80 research outputs found
Real-time functional magnetic resonance imaging in obsessive-compulsive disorder
The current literature provides substantial evidence of brain alterations associated with obsessive-compulsive disorder (OCD) symptoms (eg, checking, cleaning/decontamination, counting compulsions; harm or sexual, symmetry/exactness obsessions), and emotional problems (eg, defensive/appetitive emotional imbalance, disgust, guilt, shame, and fear learning/extinction) and cognitive impairments associated with this disorder (eg, inhibitory control, working memory, cognitive flexibility). Building on this evidence, new clinical trials can now target specific brain regions/networks. Real-time functional magnetic resonance imaging (rtfMRI) was introduced as a new therapeutic tool for the self-regulation of brain-mind. In this review, we describe initial trials testing the use of rtfMRI to target brain regions associated with specific OCD symptoms (eg, contamination), and other mind-brain processes (eg, cognitive -working memory, inhibitory control, emotional - defensive, appetitive systems, fear reduction through counter-conditioning) found impaired in OCD patients. While this is a novel topic of research, initial evidence shows the promise of using rtfMRI in training the self-regulation of brain regions and mental processes associated with OCD. Additionally, studies with healthy populations have shown that individuals can regulate brain regions associated with cognitive and emotional processes found impaired in OCD. After the initial "proof-of-concept" stage, there is a need to follow up with controlled clinical trials that could test rtfMRI innovative treatments targeting brain regions and networks associated with different OCD symptoms and cognitive-emotional impairments.info:eu-repo/semantics/publishedVersio
Gray Matter Volumes in Obsessive-Compulsive Disorder Before and After Fluoxetine or Cognitive-Behavior Therapy: A Randomized Clinical Trial
Serotonin reuptake inhibitors and cognitive-behavior therapy (CBT) are considered first-line treatments for obsessive-compulsive disorder (OCD). However, little is known about their modulatory effects on regional brain morphology in OCD patients. We sought to document structural brain abnormalities in treatment-naive OCD patients and to determine the effects of pharmacological and cognitive-behavioral treatments on regional brain volumes. Treatment-naive patients with OCD (n = 38) underwent structural magnetic resonance imaging scan before and after a 12-week randomized clinical trial with either fluoxetine or group CBT. Matched-healthy controls (n = 36) were also scanned at baseline. Voxel-based morphometry was used to compare regional gray matter (GM) volumes of regions of interest (ROIs) placed in the orbitofrontal, anterior cingulate and temporolimbic cortices, striatum, and thalamus. Treatment-naive OCD patients presented smaller GM volume in the left putamen, bilateral medial orbitofrontal, and left anterior cingulate cortices than did controls (p<0.05, corrected for multiple comparisons). After treatment with either fluoxetine or CBT (n = 26), GM volume abnormalities in the left putamen were no longer detectable relative to controls. ROI-based within-group comparisons revealed that GM volume in the left putamen significantly increased (p<0.012) in fluoxetine-treated patients (n = 13), whereas no significant GM volume changes were observed in CBT-treated patients (n = 13). This study supports the involvement of orbitofronto/cingulo-striatal loops in the pathophysiology of OCD and suggests that fluoxetine and CBT may have distinct neurobiological mechanisms of action. Neuropsychopharmacology (2012) 37, 734-745; doi: 10.1038/npp.2011.250; published online 26 October 2011Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)MedtronicEli LillyMcNeilCyberonicsNIMHNARSADTSAOCFTufts UniversityMGH Psychiatry AcademyBrainCellsSystems Research and Applications CorporationBoston UniversityCatalan Agency for Health Technology Assessment and ResearchNational Association of Social Workers MassachusettsMassachusetts Medical SocietyNIDAGerman Research Foundation/Federal Ministry for Education and ResearchOxford University PressNIHNIAAHRQJanssen PharmaceuticalsForest Research InstituteShire DevelopmentNorthstarJanssenAstraZenecaLundbeckSolvayUniv São Paulo, Sch Med, Dept Psychiat, São Paulo, BrazilUniv São Paulo, Sch Med, Inst Psychiat, São Paulo, BrazilUniversidade Federal de São Paulo UNIFESP, Dept Psychiat, Interdisciplinary Lab Clin Neurosci LiNC, São Paulo, BrazilHarvard Univ, Massachusetts Gen Hosp, Sch Med, Dept Psychiat, Boston, MA USAUniversidade Federal de São Paulo UNIFESP, Dept Psychiat, Interdisciplinary Lab Clin Neurosci LiNC, São Paulo, BrazilFAPESP: 2005/55628-8FAPESP: 06/61459-7FAPESP: 06/50273-0FAPESP: 2008/10257-0FAPESP: 06/58286-3FAPESP: 2005/04206-6CAPES: 4375/08-4Web of Scienc
