Independent component analysis of resting state activity in pediatric obsessive-compulsive disorder

Cortical and subcortical contributions to non-motor inhibitory control: an fMRI study

Inhibition is a core executive cognitive function. However, the neural correlates of non-motor inhibitory control are not well understood. We investigated this question using functional Magnetic Resonance Imaging (fMRI) and a simple Count Go/NoGo task (n = 23), and further explored the causal relationships between activated brain regions. We found that the Count NoGo task activated a distinct pattern in the subcortical basal ganglia, including bilateral ventral anterior/lateral nucleus of thalamus (VA/VL), globus pallidus/putamen (GP/putamen), and subthalamic nucleus (STN). Stepwise regressions and mediation analyses revealed that activations in these region(s) were modulated differently by only 3 cortical regions i.e. the right inferior frontal gyrus/insula (rIFG/insula), along with left IFG/insula, and anterior cingulate cortex/supplementary motor area (ACC/SMA). The activations of bilateral VA/VL were modulated by both rSTN and rIFG/insula (with rGP/putamen as a mediator) independently, and the activation of rGP/putamen was modulated by ACC/SMA, with rIFG/insula as a mediator. Our findings provide the neural correlates of inhibitory control of counting and causal relationships between them, and strongly suggest that both indirect and hyperdirect pathways of the basal ganglia are involved in the Count NoGo condition.

Alterations of regional spontaneous brain activity in obsessive-compulsive disorders: A meta-analysis

BACKGROUND

Recent studies using resting-state functional magnetic resonance imaging (rs-fMRI) demonstrate that there is aberrant regional spontaneous brain activity in obsessive-compulsive disorders (OCD). Nevertheless, the results of previous studies are contradictory, especially in the abnormal brain regions and the directions of their activities. It is necessary to perform a meta-analysis to identify the common pattern of altered regional spontaneous brain activity in patients with OCD.

METHODS

The present study conducted a systematic search for studies in English published up to May 2023 in PubMed, Web of Science, and Embase. These studies measured differences in regional spontaneous brain activity at the whole brain level using regional homogeneity (ReHo), the amplitude of low-frequency fluctuations (ALFF) and the fractional amplitude of low-frequency fluctuations (fALFF). Then the Anisotropic effect-size version of seed-based d mapping (AES-SDM) was used to investigate the consistent abnormality of regional spontaneous brain activity in patients with OCD.

RESULTS

27 studies (33 datasets) were included with 1256 OCD patients (650 males, 606 females) and 1176 healthy controls (HCs) (588 males, 588 females). Compared to HCs, patients with OCD showed increased spontaneous brain activity in the right inferior parietal gyrus (Brodmann Area 39), left median cingulate and paracingulate gyri (Brodmann Area 24), bilateral inferior cerebellum, right middle frontal gyrus (Brodmann Area 46), left inferior frontal gyrus in triangular part (Brodmann Area 45) and left middle frontal gyrus in orbital part (Brodmann Area 11). Meanwhile, decreased spontaneous brain activity was identified in the right precentral gyrus (Brodmann Area 4), right insula (Brodmann Area 48), left postcentral gyrus (Brodmann Area 43), bilateral superior cerebellum and left caudate (Brodmann Area 25).

CONCLUSIONS

This meta-analysis provided a quantitative review of spontaneous brain activity in OCD. The results demonstrated that the brain regions in the frontal lobe, sensorimotor cortex, cerebellum, caudate and insula are crucially involved in the pathophysiology of OCD. This research contributes to the understanding of the pathophysiologic mechanism underlying OCD and could provide a new perspective on future diagnosis and treatment of OCD.

Dissecting Psychiatric Heterogeneity and Comorbidity with Core Region-Based Machine Learning

Machine learning approaches are increasingly being applied to neuroimaging data from patients with psychiatric disorders to extract brain-based features for diagnosis and prognosis. The goal of this review is to discuss recent practices for evaluating machine learning applications to obsessive-compulsive and related disorders and to advance a novel strategy of building machine learning models based on a set of core brain regions for better performance, interpretability, and generalizability. Specifically, we argue that a core set of co-altered brain regions (namely 'core regions') comprising areas central to the underlying psychopathology enables the efficient construction of a predictive model to identify distinct symptom dimensions/clusters in individual patients. Hypothesis-driven and data-driven approaches are further introduced showing how core regions are identified from the entire brain. We demonstrate a broadly applicable roadmap for leveraging this core set-based strategy to accelerate the pursuit of neuroimaging-based markers for diagnosis and prognosis in a variety of psychiatric disorders.

Impairment of arbitration between model-based and model-free reinforcement learning in obsessive-compulsive disorder

Introduction

Obsessive-compulsive disorder (OCD) is characterized by an imbalance between goal-directed and habitual learning systems in behavioral control, but it is unclear whether these impairments are due to a single system abnormality of the goal-directed system or due to an impairment in a separate arbitration mechanism that selects which system controls behavior at each point in time.

Methods

A total of 30 OCD patients and 120 healthy controls performed a 2-choice, 3-stage Markov decision-making paradigm. Reinforcement learning models were used to estimate goal-directed learning (as model-based reinforcement learning) and habitual learning (as model-free reinforcement learning). In general, 29 high Obsessive-Compulsive Inventory-Revised (OCI-R) score controls, 31 low OCI-R score controls, and all 30 OCD patients were selected for the analysis.

Results

Obsessive-compulsive disorder (OCD) patients showed less appropriate strategy choices than controls regardless of whether the OCI-R scores in the control subjects were high (p = 0.012) or low (p < 0.001), specifically showing a greater model-free strategy use in task conditions where the model-based strategy was optimal. Furthermore, OCD patients (p = 0.001) and control subjects with high OCI-R scores (H-OCI-R; p = 0.009) both showed greater system switching rather than consistent strategy use in task conditions where model-free use was optimal.

Conclusion

These findings indicated an impaired arbitration mechanism for flexible adaptation to environmental demands in both OCD patients and healthy individuals reporting high OCI-R scores.

