scholarly journals T73. COGNITIVE CLUSTERING IN SCHIZOPHRENIA SPECTRUM DISORDER AND THE ASSOCIATION WITH BRAIN VOLUME

2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S259-S259
Author(s):  
Priscilla Oomen ◽  
Marieke Begemann ◽  
Hannah de Muinck Keizer ◽  
Iris Sommer
Keyword(s):  
Hierarchical Clustering ◽  
Brain Volume ◽  
Spectrum Disorder ◽  
Healthy Controls ◽  
Cognitive Profiles ◽  
Schizophrenia Spectrum Disorder ◽  
Whole Brain ◽  
Schizophrenia Spectrum ◽  
Significant Difference ◽  
Cluster 2

Abstract Background Cognitive impairment is a core feature of schizophrenia spectrum disorder (SSD), and appears in both mild and severe forms. As cognition is crucial for functioning in daily life, it is important to understand these impairments. Large heterogeneity exists within these cognitive impairments, and different cognitive profiles may be associated with dissimilar structural brain volumes. Such cognitive brain profiles may be relevant biomarkers for more homogeneous subclasses to be used for both prognosis and choice of optimal care. Methods The population consisted of 85 individuals with schizophrenia spectrum disorder (mean age 27 years, 64 males) and 40 healthy controls (mean age 24 years, 31 males). To identify cognitive clusters, hierarchical clustering analyses were conducted using performance on the Brief Assessment of Cognition in Schizophrenia (BACS) battery. The emerging cognitive clusters were compared in performance on the BACS, diagnosis and whole brain volume. Results Hierarchical clustering analyses revealed three cognitive profiles: cluster 1 “relatively intact” cluster 2 “mild-moderate impairment” and cluster 3 “severe impairment”. Cluster 1 comprised of 68% healthy controls vs 32% SSD patients, whereas clusters 3 comprised of 89% SSD patients vs 11% healthy controls. Cluster 2 was a rather mixed cluster with 25% healthy controls and 75% SSD patients. Whole brain volume shows a continuum towards smaller brain volume in the more impaired clusters with a significant difference shown in whole brain volume between cluster 1 and 3. Discussion These findings support the concept that cognitive heterogeneity among individuals with schizophrenia spectrum disorder can be reduced by using cognitive clustering methods. Furthermore, cognitive clusters are associated with brain volume sizes, indicating different underlying brain structure. Future research should focus on the predictive power of such clusters.

scholarly journals Brain Volumetric Changes and Cognitive Functions in Epileptic Patients

QJM ◽  
2020 ◽  
Vol 113 (Supplement_1) ◽  
Author(s):  
A A Ashour ◽  
A M A Nassef ◽  
E M Awad ◽  
A M Hazzou ◽  
M A Nada ◽  
...  
Keyword(s):  
Cognitive Functions ◽  
Brain Volume ◽  
Control Group ◽  
Healthy Controls ◽  
Whole Brain ◽  
Significant Difference ◽  
Epileptic Patients ◽  
Generalized Epilepsy ◽  
Patients With Epilepsy ◽  
And Control

Abstract Background Epilepsy is a serious common neurological disorder that can affect any age. Cognitive functions are highly prevalent in patients with epilepsy and is more likely to occur in patients with idiopathic generalized epilepsy (IGE). Associations were found between cognitive functions and brain volume loss in patients with epilepsy. Objective This work was carried out to assess the volumetric changes in brain of epileptic patients to use it as a biomarker for cognitive dysfunction in adult and adolescent patients with epilepsy. Patients and Methods A case control study was conducted to include 61 patients, 20 of which diagnosed with idiopathic generalized epilepsy (IGE), 21 with temporal lobe epilepsy (TLE) and 20 with frontal lobe epilepsy (FLE) who were selected from the epilepsy outpatient clinic in Ain Shams university hospitals along with 23 age and sex matched healthy controls. Both cases and control groups were subjected to Magnetic resonance imaging MRI brain volumetry and detailed cognitive testing. An informed consent was taken from each adult patient, guardian of adolescent patient and healthy control. Results Statistically significant difference in comprehension subcategory of the Wechsler adult intelligence scale (WAIS) between patients with IGE and healthy controls denoting poorer social judgment in the IGE group. The IGE group also showed poorer performance in digit symbol subcategory of the same test denoting worse psychomotor speed and sustained attention. Also, significant difference in similarities subcategory was found between TLE group and control group denoting poorer abstract thinking among the TLE group. The IGE and TLE groups also showed lower attention and concentration than control group in the mental control subcategory of the Wechsler memory scale (WMS) yet failed to show superiority over each other. No statistically significant difference was found on comparing the whole brain volume between cases and control groups. A statistically significant direct relationship was found between the arithmetic subcategory of WAIS and the whole brain volume of the patients among the patients of the FLE group. Conclusion Patients with IGE had worse psychomotor speed, sustained attention and concentration than healthy controls in addition to poorer social judgment. Also, patients with TLE showed lower attention and concentration together with poorer abstract thinking despite normal IQ. The study also concluded that increased whole brain volume in patients with frontal lobe epilepsy is associated with better mathematical problem solving.

