Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Background: Recent research has demonstrated that the dorsal striatum is directly associated with the integration of cognitive, sensory-motor, and motivational/emotional data. Disruptions in the corticostriatal circuit have been implicated in the pathophysiology of psychosis. The dorsal striatum was reported to show lateralized pathology in psychotic disorders. In this study, we aimed to analyze the laterality of the dorsal striatum with texture analysis of T2-weighted magnetic resonance imaging (MRI) images from schizoaffective disorder (SAD) patients.
Methods: Twenty SAD patients, met the inclusion criteria and had available cranial MRI data were assigned as the patient group. Twenty healthy individuals were determined as the control group. Texture analysis values were obtained from striatum region of interests (ROI) generated from T2-weighted MRI images. Data are presented as mean and standard deviation. The suitability of the data for normal distribution was analyzed with the Kolmogorov-Smirnov test. Analysis of variance (ANOVA) test (Post Hoc TUKEY) was employed to compare the group data based on test findings.
Results: There was no significant difference between the groups in terms of gender and age. There were differences in the values of texture analysis parameters of both caudate and putamen nuclei in comparison to controls. We identified differences in the left dorsal striatum nuclei in SAD. The differences in the putamen were more and more pronounced than in the caudate.
Conclusions: Texture analyses suggest that the left dorsal striatum nuclei may be different in SAD patients. Further studies are needed to determine the pathophysiology of SAD and how it may affect disease treatment.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11319760 | PMC |
| http://dx.doi.org/10.62641/aep.v52i4.1629 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Neural Correlates of Reward Processing: Impact of Individual Differences in Preference for Prosocial Interactions.
Brain Behav
September 2025
Centre For Cognitive and Clinical Neuroscience, College of Health, Medicine and Life Sciences, Brunel University of London, London, UK.
Introduction: There is an ongoing debate about the neural mechanisms and subjective preferences involved in the processing of social rewards compared to non-social reward types.
Methods: Using whole-brain functional magnetic resonance imaging (fMRI), we examined brain activation patterns during the anticipation and consumption phases of monetary and social rewards (using the Monetary and Social Incentive Delay Task-MSIDT, featuring human avatars) and their associations with self-reported social reward preferences measured by the Social Reward Questionnaire (SRQ) in 20 healthy right-handed individuals.
Results: In the anticipation phase, all reward types activated the dorsal striatum, middle cingulo-insular (salience) network, inferior frontal gyrus (IFG), and supplementary motor areas.
Refinement of efficient encodings of movement in the dorsolateral striatum throughout learning.
Cell Rep
September 2025
Department of Neurosurgery, Stanford University, Stanford, CA 94305, USA; Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD 20815, USA; Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA 94305, USA; The Phil & Penny Knight In
The dorsal striatum plays a critical role in action selection, movement, and sensorimotor learning. While action-specific striatal ensembles have been described, the mechanisms underlying their formation and evolution during motor learning remain poorly understood. Here, we employed longitudinal two-photon Ca imaging of dorsal striatal neurons in head-fixed mice as they learned to self-initiate locomotion.
View Article and Find Full Text PDFPsychotic-like experiences in adolescents enriched for high-risk for developing severe mental illness: change over two-years and associations with neural reward processing and affective symptoms.
Eur Arch Psychiatry Clin Neurosci
September 2025
Department of Psychiatry, University of Pittsburgh, 121 Meyran Avenue, Pittsburgh, PA, 15213, USA.
Psychotic-like experiences (PLEs) -subclinical experiences or symptoms that resemble psychosis, such as hallucinations and delusional thoughts-often emerge during adolescence and are predictive of serious psychopathology. Understanding PLEs during adolescence is crucial due to co-occurring developmental changes in neural reward systems that heighten the risk for psychotic-related and affective psychopathology, especially in those with a family history of severe mental illness (SMI). We examined associations among PLEs, clinical symptoms, and neural reward function during this critical developmental period.
View Article and Find Full Text PDFClinical apathy might result from either a diminished willingness to exert effort for known rewards or from reduced motivation to explore potentially beneficial future opportunities. To identify the underlying cognitive and neural bases of apathy, we used task-based fMRI to examine motivated choice computations in patients with chronic traumatic brain injury (TBI)-a condition frequently associated with apathy-and compared their behavior and neural activity to that of healthy controls (CTRLs). Participants performed two choice tasks involving distinct types of motivational tradeoffs: i) An effort-value tradeoff task (the 'Apples Task') requiring them to decide how much physical effort they were willing to exert for varying reward magnitudes, and ii) An explore-exploit tradeoff task (the 'Novelty-Bandit Task') requiring them to choose between exploiting options with a known history of reward or exploring novel options with uncertain but potentially higher future value.
View Article and Find Full Text PDFStructural brain abnormalities in psychosis are well-replicated but heterogenous posing a barrier to uncovering the pathophysiology, etiology, and treatment of psychosis. To parse neurostructural heterogeneity and assess for the presence of anatomically-derived subtypes, we applied a data-driven method, similarity network fusion (SNF), to structural neuroimaging data in a broad cohort of individuals with psychosis (schizophrenia spectrum disorders (SSD) n=280; bipolar disorder with psychotic features (BD) n=101). SNF identified two transdiagnostic subtypes in psychosis (subtype 1: n=158 SSD, n=75 BD; subtype 2: n=122 SSD, n=26 BD) that exhibited divergent patterns of abnormal cortical surface area and subcortical volumes.
View Article and Find Full Text PDF