3 runs were contributed by 5 healthy youth (3 female, ages 8.9,9.8 and 10.8 and 2 male, ages 11.8 and 10.8 years), and 4 runs by 4 healthy (all male, ages 9.7, 10.3, 12.2 and 14.5 years), 5 medicated obsessive-compulsive disorder (mOCD) (2 female, ages 15.7 and 17.4 and 3 male, ages 11.7, 11.8 and 12.2 years) and 3 uOCD (1 female, ages 14.4 and 2 male, ages 10.6 and 16.7 years) youth.

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Patient medications: Among OCD patients, thirty-four were medicated, thirty-three with selective serotonin reuptake inhibitors (3 citalopram, 18 fluoxetine, 2 fluvoxamine, 1 paroxetine, 2 sertraline) and one with guanfacine for comorbid tics. Seven SSRI-treated patients were also taking aripiprazole (n = 1), quetiapine (n = 1), risperidone (n=1), buspirone (n=1), guanfacine (n = 1), methylphenidate (n=1) or risperidone plus methylphenidate (n =1).

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Regions of interest (ROIs): The primary ROIs for posterior medial frontal cortex (pMFC) response to errors and interference were defined by the main effects of each contrast in conjunction with an MFC ROI known to preferentially associate with cognitive control processes based on the Neurosynth meta-analysis of nearly 10,000 fMRI studies (1). The MFC ROI included middle and posterior Neurosynth zones because these zones (and not the anterior zone) preferentially activate to cognitive control demands (including errors and interference) and contain dACC and preSMA, respectively (1) --- regions previously established to mediate cognitive control in general, and interference and error processing in specific (2). The pMFC ROI used in error processing analyses was defined by the voxels activated in the error contrast (peak -6, 26, 28; Z = 6.65; k = 494, Table S1) since these voxels were wholly contained within the Neurosynth posterior-middle MFC zones (1) (Fig S1, top panel, red and yellow). The pMFC ROI used in interference analyses was defined by voxels activated in the interference contrast (peak -3, 8, 46; Z = Inf; k = 7917) and masked with Neurosynth posterior-middle MFC zones (1) to yield a volume of k = 817 voxels in the pMFC centered at -3, 8, 46 (Fig S1, bottom panel, red and yellow).

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Secondary ROIs included bilateral anterior insula/frontal operculum (aI/fO) and pMFC subregions, the dorsal anterior cingulate (dACC) and pre-supplementary motor area (preSMA). The rationale for examining secondary aI/fO ROIs was based on the established networking of these regions with pMFC (i.e., cingulo-opercular network) at rest (3) and during cognitive control processes, including error and interference response (4). The aI/fO ROIs are defined in the main text. The rationale for examining secondary dACC and preSMA ROIs was based on the preferential association of these subregions with response to errors and interference, respectively (2, 5). To define dACC and preSMA ROIS for errors and interference, the larger pMFC ROIs for each contrast were subdivided using Neurosynth middle and posterior zones which include the dACC and preSMA, respectively (1). For errors, the dACC ROI contained 420 voxels and the preSMA ROI contained 36 voxels (Figure S1, top panel). For interference, the dACC ROI contained 386 voxels and the preSMA ROI contained 482 voxels (Figure S2, bottom panel).

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Supplemental Tables

18 (26%) 12 (17.4%) 7 (10.1%)

Subclinical Depression (any) Depression NOS Dysthymia

13 (19%) 12 (17.4%) 1 (1.5%)

Attention Deficit Hyperactivity Disorder

9 (13.0%)

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Anxiety Disorders (any) Generalized Anxiety Disorder Panic Disorder Separation Anxiety Disorder Social Anxiety Specific Phobia

OCD (n = 69)* 27 (39%) 12 (17.4%) 3 (4.4%) 5 (7.2%) 5 (7.2%) 6 (8.7%)

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Table S1. Comorbid diagnoses.