Preliminary Observations of Resting-State Magnetoencephalography in Nonmedicated Children with Obsessive-Compulsive Disorder

Background: Cortico-striato-thalamo-cortical (CSTC) network alterations are hypothesized to contribute to symptoms of obsessive-compulsive disorder (OCD). To date, very few studies have examined whether CSTC network alterations are present in children with OCD, who are medication naive. Medication-naive pediatric imaging samples may be optimal to study neural correlates of illness and identify brain-based markers, given the proximity to illness onset. Methods: Magnetoencephalography (MEG) data were analyzed at rest, in 18 medication-naive children with OCD (M = 12.1 years ±2.0 standard deviation [SD]; 10 M/8 F) and 13 typically developing children (M = 12.3 years ±2.2 SD; 6 M/7 F). Whole-brain MEG-derived resting-state functional connectivity (rs-fc), for alpha- and gamma-band frequencies were compared between OCD and typically developing (control) groups. Results: Increased MEG-derived rs-fc across alpha- and gamma-band frequencies was found in the OCD group compared to the control group. Increased MEG-derived rs-fc at alpha-band frequencies was evident across a number of regions within the CSTC circuitry and beyond, including the cerebellum and limbic regions. Increased MEG-derived rs-fc at gamma-band frequencies was restricted to the frontal and temporal cortices. Conclusions: This MEG study provides preliminary evidence of altered alpha and gamma networks, at rest, in medication-naive children with OCD. These results support prior findings pointing to the relevance of CSTC circuitry in pediatric OCD and further support accumulating evidence of altered connectivity between regions that extend beyond this network, including the cerebellum and limbic regions. Given the substantial portion of children and youth whose OCD symptoms do not respond to conventional treatments, our findings have implications for future treatment innovation research aiming to target and track whether brain patterns associated with having OCD may change with treatment and/or predict treatment response.

Differential patterns of association between resting-state functional connectivity networks and stress in OCD patients

Obsessive-compulsive disorder (OCD) is a highly prevalent psychiatric disorder that is characterized by its complex pathophysiology and heterogenous presentation. Multiple studies to date have identified a variety of factors that are involved in the development of symptoms, but little is known about how these affect brain function. In this study, we have tried to understand how stress, one of the most studied risk factors for OCD, may influence resting-state functional connectivity (rsFC) by comparing resting brain activity of OCD patients with healthy control subjects, while assessing self-reported levels of perceived stress using the Perceived Stress Scale-10 (PSS-10). Seventy-five OCD patients and seventy-one healthy matched control subjects were enrolled in this study, where we used a data-driven, independent component analysis approach. Our results show differences in connectivity between patients and healthy controls involving the dorsal attention (DAN) and lateral visual networks, with patients presenting increased rsFC within the DAN and decreased rsFC within the lateral visual network. Moreover, connectivity in the anterior default mode (aDMN), dorsal attention and basal ganglia networks was associated with PSS scores in OCD patients. Specifically, rsFC within the DAN and aDMN was positively correlated with PSS scores, while the opposite was observed for the basal ganglia network. This study is the first to report such association between rsFC alterations and self-reported stress levels. Our findings are relevant in the context of OCD pathophysiology given evidence of functional dysconnectivity involving the same networks in previous OCD studies and the possible involvement of these changes in the generation of obsessions.

Prediction of Obsessive-Compulsive Disorder: Importance of Neurobiology-Aided Feature Design and Cross-Diagnosis Transfer Learning

BACKGROUND

Machine learning applications using neuroimaging provide a multidimensional, data-driven approach that captures the level of complexity necessary for objectively aiding diagnosis and prognosis in psychiatry. However, models learned from small training samples often have limited generalizability, which continues to be a problem with automated diagnosis of mental illnesses such as obsessive-compulsive disorder (OCD). Earlier studies have shown that features incorporating prior neurobiological knowledge of brain function and combining brain parcellations from various sources can potentially improve the overall prediction. However, it is unknown whether such knowledge-driven methods can provide a performance that is comparable to state-of-the-art approaches based on neural networks.

METHODS

In this study, we apply a transparent and explainable multiparcellation ensemble learning framework EMPaSchiz (Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction) to the task of predicting OCD, based on a resting-state functional magnetic resonance imaging dataset of 350 subjects. Furthermore, we apply transfer learning using the features found effective for schizophrenia to OCD to leverage the commonality in brain alterations across these psychiatric diagnoses.

RESULTS

We show that our knowledge-based approach leads to a prediction performance of 80.3% accuracy for OCD diagnosis that is better than domain-agnostic and automated feature design using neural networks. Furthermore, we show that a selection of reduced feature sets can be transferred from schizophrenia to the OCD prediction model without significant loss in prediction performance.

CONCLUSIONS

This study presents a machine learning framework for OCD prediction with neurobiology-aided feature design using resting-state functional magnetic resonance imaging that is generalizable and reasonably interpretable.

A Unified Functional Network Target for Deep Brain Stimulation in Obsessive-Compulsive Disorder

BACKGROUND

Multiple deep brain stimulation (DBS) targets have been proposed for treating intractable obsessive-compulsive disorder (OCD). Here, we investigated whether stimulation effects of different target sites would be mediated by one common or several segregated functional brain networks.

METHODS

First, seeding from active electrodes of 4 OCD patient cohorts (N = 50) receiving DBS to anterior limb of the internal capsule or subthalamic nucleus zones, optimal functional connectivity profiles for maximal Yale-Brown Obsessive Compulsive Scale improvements were calculated and cross-validated in leave-one-cohort-out and leave-one-patient-out designs. Second, we derived optimal target-specific connectivity patterns to determine brain regions mutually predictive of clinical outcome for both targets and others predictive for either target alone. Functional connectivity was defined using resting-state functional magnetic resonance imaging data acquired in 1000 healthy participants.

RESULTS

While optimal functional connectivity profiles showed both commonalities and differences between target sites, robust cross-predictions of clinical improvements across OCD cohorts and targets suggested a shared network. Connectivity to the anterior cingulate cortex, insula, and precuneus, among other regions, was predictive regardless of stimulation target. Regions with maximal connectivity to these commonly predictive areas included the insula, superior frontal gyrus, anterior cingulate cortex, and anterior thalamus, as well as the original stereotactic targets.

CONCLUSIONS

Pinpointing the network modulated by DBS for OCD from different target sites identified a set of brain regions to which DBS electrodes associated with optimal outcomes were functionally connected-regardless of target choice. On these grounds, we establish potential brain areas that could prospectively inform additional or alternative neuromodulation targets for obsessive-compulsive disorder.

Classification of Obsessive-Compulsive Disorder Using Distance Correlation on Resting-State Functional MRI Images

Both the Pearson correlation and partial correlation methods have been widely used in the resting-state functional MRI (rs-fMRI) studies. However, they can only measure linear relationship, although partial correlation excludes some indirect effects. Recent distance correlation can discover both the linear and non-linear dependencies. Our goal was to use the multivariate pattern analysis to compare the ability of such three correlation methods to distinguish between the patients with obsessive-compulsive disorder (OCD) and healthy control subjects (HCSs), so as to find optimal correlation method. The main process includes four steps. First, the regions of interest are defined by automated anatomical labeling (AAL). Second, functional connectivity (FC) matrices are constructed by the three correlation methods. Third, the best discriminative features are selected by support vector machine recursive feature elimination (SVM-RFE) with a stratified N-fold cross-validation strategy. Finally, these discriminative features are used to train a classifier. We had a total of 128 subjects out of which 61 subjects had OCD and 67 subjects were normal. All the three correlation methods with SVM have achieved good results, among which distance correlation is the best [accuracy = 93.01%, specificity = 89.71%, sensitivity = 95.08%, and area under the receiver-operating characteristic curve (AUC) = 0.94], followed by Pearson correlation and partial correlation is the last. The most discriminative regions of the brain for distance correlation are right dorsolateral superior frontal gyrus, orbital part of left superior frontal gyrus, orbital part of right middle frontal gyrus, right anterior cingulate and paracingulate gyri, left the supplementary motor area, and right precuneus, which are the promising biomarkers of OCD.

