Excitatory transmission from the amygdala to nucleus accumbens facilitates reward seeking

Interactions between the basolateral amygdala (BLA) and nucleus accumbens (NAc) are involved in a number of reward-processing and addictive behaviours, but our understanding of the precise role of each of these brain areas has been limited by the inability to manipulate pathways selectively during behaviour. Stuber et al. use optogenetic technologies, in which light selectively activates or inhibits genetically-defined neuronal subpopulations, to reveal an unexpected role for the BLA a brain region usually associated with aversive behaviours. The BLA is shown to be important for processing both positive and negative effects, but glutamatergic pathways between the BLA and NAc are specifically associated with reward-seeking behaviours

Negative valence in obsessive-compulsive disorder: a worldwide mega-analysis of task-based functional neuroimaging data of the ENIGMA-OCD consortium

Objective: Obsessive-compulsive disorder (OCD) is associated with altered brain function related to processing of negative emotions. To investigate neural correlates of negative valence in OCD, we pooled functional magnetic resonance imaging data of 633 individuals with OCD and 453 healthy control participants from 16 studies using different negatively valenced tasks across the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium's OCD Working Group. Methods: Participant data were processed uniformly using HALFpipe, to extract voxelwise participant-level statistical images of one common first-level contrast: negative versus neutral stimuli. In preregistered analyses, parameter estimates were entered into Bayesian multilevel models to examine whole-brain and regional effects of OCD and its clinically relevant features-symptom severity, age of onset, and medication status. Results: We provided a proof of concept that participant-level data can be combined across several task paradigms and observed one common task activation pattern across individuals with OCD and control participants that encompasses frontolimbic and visual areas implicated in negative valence. Compared with control participants, individuals with OCD showed very strong evidence of weaker activation of the bilateral occipital cortex (P+ < 0.001) and adjacent visual processing regions during negative valence processing that was related to greater OCD severity, late onset of the disorder, and an unmedicated status. Individuals with OCD also showed stronger activation in the orbitofrontal, subgenual anterior cingulate, and ventromedial prefrontal cortex (all P+ < 0.1) that was related to greater OCD severity and late onset. Conclusions: In the first mega-analysis of this kind, we replicated previous findings of stronger ventral prefrontal activation in OCD during negative valence processing and highlight the lateral occipital cortex as an important region implicated in altered negative valence processing

Correction: The functional connectome in obsessive-compulsive disorder: resting-state mega-analysis and machine learning classification for the ENIGMA-OCD consortium

Correction to: Molecular Psychiatry, published online 2 May 2023 In this article Honami Arai, Irene Bollettini, Rosa Calvo Escalona, Ana Coelho, Federica Colombo, Leila Darwich, Martine Fontaine, Toshikazu Ikuta, Jonathan C. Ipser, Asier Juaneda-Seguí, Hitomi Kitagawa, Gerd Kvale, Mafalda Machado-Sousa, Astrid Morer, Takashi Nakamae, Jin Narumoto, Joseph O’Neill, Sho Okawa, Eva Real, Veit Roessner, Joao R. Sato, Cinto Segalàs, Roseli G. Shavitt, Dick J. Veltman, Kei Yamada were missing from the author list indexed under the ENIGMA-OCD Working Group. Additionally, there was an error regarding Tokiko Yoshida’s name, where the first name and last name were written in the wrong order. The original article has been corrected

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.publishedVersio

The effect of stress on the balance between goal-directed and habit networks in obsessive-compulsive disorder

AbstractThe classical cognitive-behavioral theory of obsessive-compulsive disorder (OCD) holds that compulsions are performed to reduce distress that is evoked by obsessions, whereas a recent neuroscience-inspired theory suggests that compulsivity results from a disbalance between goal-directed and habit-related neural networks. To bridge these theories, we investigated whether the balance between goal-directed and habit networks in patients with OCD was affected in the late aftermath of stress. Twenty-three OCD patients and twenty-three healthy controls participated in a controlled stress induction paradigm using the socially evaluated cold-pressor test in a crossover design. Stress responses were evaluated through cortisol levels, blood pressure, and anxiety ratings. Functional connectivity of the caudate nucleus and posterior putamen was assessed using seed region analysis of resting-state functional magnetic resonance imaging data, which are hubs of the goal-directed and habit network, respectively. Stress induction increased blood pressure and psychological stress measures across groups and resulted in blunted cortisol responses in patients. Furthermore, patients showed a blunted reduction in connectivity between the caudate nucleus and precuneus in the aftermath of stress, which was positively correlated with compulsivity but not obsession severity. The posterior putamen showed no significant group differences in stress-induced connectivity. These results suggest that compulsivity in OCD in the aftermath of stress is associated with altered connectivity between the goal-directed and default mode networks.</jats:p

The effect of distress on the balance between goal-directed and habit networks in obsessive-compulsive disorder