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Other Disorders (any) 4 (6%) Impulse Control Disorder** 4 (5.8%) Developmental Coordination Disorder 1 (1.5%) Note: *20 patients had obsessive-compulsive disorder (OCD) only; 49 had primary OCD with 1-3 less severe, comorbid diagnoses. **Impulse control disorders included trichotillomania, skin picking, nail biting

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Table S2. Error and interference activations across all subjects (Wholebrain analyses)

Error processing pMFC* Dorsal anterior cingulate cortexƗ Left aI/fO* Right aI/fO*

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-6, 26, 28 -30, 20, -14 36, 23, -5

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-3, 8, 46 -30, 17, 4 33, 20, 4 30, 50, 25 -33, -7, 61 -39, -16, 52 33, -4, 61 -21, -64, 46 -42, -40, 37 27, -58, 49 39, -37, 40 -27, -70, 28 -9, -19, 7 9, -16, 10 3, -19, 25

Inf Inf 7.34 6.57 Inf Inf Inf Inf Inf Inf Inf Inf 7.70 6.86 6.41

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7917c 160 235 180 7917c

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Interference processing pMFC* Pre-supplementary motor areaƗ Left aI/fO* Right aI/fO* Right dorsal prefrontal Left precentral Left postcentral Right precentral Left superior parietal Left inferior parietal Right superior parietal Right inferior parietal Left middle occipital Left Thalamus Right Thalamus Middle posterior cingulate

494 343 345

Coordinatesb

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Clustera

Brain region

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Note: a Brain maps were displayed at a height threshold of p<0.05, corrected for familywise error (FWE); clusters were considered significant at p < .05, corrected for family wise error across whole brain. Number of voxels in each significant cluster are listed. b Peak coordinates, x, y, z c Refers to the same cluster *Regions of interest (ROIs): posterior medial frontal cortex (pMFC), anterior insula/frontal operculum (aI/fO). As shown in Figure S1, pMFC ROIs were defined by activations for error and interference contrasts in conjunction with middle and posterior Neurosynth MFC zones which include dorsal anterior cingulate and pre-supplementary motor areas, respectively. The majority of voxels activated for errorprocessing were clustered in the middle MFC zone, including the peak activation at -6, 26, 28, justifying designation as “dorsal anterior cingulate cortex,” above. By contrast, voxels activated for interference were distributed more evenly across middle and posterior zones; however, the peak activation at -3, 8, 46 fell within the posterior MFC zone, justifying designation of this peak as “presupplementary motor area,” above. aI/fO = anterior insula/frontal operculum, FWE = familywise error, MFC = medial frontal cortex, pMFC = posterior medial frontal cortex, ROIs = regions of interest

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Table S3. Participant characteristics for unmedicated obsessive-compulsive disorder (uOCD), medicated OCD (mOCD) and healthy youth

Test Statistic (p-value) F(2,99) = 2.2 (.12) χ2(2,102) =.64 (.73) F(2,96) = .24 (.79) t(2,49) = 1.8 (.07)

uOCD (n = 35) 13.2 ± 3.0 19F (56%) 2.18 ± .46 20.2 ± 8.0

Interference Analysis mOCD HC Test Statistic (n = 34) (n = 72) (p-value) 14.7 ± 2.4 14.0 ± 3.3 F(2,138) = 2.0 (.14) 16F (46%) 33F (46%) χ2(2,141) = .70 (.71) 2.26 ± .51 2.24 ± .49 F(2, 135) = .38 (.68) 16.9 ± 7.0 na t(2,67) = 1.8 (.07)

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uOCD (n = 28) 13.4 ± 3.0 15F (56%) 2.19 ± .48 19.5 ± 7.8

Error Analysis mOCD HC (n = 23) (n = 51) 15.1 ± 2.3 14.1 ± 3.2 12F (50%) 23F (45%) 2.22 ± .42 2.27 ± .53 15.7 ± 6.6 na