Associations of observed preschool performance monitoring with brain functional connectivity in adolescence

Monitoring one's performance helps detect errors and adapt to prevent future mistakes. However, elevated performance monitoring is associated with increased checking behaviors and perfectionism and is characteristic of multiple psychiatric disorders. Understanding how heightened performance monitoring in early childhood relates to subsequent brain connectivity may elucidate mechanistic risk factors that influence brain and psychiatric outcomes. The aim of this study was to examine the association between performance monitoring in preschool-aged children and functional connectivity during adolescence. In the current prospective longitudinal study, we performed seed-based functional connectivity analysis using a dorsal anterior cingulate cortex (dACC) seed to assess brain-behavior relationships between observationally coded performance monitoring in preschool-aged children and adolescent functional connectivity (n = 79). We also utilized enrichment analysis to investigate network-level connectome-wide associations. Seed-based analysis revealed negative correlations between preschool performance monitoring and adolescent fc between dACC and orbitofrontal and dorsolateral prefrontal cortex while a positive correlation was observed between dACC-occipital cortex connectivity. Enrichment analysis revealed a negative correlation between preschool performance monitoring and connectivity between motor (MOT) - cingulo-opercular (CO) and salience (SN) - Reward (REW) and a positive correlation with MOT-DMN, and cerebellum (CB) - motor connectivity. Elevated performance monitoring in early childhood is associated with functional connectivity during adolescence in regions and networks associated with cognitive control, sensorimotor processing and cortico-striatal-thalamic-cortico (CTSC) aberrations. These regions and networks are implicated in psychiatric disorders characterized by elevated performance monitoring. Findings shed light on a mechanistic risk factor in early childhood with long-term associations with neural functioning.

Altered fronto-amygdalar functional connectivity predicts response to cognitive behavioral therapy in pediatric obsessive-compulsive disorder

BACKGROUND

Based on findings from adults with obsessive-compulsive disorder (OCD), this study examined alterations in resting-state functional connectivity (rs-fc) between the basolateral amygdala (BLA) and the ventromedial prefrontal cortex (vmPFC) in children and adolescents with OCD. We also assessed whether such BLA-vmPFC connectivity changed with or predicted response to exposure and response prevention (E/RP), the first-line treatment for pediatric OCD, given the involvement of these regions in fear processing, regulation, and extinction learning-a probable mechanism of action of E/RP.

METHODS

Resting state functional magnetic resonance imaging scans were acquired from 25 unmedicated, treatment-naïve pediatric patients with OCD (12.8 ± 2.9 years) and 23 age- and sex-matched healthy controls (HCs; 11.0 ± 3.3 years). Patients completed a 12-16-week E/RP intervention for OCD. Participants were rescanned after the 12-16-week period. ANCOVAs tested group differences in baseline rs-fc. Cross-lagged panel models examined relationships between BLA-vmPFC rs-fc and OCD symptoms pre- and posttreatment. All tests were adjusted for participants' age, sex, and head motion.

RESULTS

Right BLA-vmPFC rs-fc was significantly reduced (more negative) in patients with OCD relative to HCs at baseline, and increased following treatment. In patients, more positive (less negative) right BLA-vmPFC rs-fc pretreatment predicted greater OCD symptoms reduction posttreatment. Changes in BLA-vmPFC rs-fc was unassociated with change in OCD symptoms pre- to posttreatment.

CONCLUSIONS

These results provide further evidence of the BLA-vmPFC pathway as a potential target for novel treatments or prevention strategies aimed at facilitating adaptive learning and fear extinction in children with OCD or subclinical OCD symptoms.

The divided brain: Functional brain asymmetry underlying self-construal

Self-construal (orientations of independence and interdependence) is a fundamental concept that guides human behaviour, and it is linked to a large number of brain regions. However, understanding the connectivity of these regions and the critical principles underlying these self-functions are lacking. Because brain activity linked to self-related processes are intrinsic, the resting-state method has received substantial attention. Here, we focused on resting-state functional connectivity matrices based on brain asymmetry as indexed by the differential partition of the connectivity located in mirrored positions of the two hemispheres, hemispheric specialization measured using the intra-hemispheric (left or right) connectivity, brain communication via inter-hemispheric interactions, and global connectivity as the sum of the two intra-hemispheric connectivity. Combining machine learning techniques with hypothesis-driven network mapping approaches, we demonstrated that orientations of independence and interdependence were best predicted by the asymmetric matrix compared to brain communication, hemispheric specialization, and global connectivity matrices. The network results revealed that there were distinct asymmetric connections between the default mode network, the salience network and the executive control network which characterise independence and interdependence. These analyses shed light on the importance of brain asymmetry in understanding how complex self-functions are optimally represented in the brain networks.

Defining data-driven subgroups of obsessive-compulsive disorder with different treatment responses based on resting-state functional connectivity

Characterization of obsessive-compulsive disorder (OCD), like other psychiatric disorders, suffers from heterogeneities in its symptoms and therapeutic responses, and identification of more homogeneous subgroups may help to resolve the heterogeneity. We aimed to identify the OCD subgroups based on resting-state functional connectivity (rsFC) and to explore their differences in treatment responses via a multivariate approach. From the resting-state functional MRI data of 107 medication-free OCD patients and 110 healthy controls (HCs), we selected rsFC features, which discriminated OCD patients from HCs via support vector machine (SVM) analyses. With the selected brain features, we subdivided OCD patients into subgroups using hierarchical clustering analyses. We identified 35 rsFC features that achieved a high sensitivity (82.74%) and specificity (76.29%) in SVM analyses. The OCD patients were subdivided into two subgroups, which did not show significant differences in their demographic and clinical backgrounds. However, one of the OCD subgroups demonstrated more impaired rsFC that was involved either within the default mode network (DMN) or between DMN brain regions and other network regions. This subgroup also showed both lower improvements in symptom severity in the 16-week follow-up visit and lower responder percentage than the other subgroup. Our results highlight that not only abnormalities within the DMN but also aberrant rsFC between the DMN and other networks may contribute to the treatment response and support the importance of these neurobiological alterations in OCD patients. We suggest that abnormalities in these connectivity may play predictive biomarkers of treatment response, and aid to build more optimal treatment strategies.

