Network analysis of cognitive deficit in patients with schizophrenia spectrum disorders

The network structure of schizotypy in a population-based sample

10.31234/osf.io/2sgrx ◽

2018 ◽

Author(s):

David Dodell-Feder ◽

Abhishek Saxena ◽

Lauren Rutter ◽

Laura Germine

Keyword(s):

Network Analysis ◽

Network Structure ◽

Population Based ◽

Network Approach ◽

Schizophrenia Spectrum Disorders ◽

Personality Organization ◽

Schizophrenia Spectrum ◽

Spectrum Disorders ◽

Network Approaches

Outcomes for people with schizophrenia-spectrum disorders (SSDs) are generally poor making it important to understand risk states and illness transition. The network approach, which conceptualizes psychopathology as a network of causally interacting symptoms, may hold promise in this regard. Here, we present a network analysis of schizotypy—the personality organization involving schizophrenia-like phenomena that is thought to index one’s vulnerability for an SSD—using an international, population-based sample. In line with other research, we find that the schizotypy network is densely connected, characterized by three communities of items with interpersonal and disorganized features exhibiting the greatest centrality and predictability. Further, we find network differences between certain groups differing in levels of SSD risk. Together, these findings demonstrate the utility of using network approaches to understand SSD risk states as well as the replicability of network findings on schizotypy and related SSD risk concepts.

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Relationship between DNA Methylation within the YJEFN3 Gene and Cognitive Deficit in Schizophrenia Spectrum Disorders

Russian Journal of Genetics ◽

10.1134/s1022795421080019 ◽

2021 ◽

Vol 57 (9) ◽

pp. 1092-1099

Author(s):

M. V. Alfimova ◽

N. V. Kondratyev ◽

A. K. Golov ◽

V. G. Kaleda ◽

L. I. Abramova ◽

...

Keyword(s):

Dna Methylation ◽

Cognitive Deficit ◽

Schizophrenia Spectrum Disorders ◽

Schizophrenia Spectrum ◽

Spectrum Disorders

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Anomalies of Imagination, Self-Disorders, and Schizophrenia Spectrum Psychopathology: A Network Analysis

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.808009 ◽

2022 ◽

Vol 12 ◽

Author(s):

Andreas Rosén Rasmussen ◽

Andrea Raballo ◽

Antonio Preti ◽

Ditte Sæbye ◽

Josef Parnas

Keyword(s):

Mental Illness ◽

Network Analysis ◽

Healthy Controls ◽

Schizophrenia Spectrum Disorders ◽

Schizotypal Personality ◽

Canonical State ◽

Schizophrenia Spectrum ◽

Syndrome Scale ◽

Spectrum Disorders ◽

Negative Syndrome

BackgroundAnomalies of imagination encompass disturbances of the basic experiential structure of fantasies and imagery that can be explored in a semi-structured way with the Examination of Anomalous Fantasy and Imagination (EAFI). We aimed (1) to examine the distribution of anomalies of imagination among different diagnostic groups and a group of healthy controls, and (2) to examine their relation with disorders of basic self, perceptual disturbances and canonical state psychopathology of the schizophrenia-spectrum (positive, negative and general symptoms).MethodsThe 81 participants included patients with schizophrenia or other non-affective psychosis (N = 32), schizotypal personality disorder (N = 15) or other mental illness (N = 16) and healthy controls (N = 18). The assessment encompassed EAFI, Examination of Anomalous Self-Experience (EASE), parts of Bonn Scale for the Assessment of Basic Symptoms (BSABS) and Positive and Negative Syndrome Scale (PANSS). For network analysis, the associations of EAFI with the other psychopathological variables were tested by Pearson's correlation coefficient and graphically represented using multidimensional clustering. Comparisons between correlations in the network were tested with Steiger's test.ResultsAnomalies of imagination aggregated significantly in schizophrenia-spectrum disorders compared to other mental illness and healthy controls with no difference between schizophrenia and schizotypal disorder. In the network analysis, anomalies of imagination were closely inter-connected with self-disorders. Although, the anomalies of imagination correlated moderately with perceptual disturbance and positive, negative and general state symptomatology, these dimensions aggregated separately and relatively distant in the network.ConclusionsThe results support that anomalies of imagination are highly characteristic of schizophrenia-spectrum disorders and closely related to self-disorders.

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Eye Movements and Cognitive Functioning in Patients With Schizophrenia Spectrum Disorders: Network Analysis

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.736228 ◽

2021 ◽

Vol 12 ◽

Author(s):

Alexander Shmukler ◽

Alexander V. Latanov ◽

Maria Karyakina ◽

Victor N. Anisimov ◽

Marina A. Churikova ◽

...