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Age Gender SES1 CY-BOCS, Present2 CY-BOCS1, 27.6 ± 6.0 na t(2,47) = -.42 (.68) 27.0 ± 7.0 28.7 ± 6.0 na t(2,65) = -1.0 (.30) 26.8 ± 7.2 Lifetime CY-BOCS1, 7.3 ± 7.7 11.8 ± 7.5 na t(2,47 ) = -2.1 (.04) 6.8 ± 7.7 11.8 ± 7.4 na t(2,65) = -2.75 (.008) Change Illness 6.15 ± 4.36 6.94 ± 4.20 na t(2,48) = -.65 (.52) 6.15 ± 4.23 6.77 ± 3.84 na t(2,66) = -.63 (.53) 1 Duration AAO1 7.3 ± 3.0 8.1 ± 3.7 na t(2,48) = -.91 (.37) 7.1 ± 2.7 7.9 ± 3.3 na t(2,66) = -1.1 (.28) CBT1 9 (33%) 15 (68%) na χ2(2,49) = 5.9 (.01) 11 (31%) 20 (59%) na χ2(2,66) = 6.0 (.01) Inc RT 1116 ± 283 1068 ± 203 1060 ± 238 F(2,99)=.50 (.61) 1123 ± 268 1105 ± 250 1071 ± 220 F(2,138) = .61 (.54) Con RT 787 ± 200 749 ± 144 738 ± 171 F(2,99)=.75 (.47) 804 ± 199 775 ± 188 759 ± 162 F(2,138) = .72 (.49) Inc Acc .87 ± .06 .86 ± .08 .88 ± .07 F(2,99)=.84 (.43) .90 ± .07 .90 ± .08 .90 ± .07 F(2,138) = .86 (.43) Con Acc .99 ± .02 .99 ± .02 .98 ± .02 F(2,99)=.30 (.74) 1.0 ± .02 1.0 ± .02 1.0 ± .02 F(2,138) = .32 (.73) Motion4 .20 ± .08 .19 ± .10 .19 ± .13 F(2,99) = .06 (.94) .19 ± .08 .22 ± .13 .19 ± .13 F(2,138) = 1.04 (.36) Note: Age, AAO, illness duration in years. Motion summarized as mean framewise displacement (6). 1 Several subjects were missing SES (n=2 HC, 1 uOCD), lifetime C-YBOCS (n= 1 uOCD, 1 mOCD), illness duration and AAO (1 uOCD) or record of CBT exposure (1uOCD, 2 mOCD). 2 Present CY-BOCS indicate mild to moderate symptom severity; 67 had active OCD symptoms, 2 (1 uOCD and 1 mOCD) had subclinical symptoms (CYBOCS score <6) at assessment. Acc = Accuracy, AAO = age of onset, Compulsive ScaleCBT = cognitive behavioral therapy exposure, Con = Congruent, CY-BOCS = Child YaleBrown Obsessive, HC = Healthy Control, Inc = Incongruent, RT = Response time

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Table S4. Cingulo-opercular network function in pediatric unmedicated obsessive-compulsive disorder (uOCD) medicated obsessive-compulsive disorder (mOCD) and healthy youth (region of interest (ROI) analysis) ERRORS pMFC Left aI/fO Right aI/fO Intercept (grp: HC) 1.10 ± .28 <.001 1.48 ± .25 <.001 1.42 ± .26 <.001 grp(uOCD) .57 ± .48 .239 0.05 ± .42 .888 .02 ± .45 .971 grp(mOCD) 1.79 ± .55 .002 0.98 ± .45 .033 1.78 ± .52 <.001* Age -.26 ± .13 .051 --------------.13 ± .12 .290 Inc RT -.006 ± .002 <.001 --------------0.004 ± .002 .017 Inc Acc 11.01 ± 3.07 <.001 1.69 ± 3.8 .660 7.9 ± 2.89 .007* grp(uOCD) x Age .42 ± .19 .030 -------------.34 ± .17 .058 grp(mOCD) x Age .05 ± .26 .840 --------------.19 ± .25 .447 grp(uOCD) x Inc RT .006 ± .002 .010 -------------.006 ± .002 .005* grp(mOCD) x Inc RT .001 ± .003 .694 -------------.002 ± .002 .400 grp(uOCD) x Inc Acc -------------14.47 ± 6.56 .030 -------------grp(mOCD) x Inc Acc -------------3.55 ± 6.36 .578 -------------Motion --------------3.03 ± 1.57 .057 -------------Adjusted R-Square 0.19 0.12 0.16 Model ANOVA F(9,92)=3.6 (p=.001) F(6,95)=3.3 (p=.006) F (9,92) = 3.1 (p=.003) INTERFERENCE pMFC Left aI/fO Right aI/fO Intercept (grp:HC) .60 ± .07 <.001 .45 ± .08 <.001 .48 ± .06 <.001 grp(uOCD) .03± .13 .836 -.03 ± .15 .861 --------------grp(mOCD) .02 ± .13 .908 -.16 ± .14 .313 --------------Age ------------------------------------------Overall RT -.001 ± .0005 .035 -.001 ±.0004 .053 -.001 ± .0003 <.001* Overall Acc 1.88 ± 1.82 .302 4.93 ± 2.04 .017 --------------grp(uOCD) x Age .10 ± .05 .054 ----------------------------grp(mOCD)x Age -.008 ± .07 .900 ----------------------------grp(uOCD) x overall RT .002 ± .001 .012 .001 ± .0007 .046 --------------grp(mOCD) x overall RT .001 ± .001 .149 .0004 ± .001 .550 --------------grp(uOCD) x overall Acc -7.92 ± 3.27 .017 -9.36 ± 3.8 .014 --------------grp(mOCD) x overall Acc -4.03 ± 3.02 .185 -6.31 ± 3.5 .070 ---------------