Differences in prefrontal cortex activation and deactivation during strategic episodic verbal memory encoding in mild cognitive impairment
In this study we examined differences in fMRI activation and deactivation patterns during episodic verbal memory encoding between individuals with MCI (n = 18) and healthy controls (HCs) (n = 17). Participants were scanned in two different sessions during the application of self-initiated or directed instructions to apply semantic strategies at encoding of word lists. MCI participants showed reduced free recall scores when using self-initiated encoding strategies that were increased to baseline controls\u27 level after directed instructions were provided. During directed strategic encoding, greater recruitment of frontoparietal regions was observed in both MCI and control groups; group differences between sessions were observed in the ventromedial prefrontal cortex and the right superior frontal gyrus. This study provides evidence suggesting that differences of activity in these regions may be related to encoding deficits in MCI, possibly mediating executive functions during task performance
Lateral hypothalamic activity indicates hunger and satiety states in humans
Lateral hypothalamic area (LHA) local field potentials (LFPs) were recorded in a Prader–Willi patient undergoing deep brain stimulation (DBS) for obesity. During hunger, exposure to food-related cues induced an increase in beta/ low-gamma activity. In contrast, recordings during satiety were marked by prominent alpha rhythms. Based on these findings, we have delivered alphafrequency DBS prior to and during food intake. Despite reporting an early sensation of fullness, the patient continued to crave food. This suggests that the pattern of activity in LHA may indicate hunger/satiety states in humans but attest to the complexity of conducting neuromodulation studies in obesity
Brain structural correlates of sensory phenomena in patients with obsessive-compulsive disorder
Background: sensory phenomena (SP) are uncomfortable feelings, including bodily sensations, sense of inner tension, 'just-right' perceptions, feelings of incompleteness, or 'urge-only' phenomena, which have been described to precede, trigger or accompany repetitive behaviours in individuals with obsessive-compulsive disorder (OCD). Sensory phenomena are also observed in individuals with tic disorders, and previous research suggests that sensorimotor cortex abnormalities underpin the presence of SP in such patients. However, to our knowledge, no studies have assessed the neural correlates of SP in patients with OCD. Methods: we assessed the presence of SP using the University of São Paulo Sensory Phenomena Scale in patients with OCD and healthy controls from specialized units in São Paulo, Brazil, and Barcelona. All participants underwent a structural magnetic resonance examination, and brain images were examined using DARTEL voxel-based morphometry. We evaluated grey matter volume differences between patients with and without SP and healthy controls within the sensorimotor and premotor cortices. Results: we included 106 patients with OCD and 87 controls in our study. Patients with SP (67% of the sample) showed grey matter volume increases in the left sensorimotor cortex in comparison to patients without SP and bilateral sensorimotor cortex grey matter volume increases in comparison to controls. No differences were observed between patients without SP and controls. Limitations: most patients were medicated. Participant recruitment and image acquisition were performed in 2 different centres. Conclusion: we have identified a structural correlate of SP in patients with OCD involving grey matter volume increases within the sensorimotor cortex; this finding is in agreement with those of tic disorder studies showing that abnormal activity and volume increases within this region are associated with the urges preceding tic onset
Obsessive-compulsive symptoms, polygenic risk score, and thalamic development in children from the Brazilian High-Risk Cohort for Mental Conditions (BHRCS)
Background: Thalamic volume measures have been linked to obsessive-compulsive disorder (OCD) in children and adolescents. However, it is unclear if alterations in thalamic volumes occur before or after symptom onset and if there is a relation to the presence of sub-clinical obsessive-compulsive symptoms (OCS). Here, we explore the relationship between OCS and the rate of thalamic volume change in a cohort of children and youth at high risk to develop a mental disorder. A secondary aim was to determine if there is a relationship between OCS and the individual’s OCD polygenic risk score (OCD-PRS) and between the rate of thalamic volume change and the OCD-PRS. Methods: The sample included 378 children enrolled in the longitudinal Brazilian