scholarly journals Quantitative macromolecular proton fraction mapping reveals altered cortical myelin profile in schizophrenia spectrum disorders

2021 ◽  
Author(s):  
Yu Veronica Sui ◽  
Hilary Bertisch ◽  
Hong-Hsi Lee ◽  
Pippa Storey ◽  
James S Babb ◽  
...  
Keyword(s):  
Spatial Working Memory ◽  
Magnetization Transfer ◽  
Working Memory Capacity ◽  
Compensatory Mechanism ◽  
Schizophrenia Spectrum Disorders ◽  
Illness Duration ◽  
Schizophrenia Spectrum ◽  
Healthy Control ◽  
Spectrum Disorders

Abstract Myelin abnormalities have been reported in schizophrenia spectrum disorders (SSD) in white matter. However, in vivo examinations of cortical myeloarchitecture in SSD, especially using quantitative measures, are limited. Here we employed macromolecular proton fraction (MPF) obtained from quantitative magnetization transfer imaging to characterize intracortical myelin organization in 30 SSD patients versus 34 healthy control (HC) participants. We constructed cortical myelin profiles by extracting MPF values at various cortical depths and quantified their shape using a nonlinearity index (NLI). To delineate the association of illness duration with myelin changes, SSD patients were further divided into three duration groups. Between-group comparisons revealed reduced NLI in the SSD group with the longest illness duration (>5.5 years) compared to HC predominantly in bilateral prefrontal areas. Within the SSD group, cortical NLI decreased with disease duration and was positively associated with a measure of spatial working memory capacity as well as with cortical thickness. Layer specific analyses suggested that NLI decreases in the long duration SSD group may arise in part from significantly increased MPF values in the midcortical layers. The current study reveals cortical myelin profile changes in SSD with illness progression, which may reflect an abnormal compensatory mechanism of the disorder.

scholarly journals The Role of Dopaminergic Genes in Probabilistic Reinforcement Learning in Schizophrenia Spectrum Disorders

2021 ◽  
Vol 12 (1) ◽  
pp. 7
Author(s):  
Dorota Frydecka ◽  
Błażej Misiak ◽  
Patryk Piotrowski ◽  
Tomasz Bielawski ◽  
Edyta Pawlak ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Genetic Polymorphisms ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum ◽  
Probabilistic Reinforcement ◽  
Healthy Control ◽  
Spectrum Disorders ◽  
The Impact ◽  
Dopaminergic Genes ◽  
Allele Repeat

Schizophrenia spectrum disorders (SZ) are characterized by impairments in probabilistic reinforcement learning (RL), which is associated with dopaminergic circuitry encompassing the prefrontal cortex and basal ganglia. However, there are no studies examining dopaminergic genes with respect to probabilistic RL in SZ. Thus, the aim of our study was to examine the impact of dopaminergic genes on performance assessed by the Probabilistic Selection Task (PST) in patients with SZ in comparison to healthy control (HC) subjects. In our study, we included 138 SZ patients and 188 HC participants. Genetic analysis was performed with respect to the following genetic polymorphisms: rs4680 in COMT, rs907094 in DARP-32, rs2734839, rs936461, rs1800497, and rs6277 in DRD2, rs747302 and rs1800955 in DRD4 and rs28363170 and rs2975226 in DAT1 genes. The probabilistic RL task was completed by 59 SZ patients and 95 HC subjects. SZ patients performed significantly worse in acquiring reinforcement contingencies during the task in comparison to HCs. We found no significant association between genetic polymorphisms and RL among SZ patients; however, among HC participants with respect to the DAT1 rs28363170 polymorphism, individuals with 10-allele repeat genotypes performed better in comparison to 9-allele repeat carriers. The present study indicates the relevance of the DAT1 rs28363170 polymorphism in RL in HC participants.

scholarly journals Anticipatory Pleasure for Future Experiences in Schizophrenia-Spectrum Disorders and Major Depression: A Systematic Review and Meta-Analysis

2019 ◽  
Author(s):  
David John Hallford ◽  
Manoj Kumar Sharma
Keyword(s):  
Major Depression ◽  
Meta Analysis ◽  
Systemic Review ◽  
Schizophrenia Spectrum Disorders ◽  
Duration Of Illness ◽  
Schizophrenia Spectrum ◽  
Healthy Control ◽  
History Of ◽  
Spectrum Disorders ◽  
Academic Search