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Motion ---------------------------------------Adjusted R-Square 0.03 0.05 0.08 Model ANOVA* F(11,129)= 1.4 (p=.18) F(8,132)=1.9 (p=.07) F(1,139)=13.1 (p<.001) Note: Motion refers to framewise displacement (6). Dashed lines represent eliminated variables. Post-hoc comparisons of group intercepts showed greater activation in mOCD compared to uOCD in pmFC (β = 1.22 ± .61, p = .05) and right aI/fO (β = 1.76 ± .57, p= .003), but no difference in left aI/fO (β = .92 ± .51, p = .07) for errors, and no differences for interference (p’s > .45) Significance levels were p < .05 for pMFC (primary region of interest, bolded) and p < .013 for secondary ROIs (asterisked). Acc = accuracy, aI/fO = anterior insula/frontal operculum, grp = group, HC = healthy controls, Inc = incongruent, pMFC = Posterior medial frontal cortex, RT = response time.

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Table S5. Posterior medial frontal cortex (pMFC) subregion function in in pediatric obsessive-compulsive disorder (OCD) compared to healthy controls (region of interest (ROI) analysis) ERRORS

Intercept (HC) Group Age Overall RT

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preSMA 1.37 ± .32 .001 0.78 ± .44 .085 --------------.003 ± .001 .006* 1.25 ± 4.80 .795 --------------------------10.9 ± 6.63 .105 -------------0.11 F(4,97)=4.2 (p=.004)

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dACC 1.14 ± .29 <.001 .98 ± .41 .019 -.25 ± .14 .067 -.006 ± .002 .002* 10.10 ± 3.12 .002* .39 ± .18 .031 .005 ± .002 .027 --------------------------0.16 F(6,95)=4.3 (p<.001) dACC .62 ± .08 -.09 ± .11 -.03 ± .03 -.001 ± .0006

<.001 .393 .306 .065

preSMA .60 ± .07 <.001 .04 ± .11 .678 ---------------.001 ±.0004 .040

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Overall Acc 1.42 ± 1.93 .463 1.83 ± 1.86 .327 Group x Age .07 ± .05 .149 --------------Group x overall RT .002 ± .0007 .014 .001 ± .0005 .029 Group x overall Acc -5.52 ± 2.72 .045 -5.25 ± 2.7 .050 Motion --------------------------Adjusted R-Square 0.03 0.03 Model ANOVA* F(7,133)= 1.7 (p=.12) F(5,135)=1.9 (p=.10) Note: Motion refers to fractional displacement (6). Dashed lines represent predictor variables eliminated during backwards stepwise regression.

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*Significance levels were p < .013. Acc = Accuray, dACC = dorsal anterior cingulate cortex, HC = Healthy controls, Inc = incongruent, pre-SMA = pre-supplementary motor area, RT = response time

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Table S6. Posterior medial frontal cortex (pMFC) subregion function in in pediatric unmedicated OCD (uOCD), medicated OCD (mOCD) and healthy controls (HC) (region of interest (ROI) analysis)

