Biology subjects

Kathmann, N.

Publications and source records attributed to Kathmann, N..

5 recordsLinked to original sources

bioRxiv2025

Inhibitory control and error processing in Obsessive-Compulsive Disorder: A mega-analysis of task-based fMRI data by the ENIGMA-OCD consortium

ObjectiveObsessive-compulsive disorder (OCD) is a chronic condition in which impaired inhibitory control and excessive error monitoring may contribute to the maintenance of obsessions and compulsions. This mega-analysis investigates neural activation during response inhibition and error processing using adult and pediatric data from the ENIGMA-OCD consortium and the ABCD study. MethodsIndividual participant data was uniformly processed using HALFpipe to extract statistical maps for response inhibition and error processing contrasts. Bayesian multilevel models were used to assess regional and whole-brain effects of OCD, with additional analyses examining the association between the OCD clinical profile and task-related activation. ResultsAcross inhibitory control tasks, both individuals with OCD and control participants showed robust activation in regions implicated in response inhibition and error processing. During response inhibition, compared to controls, adults with OCD showed stronger somatomotor cortex activation, while children with OCD showed stronger occipital cortex activation. Children with likely OCD from the ABCD cohort showed reduced activity in the frontoparietal network in the anterior insula/frontal operculum region. During error processing, relative to controls, adults with OCD showed weaker activation in fronto-striatal regions, while children with OCD showed stronger activation in frontoparietal and attention networks. Greater OCD symptom severity was associated with weaker task-related activation in adults and stronger activation in children during response inhibition. ConclusionCase-control differences in brain activation during inhibitory control varied by age group and task contrast. Symptom severity emerged as the main clinical correlate of activation during inhibition, suggesting that inhibitory control deficits in OCD may be both state-dependent and developmentally specific.

neuroscience↗

bioRxiv2025

Executive control in Obsessive-Compulsive Disorder: A worldwide mega-analysis of task-based functional neuroimaging data of the ENIGMA-OCD consortium

ObjectiveObsessive-compulsive disorder (OCD) is associated with impaired executive function and altered activity in associated neural circuits, contributing to reduced goal-directed behavior. To investigate neural activation during executive control, we conducted a mega-analysis in the ENIGMA-OCD consortium pooling individual participant data from 475 individuals with OCD and 345 healthy controls across 15 fMRI tasks collected worldwide. MethodsIndividual participant data was uniformly processed using HALFpipe to construct voxelwise statistical images of executive control and task load contrasts. Parameter estimates extracted from regions of interest were entered into multilevel Bayesian models to examine regional and whole-brain effects of diagnosis, and, within OCD, the influence of medication status, symptom severity, and age of onset on task activation. ResultsWe observed a robust task activation pattern across individuals with OCD and control participants in executive control regions across tasks. Relative to controls, individuals with OCD showed moderate to very strong evidence of weaker activation of the dorsolateral prefrontal cortex, precuneus, frontal eye fields, and inferior parietal lobule during executive control (all positive posterior probabilities [P+]<0.1). Individuals with OCD also showed stronger activation in regions of the default mode network during executive function relative to controls. We found little evidence for differential activation during executive control in task- positive regions related to disease onset, severity and medication status. ConclusionIn the first mega-analysis of fMRI studies of executive function in OCD, we found strong evidence of weaker frontoparietal activation during executive control tasks. Our findings also suggest a failure of default mode network regions to appropriately disengage during task performance in OCD.

neuroscience↗

bioRxiv2021

Impaired differential learning of fear versus safety signs in obsessive-compulsive disorder

Pavlovian learning mechanisms are of great importance both for models of psychiatric disorders and treatment approaches, but understudied in obsessive-compulsive disorder (OCD). Using an established Pavlovian fear conditioning and reversal procedure, we studied skin conductance responses (SCRs) in 41 patients with OCD and in 32 matched healthy control participants. Within both groups, fear acquisition and reversal effects were evident. When comparing groups, patients showed impaired differential learning of threatening and safe stimuli, consistent with previous research. In contrast to prior findings, differential learning impairments were restricted to fear acquisition, and not observed in the reversal stage of the experiment. As previous and present fear reversal experiments in OCD differed in the use of color coding to facilitate stimulus discrimination, the studies converge to suggest that differential learning of threatening versus safe stimuli is impaired in OCD, but manifests itself differently depending on the difficulty of the association to be learned. When supported by the addition of color, patients with OCD previously appeared to acquire an association early but failed to reverse it according to changed contingencies. In absence of such color coding of stimuli, our data suggest that patients with OCD already show differential learning impairments during fear acquisition, which may relate to findings of altered coping with uncertainty previously observed in OCD. Impaired differential learning of threatening versus safe stimuli should be studied further in OCD, in order to determine whether impairments in differential learning predict CBT treatment outcomes in patients, and whether they are etiologically relevant for OCD.