Objectives: Deficits in anticipating pleasure may be an important dimension of anhedonia and functioning in psychiatric disorders, particularly schizophrenia and depression, however, inconsistent findings have limited the conclusions that can be drawn. We conducted the first systemic review and meta-analysis of the extant literature for research comparing psychiatric groups to healthy control groups on anticipatory pleasure. Methods: Academic Search Complete, Science Direct and CINAHL databases were systematically searched up to June 9th 2018 for relevant peer-reviewed articles, book chapters, and dissertations. Reference lists were also hand searched. A total of 36 studies were included in the review.Results: A moderate-sized deficit was observed in schizophrenia-spectrum disorders (k = 32, 1851 patients and 1449 controls, g = -0.42 [95%CI = -0.53-0.31], p < .001), and a large deficit in major depression (k = 415 patients and 506 controls, g = -0.87 [95%CI = -1.23-0.51], p < .001), with this effect being significantly larger for depression (p < .05). Meta-regression showed that heterogeneity was partially explained in schizophrenia-spectrum by longer duration of illness and lower cognitive functioning predicting larger deficits. In depression, some evidence was found that ruling out a history of psychiatric illness in controls may be related to larger effects. There was evidence for small study bias inflating estimates in schizophrenia-spectrum disorders. Conclusions: Deficits in anticipatory pleasure are manifest in these disorders, and significantly more so in major depression. These findings indicate a possible therapeutic target to link cognitive

scholarly journals Confirmation Bias in the Course of Instructed Reinforcement Learning in Schizophrenia-Spectrum Disorders

2022 ◽  
Vol 12 (1) ◽  
pp. 90
Author(s):  
Dorota Frydecka ◽  
Patryk Piotrowski ◽  
Tomasz Bielawski ◽  
Edyta Pawlak ◽  
Ewa Kłosińska ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
Large Body ◽  
Confirmation Bias ◽  
P Value ◽  
Schizophrenia Spectrum Disorders ◽  
Learning Tasks ◽  
Learning Rates ◽  
Schizophrenia Spectrum ◽  
Healthy Control ◽  
Spectrum Disorders

A large body of research attributes learning deficits in schizophrenia (SZ) to the systems involved in value representation (prefrontal cortex, PFC) and reinforcement learning (basal ganglia, BG) as well as to the compromised connectivity of these regions. In this study, we employed learning tasks hypothesized to probe the function and interaction of the PFC and BG in patients with SZ-spectrum disorders in comparison to healthy control (HC) subjects. In the Instructed Probabilistic Selection task (IPST), participants received false instruction about one of the stimuli used in the course of probabilistic learning which creates confirmation bias, whereby the instructed stimulus is overvalued in comparison to its real experienced value. The IPST was administered to 102 patients with SZ and 120 HC subjects. We have shown that SZ patients and HC subjects were equally influenced by false instruction in reinforcement learning (RL) probabilistic task (IPST) (p-value = 0.441); however, HC subjects had significantly higher learning rates associated with the process of overcoming cognitive bias in comparison to SZ patients (p-value = 0.018). The behavioral results of our study could be hypothesized to provide further evidence for impairments in the SZ-BG circuitry; however, this should be verified by neurofunctional imaging studies.

Screening Adolescents for Schizophrenia-Spectrum Disorders

2000 ◽  
Author(s):  
B. Cornblatt ◽  
M. Obuchowski ◽  
S. Roberts ◽  
S. Pollack ◽  
L. Erienmeyer-Kimling
Keyword(s):  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders

Sleep and cognition in schizophrenia spectrum disorders: A systematic review protocol.

2020 ◽  
Author(s):  
Sean Carruthers ◽  
Gemma Brunetti ◽  
Susan Rossell
Keyword(s):  
Systematic Review ◽  
Mental Illnesses ◽  
Schizophrenia Spectrum Disorders ◽  
Systematic Review Protocol ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Review Protocol ◽  
Spectrum Disorders ◽  
Sleep And Cognition ◽  
The Relationship

Schizophrenia spectrum disorders are chronic and debilitating mental illnesses characterised by both cognitive impairments and sleep deficits. In this systematic review protocol, we outline an approach to examine the available literature investigating the relationship between sleep and cognition in individuals with schizophrenia spectrum disorder.

Sign in / Sign up

Export Citation Format

Share Document