<.001 .767 .629 .306 .463 .065 .045 .990 .023 .217 .025 .110

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dACC 0.62 ± .08 -.04 ± .13 -.07 ± .14 -.03 ± .03 1.42 ± 1.93 -.001 ± .001 .11 ± .05 -.001 ± .07 -8.05 ± 3.48 -3.99 ± 3.22 .002 ± .001 .001 ± .001

preSMA 1.09 ± .32 <.001 0.39 ± 53 .467 1.26 ± .57 .029 --------------.003 ± .001 .008* 7.21 ± 3.33 .033 -------------------------------------------------------------------------------------------.10 F(4,97)=3.94 (p=.005)

preSMA 0.60 ± .07 .04 ± .13 .04 ± .13 -----------1.83 ± 1.87 -.001 ± .0004 -----------------------7.56 ± 3.45 -3.37 ± 3.17 .001 ± .001 .001 ± .001

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Intercept (HC) Grp (uOCD) Grp (mOCD) Age Total ACC Total RT Grp (uOCD) x Age Grp (mOCD) x Age Grp (uOCD) x Total ACC Grp (mOCD) x Total ACC Grp (uOCD) x Total RT Grp (mOCD) x Total RT

dACC 1.13 ± .29 <.001 .60 ± .49 .23 1.77 ± .56 .002* -.26 ± .13 .055 -.006 ± .002 .001* 11.06 ± 3.13 .001* 0.42 ± .19 .031 .05 ± .27 .838 .006 ± .002 .011* .001 ± .003 .723 ---------------------------------------.18 F(9,92)=3.5 (p<.001)

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Intercept (HC) grp(uOCD) grp(mOCD) Age Inc RT Inc Acc grp(uOCD) x Age grp(mOCD) x Age grp(uOCD) x Inc RT grp(mOCD) x Inc RT grp(uOCD) x Inc Acc grp(mOCD) x Inc Acc Motion Adjusted R-Square Model ANOVA INTERFERENCE

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<.001 .755 .734 --.330 .042 ----.030 .289 .047 .120

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Motion --------------------------Adjusted R-Square .03 .02 Model ANOVA* F(11,129)=1.43 (p=.17) F(8,132)=1.32 (p=.24) Note: Motion refers to framewise displacement (6). Dashed lines represent eliminated variables. *Significance levels were p < .013. Acc = accuracy, Grp = group, Inc = incongruent, RT = response time.

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Table S7. Error-related activations in pediatric obsessive-compulsive disorder (OCD) compared to healthy youth (Wholebrain analysis) Cluster-level statistics* k Coordinates

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OCD x Age, positive effect *pMFC (dACC)

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Predictor OCD > HC *pMFC (preSMA-dACC)

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OCD x overall RT, positive effect pMFC (dACC) .001 169 -6, 29, 7 4.18 Left caudate -15, 20, 7 4.18 Rostral ACC -12, 41, 4 3.90 Note: * Clusters are significant at p < .05 with correction for family wise error across the whole brain or, if italicized, within search volumes (pMFC, right aI/fO, or left aI/fO) defined by the main effect of errors. aI/fO = anterior insula/frontal operculum, pMFC = posterior medial frontal cortex

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57, 17, -5 57, 11, 4

4.28 4.11

*Left aI/fO

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-12, -67, 37 -15, -70, 58 9, -64, 64

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Right sup. parietal

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Table S8. Error-related activations in unmedicated OCD (uOCD) and medicated OCD (mOCD) vs. healthy controls (HC) (Wholebrain analysis) Cluster-level statistics* Predictor pFWE-corr k Coordinates Z mOCD > HC pMFC (dACC) <.001 182 3, 23, 13 4.84 0, 20, 28 4.02 -21, 41, 7 3.86 (preSMA) .06 63 12, 17, 61 4.46 12, 20, 52 3.57

-6, 29, 7 -9, 38, 4 -15, 20, 7

4.44 3.59 3.98

uOCD x Age, positive effect *pMFC (dACC)

.046

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uOCD x IncRT, positive effect *pMFC (dACC)

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6, 35, 22 3, 32, 28

3.39 3.20

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uOCD x overall RT, positive effect *pMFC (preSMA-dACC)

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uOCD x Age, positive effect *pMFC (preSMA-dACC)

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Table S9. Interference-related activations in unmedicated OCD (uOCD) and medicated OCD (mOCD) vs. healthy controls (HC) (Wholebrain analysis) Cluster-level statistics* Predictor pFWE-corr k Coordinates Z Tot Acc, positive effect *Left aI/fO .020 4 -30, 17, -2 3.32

67 9

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uOCD x overall Acc, negative effect *pMFC (preSMA-dACC)