Resting-state functional connectivity in drug-naive pediatric patients with Tourette syndrome and obsessive-compulsive disorder

Previous studies in cohorts of Tourette syndrome (TS) or obsessive-compulsive disorder (OCD) patients have not clarified whether these two disorders represent two clinical conditions or they are distinct clinical phenotypes of a common disease spectrum. The study aimed to compare functional connectivity (FC) patterns in a pediatric drug-naive cohort of 16 TS patients without any comorbidity (TS), 14 TS patients with OCD (TS + OCD), and 10 pure OCD patients as well as 11 matched controls that underwent resting state fMRI. Via independent component analysis, we examined FC in the basal ganglia (BGN), sensorimotor (SMN), cerebellum (CBN), frontoparietal (FPN), default-mode (DMN), orbitofrontal (OBFN), and salience (SAN) networks among the above cohorts and their association with clinical measures. Compared to controls, TS and TS + OCD patients showed higher FC in the BGN, SMN, CBN and DMN and lower FC in the FPN and SAN. The TS and TS + OCD groups showed comparable FC in all networks. In contrast to controls, OCD patients exhibited increased FC in the BGN, SMN, CBN, DMN, FPN, and SAN. OCD patients also showed higher FC in CBN and FPN when compared with TS and TS + OCD patients both separately and as one group. Tic severity negatively correlated with FC in CBN and FPN in the TS group, while the compulsiveness scores positively correlated with the same two networks in OCD patients. Our findings suggest common FC changes in TS and TS + OCD patients. In contrast, OCD is characterized by a distinctive pattern of FC changes prominently involving the CBN and FPN.

Towards a brain-based predictome of mental illness

Neuroimaging-based approaches have been extensively applied to study mental illness in recent years and have deepened our understanding of both cognitively healthy and disordered brain structure and function. Recent advancements in machine learning techniques have shown promising outcomes for individualized prediction and characterization of patients with psychiatric disorders. Studies have utilized features from a variety of neuroimaging modalities, including structural, functional, and diffusion magnetic resonance imaging data, as well as jointly estimated features from multiple modalities, to assess patients with heterogeneous mental disorders, such as schizophrenia and autism. We use the term "predictome" to describe the use of multivariate brain network features from one or more neuroimaging modalities to predict mental illness. In the predictome, multiple brain network-based features (either from the same modality or multiple modalities) are incorporated into a predictive model to jointly estimate features that are unique to a disorder and predict subjects accordingly. To date, more than 650 studies have been published on subject-level prediction focusing on psychiatric disorders. We have surveyed about 250 studies including schizophrenia, major depression, bipolar disorder, autism spectrum disorder, attention-deficit hyperactivity disorder, obsessive-compulsive disorder, social anxiety disorder, posttraumatic stress disorder, and substance dependence. In this review, we present a comprehensive review of recent neuroimaging-based predictomic approaches, current trends, and common shortcomings and share our vision for future directions.

Morphopathological changes in obsessive-compulsive disorder

The pathophysiology of the obsessive-compulsive disorder (OCD) has been studied for many years using several structural magnetic resonance imaging, discovering that the anomalies of function and structure of the brain are widespread, they involve different areas, structures and circuits with a complex interconnectivity. More than that, these anomalies cover all the life of a patient, from early childhood, due to variations of developmental stages until adult life. The research is highly important also because OCD has a major hereditary factor, with the phenotype variance between 27–47% due to hereditary factors. Under this paper, that follows last 10 years studies in this area, we will find some relevant findings consisting on neuroanatomic changes, the morphology findings of striatum, globus pallidus and thalamus, the blood flow circuit changes in various regions of the brain, brain connectivity and various correlations of them. Not to forget that OCD must be understand as an emotional disorder but in the same time as a cognitive disorder too. This approach highlights the abnormalities that have been found in brain regions involved in the cognitive and emotional behavior, as for example: extended temporal, parietal, and occipital regions, anterior cingulate, frontal gyrus, amygdala.

MRI Insights Into Adolescent Neurocircuitry-A Vision for the Future

Adolescence is the time of onset of many psychiatric disorders. Half of pediatric patients present with comorbid psychiatric disorders that complicate both their medical and psychiatric care. Currently, diagnosis and treatment decisions are based on symptoms. The field urgently needs brain-based diagnosis and personalized care. Neuroimaging can shed light on how aberrations in brain circuits might underlie psychiatric disorders and their development in adolescents. In this perspective article, we summarize recent MRI literature that provides insights into development of psychiatric disorders in adolescents. We specifically focus on studies of brain structural and functional connectivity. Ninety-six included studies demonstrate the potential of MRI to assess psychiatrically relevant constructs, diagnose psychiatric disorders, predict their development or predict response to treatment. Limitations of the included studies are discussed, and recommendations for future research are offered. We also present a vision for the role that neuroimaging may play in pediatrics and primary care in the future: a routine neuropsychological and neuropsychiatric imaging (NPPI) protocol for adolescent patients, which would include a 30-min brain scan, a quality control and safety read of the scan, followed by computer-based calculation of the structural and functional brain network metrics that can be compared to the normative data by the pediatrician. We also perform a cost-benefit analysis to support this vision and provide a roadmap of the steps required for this vision to be implemented.

Altered network connectivity predicts response to cognitive-behavioral therapy in pediatric obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is commonly associated with alterations in cortico-striato-thalamo-cortical brain networks. Yet, recent investigations of large-scale brain networks suggest that more diffuse alterations in brain connectivity may underlie its pathophysiology. Few studies have assessed functional connectivity within or between networks across the whole brain in pediatric OCD or how patterns of connectivity associate with treatment response. Resting-state functional magnetic resonance imaging scans were acquired from 25 unmedicated, treatment-naive children and adolescents with OCD (12.8 ± 2.9 years) and 23 matched healthy control (HC) participants (11.0 ± 3.3 years) before participants with OCD completed a course of cognitive-behavioral therapy (CBT). Participants were re-scanned after 12-16 weeks. Whole-brain connectomic analyses were conducted to assess baseline group differences and group-by-time interactions, corrected for multiple comparisons. Relationships between functional connectivity and OCD symptoms pre- and post-CBT were examined using longitudinal cross-lagged panel modeling. Reduced connectivity in OCD relative to HC participants was detected between default mode and task-positive network regions. Greater (less altered) connectivity between left angular gyrus and left frontal pole predicted better response to CBT in the OCD group. Altered connectivity between task-positive and task-negative networks in pediatric OCD may contribute to the impaired control over intrusive thoughts early in the illness. This is the first study to show that altered connectivity between large-scale network regions may predict response to CBT in pediatric OCD, highlighting the clinical relevance of these networks as potential circuit-based targets for the development of novel treatments.

