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Biology subjects

Lencer, R.

Publications and source records attributed to Lencer, R..

5 recordsLinked to original sources

Prior Information Shapes Perceptual Evidence Accumulation Dynamics Differentially in Psychosis

Humans rely on prior information to navigate sensory uncertainty: Such priors could shape the decision process before sensory evidence is gathered (origin model), or could amplify sensory evidence dynamically (gain model). Dysfunctionalities in the utilisation of priors may underlie hallucinatory percepts and delusional ideation in psychosis, yet their impact on decision-making across sensory modalities has remained unclear. Using a perceptual target-detection task across auditory and visual domains in laboratory and online samples, we applied hierarchical drift diffusion modelling to examine how prior probabilities shape evidence accumulation in clinical and non-clinical populations. We show that in healthy individuals, prior information enhances sensory gain and decision flexibility, as represented by drift criterion and rate, consistent with the gain model. In contrast, individuals with psychosis exhibit diminished sensory gain, relying instead on pre-evidence biases, consistent with the origin model. Notably, greater positive symptom severity predicted a reduction in traditional criterion decision bias. These results suggest that sensory gain deficits may serve as a computational marker for psychosis progression, linking dysfunctional prior use to perceptual aberrancies. By demonstrating how prior information modulates evidence accumulation across sensory modalities, our study advances the understanding of psychotic perception and decision-making, offering insights for computational psychiatry and fine-tuned clinical diagnostics.

neuroscience↗

Alterations of Task-based fMRI Topology Underlying Cognitive Flexibility and Stability in Schizophrenia

Recently, it has been suggested that brain dysconnectivity in patients with schizophrenia contributes to the wide-ranging cognitive deficits that characterize the disorder. Graph theoretical analysis offers a unique method for studying how architectural alterations in large- scale brain networks may contribute to cognitive impairments in these patients. Implementing this technique, we analyzed the functional brain activity during a predictive switch-drift task from 21 patients with schizophrenia and 22 matched healthy controls. We specifically calculated task-based global graph measures for the functional networks that were activated during expected events, events requiring a flexible updating of predictions, and events that required the stabilization of predictions. By implementing Bayesian multivariate generalized linear models, we found functional network alterations during all event types, which indicated less centralized, less integrated, and simultaneously less segregated network topology in patients with schizophrenia compared to controls. In addition, the rate of correctly detected switches, requiring flexible updating of internal models, predicted global graph measures differently for patients compared to controls. In particular, lower cognitive flexibility in patients was associated with reduced integration of functional networks. Overall, the results indicate an adaptation of network topologies, resulting in less optimal network organization in patients with schizophrenia compared to healthy controls.

neuroscience↗

Personalized tDCS targeting visual motion area V5 modulates smooth pursuit initiation

Transcranial direct current stimulation (tDCS) for the modulation of ongoing eye movements provides an ideal model for investigating sensorimotor integration. Within neural networks subserving smooth pursuit eye movements, visual motion area V5 is a core hub to integrate visual motion information with oculomotor control. Here, we applied personalized tDCS explicitly targeting individual V5 in healthy human participants using algorithmic optimization informed by functional magnetic resonance imaging and combined electro- and magnetencephalography. We hypothesized subtle modulation of sensorimotor integration during pursuit and assessed the gain by personalized tDCS targeting V5, compared to personalized tDCS targeting the frontal eye field, as well as conventional normative tDCS over V5. Indeed, pursuit initiation was specifically delayed during personalized cathodal tDCS targeting right V5 indicating the involvement of distinct functional subregions of V5 in the initial sensorimotor integration of visual motion information with pursuit eye movements, but not the maintenance of ongoing pursuit. The results were well-controlled by anodal and sham tDCS, different pursuit tasks, finite-element simulations of individual electric fields, and by two additional control experiments, one that applied personalized tDCS targeting frontal eye field and another that applied normative tDCS over V5. Importantly, in contrast to personalized tDCS targeting FEF and normative tDCS over V5, personalized tDCS targeting V5 effectively modulated pursuit by adapting electric fields to individual anatomical and functional V5 properties. Our results provide evidence for the specific involvement of area V5 in sensorimotor integration during pursuit initiation and the ability of (targeted) tDCS to specifically introduce subtle modulation of the brain network underlying smooth pursuit eye movements. Further, our results indicate the potential of personalized tDCS to alter behavior as the main aspect of interest in human neuromodulation.

neuroscience↗

Connectome architecture shapes large-scale cortical reorganization in schizophrenia: a worldwide ENIGMA study

While schizophrenia is considered a prototypical network disorder characterized by widespread brain-morphological alterations, it still remains unclear whether distributed structural alterations robustly reflect underlying network layout. Here, we tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2,439 adults with schizophrenia and 2,867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n=207), we evaluated structural alterations of schizophrenia against two network susceptibility models: i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; ii) epicenter mapping, which identify regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Schizophrenia-related structural alterations co-localized with interconnected functional and structural hubs and harbored temporo-paralimbic and frontal epicenters. Findings were robust across sites and related to individual symptom profiles. We observed localized unique epicenters for first-episode psychosis and early stages, and transmodal epicenters that were shared across first-episode to chronic stages. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, yielding insights in pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work contributes to recognizing potentially common pathways to better understand macroscale structural alterations, and inter-individual variability in schizophrenia.

neuroscience↗

Common variants of NRXN1, LRP1B and RORA are associated with increased ventricular volumes in psychosis - GWAS findings from the B-SNIP deep phenotyping study

Schizophrenia, Schizoaffective, and Bipolar Disorders share common illness traits, intermediate phenotypes and a partially overlapping polygenic basis. We performed GWAS on deep phenotyping data, including structural MRI and DTI, clinical, and behavioral scales from 1,115 cases and controls. Significant associations were observed with two cerebrospinal fluid volumes: the temporal horn of left lateral ventricle was associated with NRXN1, and the volume of the cavum septum pellucidum was associated with LRP1B and RORA. Both volumes were associated with illness. Suggestive associations were observed with local gyrification indices, fractional anisotropy and age at onset. The deep phenotyping approach allowed unexpected genetic sharing to be found between phenotypes, including temporal horn of left lateral ventricle and age at onset.

genetics↗