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aI/fO = anterior insula/frontal operculum, pMFC = posterior medial frontal cortex

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mOCD x overall Acc, negative effect *Left aI/fO .020 4 -33, 14, 1 3.37 Note: *Clusters are significant at p < .05 with correction for family wise errors within search volumes (pMFC, right aI/fO, or left aI/fO) defined by the main effect of interference

Table S10. Obsessive-compulsive disorder (OCD) severity and cingulo-opercular network function in pediatric unmedicated OCD (uOCD) and medicated OCD (mOCD) (region of interest (ROI)analysis) ERRORS pMFC Left aI/fO Right aI/fO

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1.5 ± .32 <.001 -------------.25 ± .12 .041 1.43 ± .50 .007* -------------8.17 ± 3.37 .020 --------------.27 ± .19 .164 --------------------------7.15 ± 3.39 .040 .21 F (5,45) = 3.6 (.008)

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1.65 ± .32 <.001 -.04 ± .03 .181 .23 ± .11 .034 .78 ± .48 .115 -------------9.93 ± 3.28 .004* --------------.40 ± .19 .042 -.02 ± .01 .174 --------------------------.25 F(6,44)=3.8 (p=.004)

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1.70 ± .34 <.001 -.11 ± .04 .014 .23 ± .12 .053 .89 ± .52 .100 -------------13.45 ± 3.61 <.001 .04 ± .08 .661 -.18 ± .21 .382 -.04 ± .02 .007 .07 ± .04 .089 -------------.36 F(8,42)=4.5 (p<.001)

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Intercept (grp:uOCD) CYBOCS Age Meds Inc RT Inc Acc CY-BOCs x Meds Age x Meds CY-BOCS x Age CY-BOCS x Meds x Age Motion Adjusted R-Square Model ANOVA INTERFERENCE

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pMFC Left aI/fO Right aI/fO Intercept (grp:uOCD) .68 ± .10 <.001 .52 ± .11 <.001 .48 ± .13 <.001 CY-BOCS -.01 ± .01 .240 -.03 ± .01 .003* -.0003 ± .02 .988 Age .06 ± .04 .083 .02 ± .03 .471 .08 ± .04 .066 Meds -.16 ± .15 .316 -.34 ± .17 .052 -.22 ± .20 .251 Overall RT ---------------------------------------Overall Acc -3.86 ± 1.78 .034 --------------3.78 ± 2.34 .111 CY-BOCS x Meds --------------------------.001 ± .03 .959 Age x Meds -.10 ± .06 .086 --------------.07 ± .07 .332 CY-BOCS x Age -.01 ± .004 .030 -.01 ± .004 .028 -.002 ± .01 .713 CY-BOCS x Meds x Age ---------------------------.02 ± .01 .076 Motion 1.31 ± .81 .107 --------------------------Adjusted R-Square 0.13 0.15 0.05 Model ANOVA F(7,61)=2.4 (p=.03) F(4,64)=4.1 (p=.005) F(7,60)=1.5 (p=.18) Note: Motion refers to framewise displacement (6) Effects of CYBOCs and CYBOCs-by-age interaction on pMFC response to errors were significant only for uOCD, whereas the effects of these terms on pMFC and left aI/fO response to interference were significant across both uOCD and mOCD patient groups.

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Acc = accuracy, (aI/fO) = anterior insula/frontal operculum, : aI/fO = anterior insula/frontal operculum, CY-BOCS = Child Yale- Brown Obsessive Compulsive Scale, Inc – incongruent, Meds = medication, mOCD = medicated OCD, uOCD = unmedicated OCD, pMFC = posterior medial frontal cortex, RT = response time

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Table S11. Obsessive-compulsive disorder (OCD) severity and posterior medial frontal cortex (pMFC) subregion function in pediatric OCD ERRORS dACC preSMA Intercept 1.92 ± .26 <.001 1.65 ± .32 <.001 CYBOCS -.08 ± .04 .023 -.05 ± .03 .166 Age .14 ± .09 .147 .17 ± .10 .102 Inc RT --------------------------Inc Acc 12.79 ± 3.72 .001* 12.03 ± 4.04 .005* CY-BOCS x Age -.02 ± .01 .070 -.03 ± .02 .052 Motion --------------------------Adjusted R-Square .30 .23 Model ANOVA F(4,46)=6.3 (p<.001) F(4,46)=4.8 (p=.005) INTERFERENCE dACC preSMA Intercept .54 ± .08 <.001 .63 ± .08 <.001 CY-BOCS --------------.005 ± .01 .591 Age -------------.02 ± .03 .508 Overall RT --------------------------Overall Acc -4.36 ± 1.92 .026 -3.41 ± 1.89 .074 CY-BOCS x Age --------------.008 ± .004 .061 Motion 1. 20 ± .72 .102 1.5 ± .79 .055 Adjusted R-Square 0.07 0.09