Frontoparietal and salience network alterations in obsessive–compulsive disorder: insights from independent component and sliding time window analyses

BACKGROUND

Resting-state functional MRI (fMRI) studies commonly report alterations in 3 core networks in obsessive–compulsive disorder (OCD) — the frontoparietal network, the default mode network and the salience network — defined by functionally connected infraslow oscillations in ongoing brain activity. However, most of these studies observed static functional connectivity in the brains of patients with OCD.

METHODS

To investigate dynamic functional connectivity alterations and widen the evidence base toward the triple network model in OCD, we performed group-based independent component and sliding time window analyses in 49 patients with OCD and 41 healthy controls.

RESULTS

The traditional independent component analysis showed alterations in the left frontoparietal network as well as between the left and right frontoparietal networks in patients with OCD compared with healthy controls. For dynamic functional connectivity, the sliding time window approach revealed peak dysconnectivity between the left and right frontoparietal networks and between the left frontoparietal network and the salience network.

LIMITATIONS

The number of independent components, noise in the resting-state fMRI images, the heterogeneity of the OCD sample, and comorbidities and medication status in the patients could have biased the results.

CONCLUSION

Disrupted modulation of these intrinsic brain networks may contribute to the pathophysiology of OCD.

Toward identifying reproducible brain signatures of obsessive-compulsive profiles: rationale and methods for a new global initiative

BACKGROUND

Obsessive-compulsive disorder (OCD) has a lifetime prevalence of 2-3% and is a leading cause of global disability. Brain circuit abnormalities in individuals with OCD have been identified, but important knowledge gaps remain. The goal of the new global initiative described in this paper is to identify robust and reproducible brain signatures of measurable behaviors and clinical symptoms that are common in individuals with OCD. A global approach was chosen to accelerate discovery, to increase rigor and transparency, and to ensure generalizability of results.

METHODS

We will study 250 medication-free adults with OCD, 100 unaffected adult siblings of individuals with OCD, and 250 healthy control subjects at five expert research sites across five countries (Brazil, India, Netherlands, South Africa, and the U.S.). All participants will receive clinical evaluation, neurocognitive assessment, and magnetic resonance imaging (MRI). The imaging will examine multiple brain circuits hypothesized to underlie OCD behaviors, focusing on morphometry (T1-weighted MRI), structural connectivity (Diffusion Tensor Imaging), and functional connectivity (resting-state fMRI). In addition to analyzing each imaging modality separately, we will also use multi-modal fusion with machine learning statistical methods in an attempt to derive imaging signatures that distinguish individuals with OCD from unaffected siblings and healthy controls (Aim #1). Then we will examine how these imaging signatures link to behavioral performance on neurocognitive tasks that probe these same circuits as well as to clinical profiles (Aim #2). Finally, we will explore how specific environmental features (childhood trauma, socioeconomic status, and religiosity) moderate these brain-behavior associations.

DISCUSSION

Using harmonized methods for data collection and analysis, we will conduct the largest neurocognitive and multimodal-imaging study in medication-free subjects with OCD to date. By recruiting a large, ethno-culturally diverse sample, we will test whether there are robust biosignatures of core OCD features that transcend countries and cultures. If so, future studies can use these brain signatures to reveal trans-diagnostic disease dimensions, chart when these signatures arise during development, and identify treatments that target these circuit abnormalities directly. The long-term goal of this research is to change not only how we conceptualize OCD but also how we diagnose and treat it.

The resting-brain of obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is one of the most debilitating psychiatric conditions, having a dramatic impact on patients' daily living. In this work, we aimed to explore resting-state functional connectivity in OCD patients, using an independent component analysis. Eighty individuals (40 patients and 40 healthy controls) performed a resting state fMRI protocol. OCD patients displayed reduced functional connectivity (FC) in visual and sensorimotor networks. In addition, patients displayed decreased FC between sensory networks and increased FC between default-mode and cerebellar networks.

Sertraline Effects on Striatal Resting-State Functional Connectivity in Youth With Obsessive-Compulsive Disorder: A Pilot Study

OBJECTIVE

Foundational knowledge on neural circuitry underlying pediatric obsessive-compulsive disorder (OCD) and how it changes during standard treatment is needed to provide the basis for conceptualization and development of novel targeted treatments. This study explored the effects of sertraline, a selective serotonin reuptake inhibitor, on resting-state functional connectivity in cortico-striatal-thalamic-cortical circuits in pediatric OCD.

METHOD

Medication-free youths with OCD (n = 14) and healthy controls (n = 14) were examined at baseline and 12 weeks with resting-state functional magnetic resonance imaging. Between scan sessions, participants with OCD received 12 weeks of sertraline. For each scan, seed-based whole-brain resting-state functional connectivity analyses were conducted with 6 striatal seeds. Analysis of variance examined the interaction between group and time on striatal connectivity, including cluster-based thresholding to correct for multiple tests. Connectivity changes within circuits identified in group analyses were correlated with clinical change.

RESULTS

Two significant group-by-time effects in the OCD group showed increased striatal connectivity from baseline to 12 weeks compared with controls. Circuits demonstrating this pattern included the right putamen with the left frontal cortex and insula and the left putamen with the left frontal cortex and pre- and post-central cortices. Increase in connectivity in the left putamen circuit was significantly correlated with clinical improvement on the Children's Yale-Brown Obsessive-Compulsive Scale score (r = -0.58, p = .03).

CONCLUSION

Sertraline appears to affect specific striatal-based circuits in pediatric OCD, and these changes in part could account for clinical improvement. Future work is needed to confirm these preliminary findings, which would facilitate identification of circuit-based targets for novel treatment development.

CLINICAL TRIAL REGISTRATION INFORMATION

Effects of Sertraline on Brain Connectivity in Adolescents with OCD; https://clinicaltrials.gov/; NCT02797808.

Diagnostic neuroimaging markers of obsessive-compulsive disorder: Initial evidence from structural and functional MRI studies

As of yet, no diagnostic biomarkers are available for obsessive-compulsive disorder (OCD), and its diagnosis relies entirely upon the recognition of behavioural features assessed through clinical interview. Neuroimaging studies have shown that various brain structures are abnormal in OCD patients compared to healthy controls. However, the majority of these results are based on average differences between groups, which limits diagnostic usage in clinical practice. In recent years, a growing number of studies have applied multivariate pattern analysis (MVPA) techniques on neuroimaging data to extract patterns of altered brain structure, function and connectivity typical for OCD. MVPA techniques can be used to develop predictive models that extract regularities in data to classify individual subjects based on their diagnosis. In the present paper, we reviewed the literature of MVPA studies using data from different imaging modalities to distinguish OCD patients from controls. A systematic search retrieved twelve articles that fulfilled the inclusion and exclusion criteria. Reviewed studies have been able to classify OCD diagnosis with accuracies ranging from 66% up to 100%. Features important for classification were different across imaging modalities and widespread throughout the brain. Although studies have shown promising results, sample sizes used are typically small which can lead to high variance of the estimated model accuracy, cohort-specific solutions and lack of generalizability of findings. Some of the challenges are discussed that need to be overcome in order to move forward toward clinical applications.