High-Risk Cohort for Mental Conditions. Participants were assessed for OCS and the symmetrized percent change (SPC) of thalamic volume across two time-points separated by 3 years, along with the OCD-PRS. Zero-altered negative binomial models were used to analyze the relationship between OCS and thalamic SPC. Multiple linear regressions were used to examine the relationship between thalamic SPC and OCD-PRS. Results: A significant relationship between OCS and the right thalamus SPC (p = 0.042) was found. There was no significant relationship between changes in thalamic volume SPC and OCD-PRS. Conclusions: The findings suggest that changes in the right thalamic volume over the course of 3 years in children may be associated to OCS. Future studies are needed to confirm these results and further characterize the specific nature of OCS symptoms associated with thalamic volumes
Desenhando as novas fronteiras para a compreensão do transtorno obsessivo-compulsivo: uma revisão de sua relação com o medo e a ansiedade
Anxiety is an important component of the psychopathology of the obsessive-compulsive disorder (OCD). So far, most interventions that have proven to be effective for treating OCD are similar to those developed for other anxiety disorders. However, neurobiological studies of OCD came to conclusions that are not always compatible with those previously associated with other anxiety disorders. OBJECTIVES: The aim of this study is to review the degree of overlap between OCD and other anxiety disorders phenomenology and pathophysiology to support the rationale that guides research in this field. RESULTS: Clues about the neurocircuits involved in the manifestation of anxiety disorders have been obtained through the study of animal anxiety models, and structural and functional neuroimaging in humans. These investigations suggest that in OCD, in addition to dysfunction in cortico-striatal pathways, the functioning of an alternative neurocircuitry, which involves amygdalo-cortical interactions and participates in fear conditioning and extinction processes, may be impaired. CONCLUSION: It is likely that anxiety is a relevant dimension of OCD that impacts on other features of this disorder. Therefore, future studies may benefit from the investigation of the expression of fear and anxiety by OCD patients according to their type of obsessions and compulsions, age of OCD onset, comorbidities, and patterns of treatment response
The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium
Current knowledge about functional connectivity in obsessive-compulsive disorder (OCD) is based on small-scale studies, limiting the generalizability of results. Moreover, the majority of studies have focused only on predefined regions or functional networks rather than connectivity throughout the entire brain. Here, we investigated differences in resting-state functional connectivity between OCD patients and healthy controls (HC) using mega-analysis of data from 1024 OCD patients and 1028 HC from 28 independent samples of the ENIGMA-OCD consortium. We assessed group differences in whole-brain functional connectivity at both the regional and network level, and investigated whether functional connectivity could serve as biomarker to identify patient status at the individual level using machine learning analysis. The mega-analyses revealed widespread abnormalities in functional connectivity in OCD, with global hypo-connectivity (Cohen’s d: -0.27 to -0.13) and few hyper-connections, mainly with the thalamus (Cohen’s d: 0.19 to 0.22). Most hypo-connections were located within the sensorimotor network and no fronto-striatal abnormalities were found. Overall, classification performances were poor, with area-under-the-receiver-operating-characteristic curve (AUC) scores ranging between 0.567 and 0.673, with better classification for medicated (AUC = 0.702) than unmedicated (AUC = 0.608) patients versus healthy controls. These findings provide partial support for existing pathophysiological models of OCD and highlight the important role of the sensorimotor network in OCD. However, resting-state connectivity does not so far provide an accurate biomarker for identifying patients at the individual level
Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.
Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions
White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group
White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) “OCD vs. healthy controls” (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) “unmedicated OCD vs. healthy controls” (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) “medicated OCD vs. unmedicated OCD” (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6–79.1 in adults; 35.9–63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research
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