neuroscience↗

bioRxiv2019

Cue-induced effects on decision-making distinguish subjects with gambling disorder from healthy controls

While an increased impact of cues on decision-making has been associated with substance dependence, it is yet unclear whether this is also a phenotype of non-substance related addictive disorders, such as gambling disorder. To better understand the basic mechanisms of impaired decision-making in addiction, we investigated whether cue-induced changes in decision-making could distinguish gambling disorder (GD) from healthy control (HC) subjects. We expected that cue-induced changes in gamble acceptance and specifically in loss aversion would distinguish GD from HC subjects. 30 GD subjects and 30 matched HC subjects completed a mixed gambles task where gambling and other emotional cues were shown in the background. We used machine learning and classification to carve out the importance of cue-dependency of decision-making and of loss aversion for distinguishing GD from HC subjects. Cross-validated classification yielded an area under the receiver operating curve (AUC-ROC) of 68.9% (p=0.002). Applying the classifier to an independent sample yielded an AUC-ROC of 65.0% (p=0.047). As expected, the classifier used cue-induced changes in gamble acceptance to distinguish GD from HC. Especially increased gambling during the presentation of gambling cues was characteristic of GD subjects. However, unexpectedly, cue-induced changes in loss aversion were irrelevant for distinguishing GD from HC subjects. To our knowledge, this is the first study to investigate the classificatory power of addiction-relevant behavioral task parameters when distinguishing GD from HC subjects. The results indicate that cue-induced changes in decision-making are a characteristic feature of addictive disorders, independent of a substance of abuse.

neuroscience↗

bioRxiv2018

Neural correlates of cue-induced changes in decision-making distinguish subjects with gambling disorder from healthy controls

Background: Just as substance use disorders (SUDs), gambling disorder (GD) is characterized by an increase in cue-dependent decision-making (similar to Pavlovian-to-instrumental transfer, PIT). PIT, as studied in SUDs and healthy subjects, is associated with altered communication between Nucleus Accumbens (NAcc), amygdala, and orbitofrontal cortex (OFC). These neural differences are, however, poorly understood. For example, it is unclear whether they are due to the physiological effects of substance abuse, or rather related to learning processes and/or other etiological factors like innate traits associated with addiction. We have thus investigated whether network activation patterns during a PIT task are also altered in GD, an addictive disorder not involving substance abuse. We have specifically studied which neural PIT patterns were best at distinguishing GD from HC subjects, all to improve our understanding of the neural signatures of GD and of addiction-related PIT in general. Methods: 30 GD and 30 HC subjects completed an affective decision-making task in a functional magnetic resonance imaging (fMRI) scanner. Gambling associated and other emotional cues were shown in the background during the task, allowing us to record multivariate neural PIT signatures focusing on a network of NAcc, amygdala and OFC. We built and tested a classifier based on these multivariate neural PIT signatures using cross-validated elastic net regression. Results and Discussion: As expected, GD subjects showed stronger PIT than HC subjects because they showed stronger increase in gamble acceptance when gambling cues were presented in the background. Classification based on neural PIT signatures yielded a significant AUC-ROC (0.70, p = 0.013). When inspecting the features of the classifier, we observed that GD showed stronger PIT-related functional connectivity between NAcc and amygdala elicited by gambling background cues, as well as between amygdala and OFC elicited by negative and positive cues. Conclusion: We propose that HC and GD subjects are distinguishable by PIT-related neural signatures including amygdala-NAcc-OFC functional connectivity. Our findings suggest that neural PIT alterations in addictive disorders might not depend on the physiological effect of a substance of abuse, but on related learning processes or even innate neural traits, also found in behavioral addictions.

neuroscience↗