Imbalanced functional link between reward circuits and the cognitive control system in patients with obsessive-compulsive disorder

Altered reward processing and cognitive deficits are often observed in patients with obsessive-compulsive disorder (OCD); however, whether the imbalance in activity between reward circuits and the cognitive control (CC) system is associated with compulsive behavior remains unknown. Sixty-eight OCD patients and 33 cognitively normal (CN) healthy subjects participated in this resting-state functional magnetic resonance imaging study. Alterations in the functional connectivity between reward circuits and the CC system were quantitatively assessed and compared between the groups. A Granger causality analysis was used to determine the causal informational influence between and within reward circuits and the CC system across all subjects. OCD patients showed a dichotomous pattern of enhanced functional coupling in their reward circuits and a weakened functional coupling in their CC system when compared to CN subjects. Neural correlates of compulsive behavior were primarily located in the reward circuits and CC system in OCD patients. Importantly, the CC system exerted a reduced interregional causal influence over the reward system in OCD patients relative to its effect in CN subjects. The limitations of this study are that it was a cross-sectional study and the potential effects of environmental and genetic factors were not explored. OCD patients showed an imbalance in the functional link between reward circuits and the CC system at rest. This bias toward a loss of control may define a pathological state in which subjects are more vulnerable to engaging in compulsive behaviors.

Investigation of a Mobile "Serious Game" in the Treatment of Obsessive-Compulsive Disorder: A Pilot Study

OBJECTIVE

Exposure and response prevention (ERP) therapy is considered a first-line treatment for obsessive-compulsive disorder (OCD). Dysregulation in the cortico-striato-thalamo-cortical (CSTC) circuit has been implicated in the pathophysiology of OCD, as have decreased functional connectivity (FC) between the dorsal anterior cingulate cortex (dACC) and the prefrontal cortex and increased FC between the dACC and the basal ganglia. We hypothesized that a new ERP-inspired mobile "serious game" would improve clinical symptoms in OCD and that symptom improvement would be associated with altered FC within CSTC.

MATERIALS AND METHODS

Fifteen OCD subjects and 15 healthy controls were recruited. All subjects completed questionnaires covering demographic data, the Yale-Brown Obsessive-Compulsive Scale, the Beck Depressive Inventory, and the Beck Anxiety Inventory. In addition, all subjects were scanned at baseline to assess brain FC using resting-state functional magnetic resonance imaging.

RESULTS

After 3 weeks of gameplay, FC from the left dACC seed to the right frontal precentral gyrus and from the right dACC seed to the left inferior frontal gyrus and the right middle frontal gyrus, increased in the OCD group. Responders showed increased brain connectivity from the left dACC seed to the right superior frontal gyrus compared with nonresponders.

CONCLUSION

Our results suggest that serious games may improve symptoms in OCD and that this improvement may be related to increased brain connectivity between the dACC and the prefrontal cortex. Further exploration is needed to assess the potential role of serious games in OCD treatment.

The role of stress in the pathogenesis and maintenance of obsessive-compulsive disorder

Individuals with obsessive-compulsive disorder often identify psychosocial stress as a factor that exacerbates their symptoms, and many trace the onset of symptoms to a stressful period of life or a discrete traumatic incident. However, the pathophysiological relationship between stress and obsessive-compulsive disorder remains poorly characterized: it is unclear whether trauma or stress is an independent cause of obsessive-compulsive disorder symptoms, a triggering factor that interacts with a preexisting diathesis, or simply a nonspecific factor that can exacerbate obsessive-compulsive disorder along with other aspects of psychiatric symptomatology. Nonetheless, preclinical research has demonstrated that stress has conspicuous effects on corticostriatal and limbic circuitry. Specifically, stress can lead to neuronal atrophy in frontal cortices (particularly the medial prefrontal cortex), the dorsomedial striatum (caudate), and the hippocampus. Stress can also result in neuronal hypertrophy in the dorsolateral striatum (putamen) and amygdala. These neurobiological effects mirror reported neural abnormalities in obsessive-compulsive disorder and may contribute to an imbalance between goal-directed and habitual behavior, an imbalance that is implicated in the pathogenesis and expression of obsessive-compulsive disorder symptomatology. The modulation of corticostriatal and limbic circuits by stress and the resultant imbalance between habit and goal-directed learning and behavior offers a framework for investigating how stress may exacerbate or trigger obsessive-compulsive disorder symptomatology.

Low frequency fluctuation of brain spontaneous activity and obsessive-compulsive symptoms in a large school-age sample

BACKGROUND

The present study was designed to explore alterations in brain dynamics at rest that are associated with Obsessive Compulsive Symptoms (OCS) in childhood by measuring low frequency fluctuation of spontaneous brain activity in a large school community sample from a developing country.

METHOD

Resting state functional magnetic resonance imaging data were collected in a sample of 655 children and adolescents (6-15 years old) from the brazilian 'High Risk Cohort Study for Psychiatric Disorders (HRC)'. OCS were assessed using items from the Compulsion and Obsessions section of the Development and Well-Being Assessment (DAWBA). The correlation between the fractional amplitude of low frequency fluctuations (fALFF) and the number of OCS were explored by using a general linear model, considering fALFF as response variable, OCS score as regressor and age, gender and site as nuisance variables.

RESULTS

The number of OCS was positively correlated with the fALFF coefficients at the right sensorimotor cortex (pre-motor, primary motor cortex and post-central gyrus) and negatively correlated with the fALFF coefficients at the insula/superior temporal gyrus of both hemispheres. Our results were specific to OCS and not due to associations with overall psychopathology.

CONCLUSIONS

Our results suggest that brain spontaneous activity at rest in the sensorimotor and insular/superior-temporal cortices may be involved in OCS in children. These findings need independent replication and future studies should determine whether brain spontaneous activity changes within these regions might be predictors of risk for obsessive-compulsive disorder latter in life.

Altered connectivity within and between the default mode, central executive, and salience networks in obsessive-compulsive disorder

BACKGROUND

Default mode network (DMN), central executive network (CEN) and salience network (SN) are the three most important intrinsic networks of the human brain. Recent studies emphasized the importance of the "triple-network model" which illustrated the interactions within and between DMN, CEN and SN in the pathophysiology of psychiatric disorders. However, previous studies of obsessive-compulsive disorder (OCD) just explored the altered connectivity within these networks while neglected the coupling between them. Hence, the present study was designed to fill this research gap.