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F(5,63)=2.4 (p=.05)

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F(2,66)=3.7 (p=.03)

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Model ANOVA

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dACC .63 ± .11 <.001 -.02 ± .01 .172 .07 ± .04 .073 -.15 ± .16 .356 --------------4.27 ± 1.89 .023 --------------.12 ± .06 .049 -.01 ± .004 .075 -------------1.17 ±.86 .178 0.12 F(7,61)=2.3 (p=.04)

preSMA .73 ± .11 <.001 -.01 ± .01 .352 .06 ± .04 .123 -.16 ± .16 .321 --------------3.54 ± 1.86 .062 --------------.08 ± .06 .170 -.01 ± .004 .021 -------------1.46 ± .85 .089 0.11 F(7,61)=2.2 (p=.05)

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preSMA 1.65 ± .32 <.001 -.09 ± .05 .075 .09 ± .11 .454 .60 ± .59 .316 -.002 ± .001 .149 11.73 ± 4.02 .006* .11 ± .08 .172 --------------.04 ± .02 .026 --------------------------.25 F(7,43)=3.5 (p=.005)

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dACC 1.70 ± .34 <.001 -.11 ± .04 .012 .23 ± .12 .052 .89 ± .52 .134 -------------13.51 ± 3.69 <.001* .04 ± .08 .622 -.18 ± .21 .396 -.04 ± .02 .005* .07 ± .04 .083 -------------.36 F(8,42)=4.5 (p<.001)

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Intercept (grp:uOCD) CYBOCS Age Meds Inc RT Inc Acc CY-BOCs x Meds Age x Meds CY-BOCS x Age CY-BOCS x Meds x Age Motion Adjusted R-Square Model ANOVA INTERFERENCE

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Table S12. Obsessive-compulsive disorder (OCD) severity and posterior medial frontal cortex (pMFC) subregion function in pediatric unmedicated OCD (uOCD) and medicated OCD (mOCD) (region of interest (ROI) analysis)

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Note: aI = anterior insula, Acc = accuracy, CY-BOCS = Child Yale- Brown Obsessive Compulsive Scale, Inc = incongruent, Meds = medication, pMFC = Posterior medial frontal cortex, RT = Response time Motion refers to framewise displacement (6)

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Table S13. Obsessive-compulsive disorder (OCD) severity and error-related activations unmedicated OCD (uOCD) and medicated OCD (mOCD) vs. healthy controls (HC) (Wholebrain analysis)

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Predictor Cluster-level statistics* ERRORS pFWE-corr k Coordinates Z CY-BOCS, negative effect€ *pMFC .010 20 12, 17, 52 3.70 Med > Unmed Right aI/fO .048 59 57, 17, -5 3.82 Precuneus .026 70 3, -58, 61 3.92 Inc RT, negative effect Left Superior Parietal .011 85 -27, -52, 55 4.23 Inc Acc, positive effect pMFC .022 73 -3, 20, 28 4.26 Right middle frontal (6) .023 72 45, 11, 43 4.56 *Right aI/fO .011 15 36, 26, -5 3.89 € CY-BOCS x Age, negative effect *Posterior medial frontal cortex .013 17 -6, 20, 46 4.12 *Posterior medial frontal cortex .019 13 6, 14, 55 3.52 Note: * Clusters are significant at p < .05 with correction for family wise error across the whole brain or, if italicized, within search volumes (pMFC, right aI/fO, or left aI/fO) defined by the main effect of errors. € The effects of CYBOCs and CYBOCs-by-age interaction on pMFC response to errors were significant only for uOCD. aI/fO = anterior insula/frontal operculum, Acc = accuracy, CY-BOCS = Child Yale- Brown Obsessive Compulsive Scale, Inc = incongruent, Meds = Medication, pMFC = posterior medial frontal cortex, RT = response time