Keyword(s):

Eye Movements ◽

Network Analysis ◽

Cognitive Functioning ◽

Rating Scale ◽

Central Element ◽

Depression Scale ◽

Schizophrenia Spectrum Disorders ◽

Young Mania ◽

Schizophrenia Spectrum ◽

Spectrum Disorders

Background: Eye movement parameters are often used during cognitive functioning assessments of patients with psychotic spectrum disorders. It is interesting to compare these oculomotor parameters with cognitive functions, as assessed using psychometric cognitive tests. A network analysis is preferable for understanding complex systems; therefore, the aim of this study was to determine the multidimensional relationships that exist between oculomotor reactions and neurocognition in patients with schizophrenia spectrum disorders.Materials and Methods: A total of 134 subjects (93 inpatients with schizophrenia spectrum disorders (ICD-10) and 41 healthy volunteers) participated in this study. Psychiatric symptom severity was assessed using the Positive and Negative Syndrome Scale, the Calgary Depression Scale for Schizophrenia, and the Young Mania Rating Scale. Extrapyramidal symptoms were assessed using the Simpson-Angus Scale, and akathisia was assessed using the Barnes Akathisia Rating Scale. Eye movements were recorded using an eye-tracker SMI RED 500, and cognitive function was assessed using the Brief Assessment of Cognition in Schizophrenia. The statistical analyses were conducted using Minitab 17 Statistical Software, version 17.2.1. Data visualization and additional analyses were performed in the R 4.0.3 environment, using RStudio V 1.3.1093 software.Results: A network model of neurocognitive and oculomotor functions was constructed for the patients. In the full network (which includes all correlations) the median antisaccade latency value is the central element of the oculomotor domain, and the Symbol Coding test, the Digit Sequencing test, and the Verbal Fluency test are central elements in the neurocognitive domain. Additionally, there were connections between other cognitive and oculomotor functions, except for the antisaccade error latency in the oculomotor domain and the Token Motor Task in the neurocognitive domain.Conclusion: Network analysis provides measurable criteria for the assessment of neurophysiological and neurocognitive abnormalities in patients with schizophrenic spectrum disorders and allows to select key targets for their management and cognitive remediation.

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O6.2. A NETWORK FOR COGNITIVE, MOTOR, AND PSYCHOPATHOLOGICAL ALTERATIONS IN SCHIZOPHRENIA SPECTRUM DISORDERS

Schizophrenia Bulletin ◽

10.1093/schbul/sbaa028.031 ◽

2020 ◽

Vol 46 (Supplement_1) ◽

pp. S13-S14

Author(s):

Bernardo Moura ◽

Geeske van Rooijen ◽

Frederike Schirmbeck ◽

Johanna Wigman ◽

Peter Van Harten ◽

...

Keyword(s):

Network Analysis ◽

Graphical Model ◽

Clinical Manifestations ◽

Schizophrenia Spectrum Disorders ◽

Psychopathological Symptoms ◽

Remission Status ◽

Schizophrenia Spectrum ◽

Assessment And Treatment ◽

Spectrum Disorders ◽

Motor Alterations

Abstract Background Schizophrenia spectrum disorders are complex syndromes involving multiple clinical manifestations. Besides psychopathological symptoms, cognitive and motor alterations are also highly relevant in the context of the comprehension, assessment, and treatment of these disorders. Moreover, these three domains of clinical manifestations display complex reciprocal interactions that require further characterization. This work aims to use network analysis to investigate the associations between cognitive, motor, and psychopathological alterations in schizophrenia spectrum disorders. This approach might prove to be advantageous in identifying key variables for the assessment and treatment of these disorders. Methods A sample of 732 patients with schizophrenia spectrum disorders from a multi-site cohort study was included in the analysis. We estimated a network using a regularized Gaussian Graphical Model and conducted network stability analyses. Twenty-six nodes were included, encompassing items from the Positive and Negative Syndrome Scale, multiple neuropsychological tests, and clinician-assessed extrapyramidal symptoms’ scores. The results were further explored with centrality analyses and network comparisons between subgroups defined according to illness duration and remission status. Results We found that the estimated network was densely interconnected. Furthermore, nodes representing symptoms of disorganization were very central and, therefore, pivotal in connecting other psychopathological symptoms to cognitive and motor alterations. The estimated network for the subgroup of patients in remission showed a more sparse density and a different structure from the network of non-remitted patients. Discussion In conclusion, in the context of a broader representation of schizophrenia spectrum disorders’ manifestations, our results of a network analysis confirm a close association between different symptom domains and unveil a highly influential role of disorganization symptoms. Moreover, structural differences in networks occur according to remission status. These results are relevant for research in nosology, clinical assessment, and treatment approaches.

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