METHODS

Resting-state functional magnetic resonance imaging (fMRI) data from 35 OCD patients and 32 healthy controls (HCs) were acquired. Independent component analysis (ICA) was used to extract sub-networks of the DMN, CEN, and SN. Functional connectivity (FC) values within and between these networks were measured.

RESULTS

OCD patients had increased FC within several DMN, CEN, and SN subsystems. In addition, OCD patients demonstrated aberrant functional interactions between the SN and anterior DMN (aDMN) as well as between the SN and the dorsal CEN (dCEN), and the interaction between the SN and dCEN significantly correlated with trait anxiety level in the OCD group.

LIMITATION

Lack of the assessments of cognitive functions is the main limitation of the present study.

CONCLUSIONS

Not only impaired coupling within the brain core intrinsic large-scale networks, but also coupling between large-scale neurocognitive networks, which reflect the difficulties in switching between task-negative and task-positive processing modes are involved in the neurobiological mechanism of OCD.

A Neural Marker of Obsessive-Compulsive Disorder from Whole-Brain Functional Connectivity

Obsessive-compulsive disorder (OCD) is a common psychiatric disorder with a lifetime prevalence of 2–3%. Recently, brain activity in the resting state is gathering attention for exploring altered functional connectivity in psychiatric disorders. Although previous resting-state functional magnetic resonance imaging studies investigated the neurobiological abnormalities of patients with OCD, there are concerns that should be addressed. One concern is the validity of the hypothesis employed. Most studies used seed-based analysis of the fronto-striatal circuit, despite the potential for abnormalities in other regions. A hypothesis-free study is a promising approach in such a case, while it requires researchers to handle a dataset with large dimensions. Another concern is the reliability of biomarkers derived from a single dataset, which may be influenced by cohort-specific features. Here, our machine learning algorithm identified an OCD biomarker that achieves high accuracy for an internal dataset (AUC = 0.81; N = 108) and demonstrates generalizability to an external dataset (AUC = 0.70; N = 28). Our biomarker was unaffected by medication status, and the functional networks contributing to the biomarker were distributed widely, including the frontoparietal and default mode networks. Our biomarker has the potential to deepen our understanding of OCD and to be applied clinically.

Meta-analytic investigations of common and distinct grey matter alterations in youths and adults with obsessive-compulsive disorder

Obsessive-compulsive disorder (OCD) is a disabling illness with onset generally in childhood. OCD-youths differ from OCD-adults with regard to gender distribution, comorbidity patterns and treatment options. However, little is known about the neural correlate differences underpin those two populations. The current meta-analysis summarizes voxel based morphometry findings to elucidate whether differences of neural correlates exist between these two populations. Both OCD-youths and OCD-adults demonstrated greater striatal volume and smaller prefrontal grey matter volume (GMV). However, smaller GMV in left visual cortex was observed in OCD-youths only, while smaller GMV in anterior cingulate gyrus and greater GMV in cerebellum were demonstrated only in OCD-adults. Meta-regression showed greater GMV in left putamen was most prominent in samples with higher percentages of medicated OCD-adults. Our findings confirmed the most consistent GMV alterations in OCD were in prefrontal-striatal circuitry. Besides, other regions may involve at different developmental stages including deficits of visual cortex in OCD-youths and abnormalities of limbic-cerebellar circuit in OCD-adults. Medication effect may be more pronounced in the striatum, especially the putamen.

Can Neuroimaging Provide Reliable Biomarkers for Obsessive-Compulsive Disorder? A Narrative Review

In this integrative review, we discuss findings supporting the use neuroimaging biomarkers in the diagnosis and treatment of obsessive-compulsive disorder (OCD). To do so, we have selected the most recent studies that attempted to identify the underlying pathogenic process associated with OCD and whether they provide useful information to predict clinical features, natural history or treatment responses. Studies using functional magnetic resonance (fMRI), voxel-based morphometry (VBM), diffusion tensor imaging (DTI) and proton magnetic resonance spectroscopy (1H MRS) in OCD patients are generally supportive of an expanded version of the earlier cortico-striatal-thalamus-cortical (CSTC) model of OCD. Although it is still unclear whether this information will be incorporated into the daily clinical practice (due to current conceptual approaches to mental illness), statistical techniques, such as pattern recognition methods, appear promising in identifying OCD patients and predicting their outcomes.

Spontaneous neuronal activity in insula predicts symptom severity of unmedicated obsessive compulsive disorder adults

Emerging evidence has suggested that the pathophysiology of obsessive compulsive disorder (OCD) might involve widely distributed large-scale brain systems. The dysfunction within salience network, which is comprised of dorsal anterior cingulated cortex (dACC) and bilateral insular areas, has been proposed to contribute to OCD onset. The mechanism underlying salience network abnormality remains unclear and it is worthwhile to investigate its clinical relevance using functional neuroimaging approaches. In this study, we performed the spontaneous brain activity measurement using resting-state functional magnetic resonance imaging (fMRI) on unmedicated OCD patients (n=23). Specifically, the amplitude of low frequency (0.01-0.08 Hz) fluctuations (ALFF) was calculated for regions in salience network. The voxel-based Pearson's correlative analysis was conducted to explore the relationship beween ALFF measures and symptom severity for OCD patients. The results showed that the spontaneous neuronal activity in insula was significantly correlated to OCD clinical symptoms, especially compulsive behaviors. Our findings consolidated that the salience network played an important role in the pathogenesis of OCD and the intensity of intrinsic brain activity in insula provided a predictive biomarker for OCD symptom severity.

Role of the dorsal anterior cingulate cortex in obsessive-compulsive disorder: converging evidence from cognitive neuroscience and psychiatric neurosurgery

OBJECTIVE Advances in understanding the neurobiological basis of psychiatric disorders will improve the ability to refine neuromodulatory procedures for treatment-refractory patients. One of the core dysfunctions in obsessive-compulsive disorder (OCD) is a deficit in cognitive control, especially involving the dorsal anterior cingulate cortex (dACC). The authors' aim was to derive a neurobiological understanding of the successful treatment of refractory OCD with psychiatric neurosurgical procedures targeting the dACC. METHODS First, the authors systematically conducted a review of the literature on the role of the dACC in OCD by using the search terms "obsessive compulsive disorder" and "anterior cingulate." The neuroscience literature on cognitive control mechanisms in the dACC was then combined with the literature on psychiatric neurosurgical procedures targeting the dACC for the treatment of refractory OCD. RESULTS The authors reviewed 89 studies covering topics that included structural and functional neuroimaging and electrophysiology. The majority of resting-state functional neuroimaging studies demonstrated dACC hyperactivity in patients with OCD relative to that in controls, while task-based studies were more variable. Electrophysiological studies showed altered dACC-related biomarkers of cognitive control, such as error-related negativity in OCD patients. These studies were combined with the cognitive control neurophysiology literature, including the recently elaborated expected value of control theory of dACC function. The authors suggest that a central feature of OCD pathophysiology involves the generation of mis-specified cognitive control signals by the dACC, and they elaborate on this theory and provide suggestions for further study. CONCLUSIONS Although abnormalities in brain structure and function in OCD are distributed across a wide network, the dACC plays a central role. The authors propose a theory of cognitive control dysfunction in OCD that attempts to explain the therapeutic efficacy of dACC neuromodulation. This theoretical framework should help to guide further research into targeted treatments of OCD and other disorders of cognitive control.