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6, 47, 40 57, -55, 37

4.14 4.23

.011 .029

93 73

-27, -46, 40 -12, -79, 37

4.48 4.36

.005 .052

111 62

24, -52, 40 -42, -1, 34

4.41 4.16

.003 .018

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51, -73, 28 -45, 61, 28

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.028

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.024

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INTERFERENCE CY-BOCS, positive effect Superior medial frontal Right Inferior Parietal Unmed > Med Left Superior Parietal Left Precuneus Age, positive effect Right Superior Parietal Left Precentral Age, negative effect Right Superior Parietal Left Superior Parietal Overall RT, negative Right Superior Parietal Overall Acc, negative Left Middle Frontal (dlPFC) CY-BOCS x Med Right Superior Parietal CY-BOCS x Age, positive effect Left Inferior Parietal Right Superior Parietal CY-BOCS x Age, negative effect * Left aI/fO Left Inferior Parietal

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Table S14. Obsessive-compulsive disorder (OCD) severity and interference-related activations in unmedicated OCD (uOCD) and medicated OCD (mOCD) vs. healthy controls (HC) (Wholebrain analysis)

Motion, positive Cerebellum <.001 193 6, -55, 23 4.35 Note: * Clusters are significant at p < .05 with correction for family wise error across the whole brain or, if italicized, within search volumes (pMFC, right aI/fO, or left aI/fO) defined by the main effect of errors.

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Motion = mean framewise displacement 28. Age, AAO, illness duration in years. a SES missing for 2 HC, 1 OCD. aI/fO = anterior insula/frontal operculum, AAO = age of onset, Acc = accuracy, Con = congruent, CY-BOCS = Child Yale-Brown Obsessive Compulsive Scale, HC = Healthy Control, Inc = incongruent, OCD = Obsessive Compulsive Disorder, pMFC = posterior medial frontal cortex, RT = response time

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Supplemental Figures

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Figure S1. Multisource Interference Task (MSIT) Design

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Figure S2. Dorsal accuracy (ACC) and pre-supplementary motor area (pre-SMA) region of interests (ROIS)

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Note: Dorsal ACC (red) and pre-SMA (yellow) were defined by conjunction of main effects for error and interference contrasts with Neurosynth middle and posterior MFC zones, respectively. MFC = medial frontal cortex

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Figure S3. Effects of age and performance on cingulo-opercular network function in pediatric unmedicated OCD (uOCD), medicated OCD (mOCD) and healthy youth (region of interest (ROI) analysis)

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Figure S4: Effects of obsessive-compulsive disorder (OCD) severity on cingulo-opercular function in pediatric unmedicated OCD (uOCD) and

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medicated OCD (mOCD).

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References

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1. de la Vega A, Chang LJ, Banich MT, Wager TD, Yarkoni T. Large-Scale Meta-Analysis of Human Medial Frontal Cortex Reveals Tripartite Functional Organization. J Neurosci. 2016;36:6553-6562. 2. Ridderinkhof KR, Ullsperger M, Crone EA, Nieuwenhuis S. The role of the medial frontal cortex in cognitive control. Science. 2004;306:443-447. 3. Fair DA, Dosenbach NU, Church JA, Cohen AL, Brahmbhatt S, Miezin FM, Barch DM, Raichle ME, Petersen SE, Schlaggar BL. Development of distinct control networks through segregation and integration. Proc Natl Acad Sci U S A. 2007;104:13507-13512. 4. Dosenbach NU, Visscher KM, Palmer ED, Miezin FM, Wenger KK, Kang HC, Burgund ED, Grimes AL, Schlaggar BL, Petersen SE. A core system for the implementation of task sets. Neuron. 2006;50:799-812. 5. Hester R, Fassbender C, Garavan H. Individual differences in error processing: a review and reanalysis of three event-related fMRI studies using the GO/NOGO task. Cereb Cortex. 2004;14:986-994. 6. Power JD, Barnes KA, Snyder AZ, Schlaggar BL, Petersen SE. Spurious but systematic correlations in functional connectivity MRI networks arise from subject motion. NeuroImage. 2012;59:2142-2154.