AbstractThe classical cognitive-behavioral theory of obsessive-compulsive disorder (OCD) holds that compulsions are performed to reduce distress that is evoked by obsessions, whereas a recent neuroscience-inspired theory suggests that compulsivity results from a disbalance between goal-directed and habit-related neural networks. To bridge these theories, we investigated whether the balance between goal-directed and habit networks in patients with OCD was affected during psychological distress. Twenty-three OCD patients and twenty-three healthy controls participated in a controlled stress induction paradigm using the socially evaluated cold-pressor test in a crossover design. Stress responses were evaluated through cortisol levels, blood pressure, and anxiety ratings. Functional connectivity of the caudate nucleus and posterior putamen was assessed using seed region analysis of resting-state functional magnetic resonance imaging data, which are hubs of the goal-directed and habit network, respectively. Stress induction increased blood pressure and psychological stress measures across groups and resulted in blunted cortisol responses in patients. Furthermore, patients showed a blunted reduction in connectivity between the caudate nucleus and precuneus during psychological distress, which was positively correlated with compulsivity but not obsession severity. The posterior putamen showed no significant group differences in distress-induced connectivity. These results suggest that compulsivity in OCD is associated with altered connectivity between the goal-directed and default mode networks during psychological distress.</jats:p

The effect of distress on the balance between goal-directed and habit networks in obsessive-compulsive disorder

The classical cognitive-behavioral theory of obsessive-compulsive disorder (OCD) holds that compulsions are performed to reduce distress that is evoked by obsessions, whereas a recent neuroscience-inspired theory suggests that compulsivity results from a disbalance between goal-directed and habit-related neural networks. To bridge these theories, we investigated whether the balance between goal-directed and habit networks in patients with OCD was affected during psychological distress. Twenty-three OCD patients and twenty-three healthy controls participated in a controlled stress induction paradigm using the socially evaluated cold-pressor test in a crossover design. Stress responses were evaluated through cortisol levels, blood pressure, and anxiety ratings. Functional connectivity of the caudate nucleus and posterior putamen was assessed using seed region analysis of resting-state functional magnetic resonance imaging data, which are hubs of the goal-directed and habit network, respectively. Stress induction increased blood pressure and psychological stress measures across groups and resulted in blunted cortisol responses in patients. Furthermore, patients showed a blunted reduction in connectivity between the caudate nucleus and precuneus during psychological distress, which was positively correlated with compulsivity but not obsession severity. The posterior putamen showed no significant group differences in distress-induced connectivity. These results suggest that compulsivity in OCD is associated with altered connectivity between the goal-directed and default mode networks during psychological distress

The effect of amylose:amylopectin ratio in dietary starch on growth performance and gut morphology in broiler chickens

BACKGROUND: Hodgkin lymphoma (HL) survivors have an increased colorectal cancer (CRC) risk. Diagnostic accuracy of quantitative fecal immunochemical testing (FIT, OC Sensor) and/or a multi-target stool DNA test (mt-sDNA, Cologuard®) for advanced neoplasia (AN) was evaluated. METHODS: 101 HL survivors underwent a surveillance colonoscopy and were asked to perform two stool tests (FIT and mt-sDNA). Advanced adenoma (AA), advanced serrated lesion (ASL), and AN (AA, ASL, CRC) were evaluated. Sensitivity, specificity, and area under the curve (AUC) for AN were calculated for different FIT cut-offs and mt-sDNA with colonoscopy as reference. RESULTS: FIT and mt-sDNA were analyzed in 73 (72%) and 82 (81%) participants, respectively. AN was detected in 19 (26%) and 22 (27%), respectively. AN sensitivities for FIT cut-off of 10 ug Hb/g feces (FIT10) and mt-sDNA were 37% (95% confidence interval (CI): 16-62) and 68% (95% CI: 45-86), with corresponding specificities of 91% (95% CI: 80-97) and 70% (95% CI: 57-86), respectively. AUC for FIT was 0.68 (95% CI: 0.54-0.82) and for mt-sDNA 0.76 (95% CI: 0.63-0.89). CONCLUSIONS: In HL survivors, mt-sDNA showed highest sensitivity but with relatively low specificity for AN. Cost-effectiveness analyses is necessary to determine the optimal surveillance strategy

Diagnostic Accuracy of Stool Tests for Colorectal Cancer Surveillance in Hodgkin Lymphoma Survivors

Background: Hodgkin lymphoma (HL) survivors have an increased colorectal cancer (CRC) risk. Diagnostic accuracy of quantitative fecal immunochemical testing (FIT, OC Sensor) and/or a multi-target stool DNA test (mt-sDNA, Cologuard®) for advanced neoplasia (AN) was evaluated. Methods: 101 HL survivors underwent a surveillance colonoscopy and were asked to perform two stool tests (FIT and mt-sDNA). Advanced adenoma (AA), advanced serrated lesion (ASL), and AN (AA, ASL, CRC) were evaluated. Sensitivity, specificity, and area under the curve (AUC) for AN were calculated for different FIT cut-offs and mt-sDNA with colonoscopy as reference. Results: FIT and mt-sDNA were analyzed in 73 (72%) and 82 (81%) participants, respectively. AN was detected in 19 (26%) and 22 (27%), respectively. AN sensitivities for FIT cut-off of 10 ug Hb/g feces (FIT10) and mt-sDNA were 37% (95% confidence interval (CI): 16–62) and 68% (95% CI: 45–86), with corresponding specificities of 91% (95% CI: 80–97) and 70% (95% CI: 57–86), respectively. AUC for FIT was 0.68 (95% CI: 0.54–0.82) and for mt-sDNA 0.76 (95% CI: 0.63–0.89). Conclusions: In HL survivors, mt-sDNA showed highest sensitivity but with relatively low specificity for AN. Cost-effectiveness analyses is necessary to determine the optimal surveillance strategy.</jats:p