Abnormal striatal resting-state functional connectivity in adolescents with obsessive-compulsive disorder

Neuroimaging research has implicated abnormalities in cortico-striatal-thalamic-cortical (CSTC) circuitry in pediatric obsessive-compulsive disorder (OCD). In this study, resting-state functional magnetic resonance imaging (R-fMRI) was used to investigate functional connectivity in the CSTC circuitry in adolescents with OCD. Imaging was obtained with the Human Connectome Project (HCP) scanner using newly developed pulse sequences which allow for higher spatial and temporal resolution. Fifteen adolescents with OCD and 13 age- and gender-matched healthy controls (ages 12-19) underwent R-fMRI on the 3T HCP scanner. Twenty-four minutes of resting-state scans (two consecutive 12-min scans) were acquired. We investigated functional connectivity of the striatum using a seed-based, whole brain approach with anatomically-defined seeds placed in the bilateral caudate, putamen, and nucleus accumbens. Adolescents with OCD compared with controls exhibited significantly lower functional connectivity between the left putamen and a single cluster of right-sided cortical areas including parts of the orbitofrontal cortex, inferior frontal gyrus, insula, and operculum. Preliminary findings suggest that impaired striatal connectivity in adolescents with OCD in part falls within the predicted CSTC network, and also involves impaired connections between a key CSTC network region (i.e., putamen) and key regions in the salience network (i.e., insula/operculum). The relevance of impaired putamen-insula/operculum connectivity in OCD is discussed.

Alterations of resting state networks and structural connectivity in relation to the prefrontal and anterior cingulate cortices in late prematurity

Late preterm birth is increasingly recognized as a risk factor for cognitive and social deficits. The prefrontal cortex is particularly vulnerable to injury in late prematurity because of its protracted development and extensive cortical connections. Our study examined children born late preterm without access to advanced postnatal care to assess structural and functional connectivity related to the prefrontal cortex. Thirty-eight preadolescents [19 born late preterm (34-36 /7 weeks gestational age) and 19 at term] were recruited from a developing community in Brazil. Participants underwent neuropsychological testing. Individuals underwent three-dimensional T1-weighted, diffusion-weighted, and resting state functional MRI. Probabilistic tractography and functional connectivity analyses were carried out using unilateral seeds combining the medial prefrontal cortex and the anterior cingulate cortex. Late preterm children showed increased functional connectivity within regions of the default mode, salience, and central-executive networks from both right and left frontal cortex seeds. Decreased functional connectivity was observed within the right parahippocampal region from left frontal seeding. Probabilistic tractography showed a pattern of decreased streamlines in frontal white matter pathways and the corpus callosum, but also increased streamlines in the left orbitofrontal white matter and the right frontal white matter when seeded from the right. Late preterm children and term control children scored similarly on neuropsychological testing. Prefrontal cortical connectivity is altered in late prematurity, with hyperconnectivity observed in key resting state networks in the absence of neuropsychological deficits. Abnormal structural connectivity indicated by probabilistic tractography suggests subtle changes in white matter development, implying disruption of normal maturation during the late gestational period.

Altered Structural and Functional Connectivity in Late Preterm Preadolescence: An Anatomic Seed-Based Study of Resting State Networks Related to the Posteromedial and Lateral Parietal Cortex

OBJECTIVE

Late preterm birth confers increased risk of developmental delay, academic difficulties and social deficits. The late third trimester may represent a critical period of development of neural networks including the default mode network (DMN), which is essential to normal cognition. Our objective is to identify functional and structural connectivity differences in the posteromedial cortex related to late preterm birth.

METHODS

Thirty-eight preadolescents (ages 9-13; 19 born in the late preterm period (≥32 weeks gestational age) and 19 at term) without access to advanced neonatal care were recruited from a low socioeconomic status community in Brazil. Participants underwent neurocognitive testing, 3-dimensional T1-weighted imaging, diffusion-weighted imaging and resting state functional MRI (RS-fMRI). Seed-based probabilistic diffusion tractography and RS-fMRI analyses were performed using unilateral seeds within the posterior DMN (posterior cingulate cortex, precuneus) and lateral parietal DMN (superior marginal and angular gyri).

RESULTS

Late preterm children demonstrated increased functional connectivity within the posterior default mode networks and increased anti-correlation with the central-executive network when seeded from the posteromedial cortex (PMC). Key differences were demonstrated between PMC components with increased anti-correlation with the salience network seen only with posterior cingulate cortex seeding but not with precuneus seeding. Probabilistic tractography showed increased streamlines within the right inferior longitudinal fasciculus and inferior fronto-occipital fasciculus within late preterm children while decreased intrahemispheric streamlines were also observed. No significant differences in neurocognitive testing were demonstrated between groups.

CONCLUSION

Late preterm preadolescence is associated with altered functional connectivity from the PMC and lateral parietal cortex to known distributed functional cortical networks despite no significant executive neurocognitive differences. Selective increased structural connectivity was observed in the setting of decreased posterior interhemispheric connections. Future work is needed to determine if these findings represent a compensatory adaptation employing alternate neural circuitry or could reflect subtle pathology resulting in emotional processing deficits not seen with neurocognitive testing.

Arbitration between Action Strategies in Obsessive-Compulsive Disorder

Decision making in a complex world, characterized both by predictable regularities and by frequent departures from the norm, requires dynamic switching between rapid habit-like, automatic processes and slower, more flexible evaluative processes. These strategies, formalized as "model-free" and "model-based" reinforcement learning algorithms, respectively, can lead to divergent behavioral outcomes, requiring a mechanism to arbitrate between them in a context-appropriate manner. Recent data suggest that individuals with obsessive-compulsive disorder (OCD) rely excessively on inflexible habit-like decision making during reinforcement-driven learning. We propose that inflexible reliance on habit in OCD may reflect a functional weakness in the mechanism for context-appropriate dynamic arbitration between model-free and model-based decision making. Support for this hypothesis derives from emerging functional imaging findings. A deficit in arbitration in OCD may help reconcile evidence for excessive reliance on habit in rewarded learning tasks with an older literature suggesting inappropriate recruitment of circuitry associated with model-based decision making in unreinforced procedural learning. The hypothesized deficit and corresponding circuitry may be a particularly fruitful target for interventions, including cognitive remediation.