scholarly journals Spatial frequency discrimination in patients with schizophrenia spectrum and bipolar disorders: Evidence of early visual processing deficits and associations with intellectual abilities

2021 ◽  
Author(s):  
Aili Roetterud Loechen ◽  
Knut Kolskaar ◽  
Ann-Marie Glasoe de Lange ◽  
Markus Sneve ◽  
Beathe Haatveit ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Visual Discrimination ◽  
Linear Models ◽  
Bipolar Disorders ◽  
Discrimination Threshold ◽  
Spectrum Disorder ◽  
Healthy Controls ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Post Hoc

Objective: Low-level sensory disruption is hypothesized as a precursor to clinical and cognitive symptoms in severe mental disorders. We compared visual discrimination performance in patients with schizophrenia spectrum disorder or bipolar disorder with healthy controls, and investigated associations with clinical symptoms and IQ. Methods: Patients with schizophrenia spectrum disorder (n=32), bipolar disorder (n=55) and healthy controls (n=152) completed a computerized visual discrimination task. Participants responded whether the latter of two consecutive grids had higher or lower spatial frequency, and discrimination thresholds were estimated using an adaptive maximum likelihood procedure. Case-control differences in threshold were assessed using linear regression, F-test and post-hoc pair-wise comparisons. Linear models were used to test for associations between visual discrimination threshold and psychotic symptoms derived from the PANSS and IQ assessed using the Matrix Reasoning and Vocabulary subtests from the Wechsler Abbreviated Scale of Intelligence (WASI). Results: Robust regression revealed a significant main effect of diagnosis on discrimination threshold (robust F=6.76, p=.001). Post-hoc comparisons revealed that patients with a schizophrenia spectrum disorder (mean=14%, SD=0.08) had higher thresholds compared to healthy controls (mean=10.8%, SD = 0.07, β = 0.35, t=3.4, p=0.002), as did patients with bipolar disorder (12.23%, SD=0.07, β= 0.21, t=2.42, p=0.04). There was no significant difference between bipolar disorder and schizophrenia (β=-0.14, t=-1.2, p=0.45). Linear models revealed negative associations between IQ and threshold across all participants when controlling for diagnostic group (β = -0.3, t=-3.43, p=0.0007). This association was found within healthy controls (t=-3.72, p=.0003) and patients with bipolar disorder (t=-2.53, p=.015), and no significant group by IQ interaction on threshold (F=0.044, p=.97). There were no significant associations between PANSS domain scores and discrimination threshold. Conclusion: Patients with schizophrenia spectrum or bipolar disorders exhibited higher visual discrimination thresholds than healthy controls, supporting early visual deficits among patients with severe mental illness. Discrimination threshold was negatively associated with IQ among healthy controls and bipolar disorder patients. These findings elucidate perception-related disease mechanisms in severe mental illness, which warrants replication in independent samples.

scholarly journals Semantic Memory Impairment Across the Schizophrenia Continuum: A Meta-Analysis of Category Fluency Performance

2020 ◽  
Vol 1 (1) ◽  
Author(s):  
Eric Josiah Tan ◽  
Erica Neill ◽  
Kiandra Tomlinson ◽  
Susan Lee Rossell
Keyword(s):  
Semantic Memory ◽  
Cluster Size ◽  
Spectrum Disorder ◽  
Healthy Controls ◽  
Chronic Patients ◽  
Schizophrenia Spectrum Disorder ◽  
Illness Onset ◽  
First Degree Relatives ◽  
Schizophrenia Spectrum ◽  
Category Fluency

Abstract Semantic memory (SM) impairments are a core feature of schizophrenia and are present along the psychosis continuum. It is, however, unclear whether the degree of SM impairments vary along this continuum and if demographic and clinical factors affect impairment severity. This study performed meta-analyses of category fluency task performance (a task commonly used to assess SM) in 4 groups along the schizophrenia continuum: high schizotypes (HSZT), first-degree relatives (FDR), recent-onset patients (≤2 y; ROP) and chronic patients (CSZ). Electronic databases were searched for relevant studies published up to October 2019 resulting in the inclusion of 48 articles. The main analyses assessed fluency productivity scores in 2978 schizophrenia spectrum disorder patients, 340 first-degree relatives of schizophrenia spectrum disorder patients, and 3204 healthy controls. Further analyses assessed errors, mean cluster size, and switching data that were available in the CSZ group only. Results revealed significant impairments in fluency productivity were present in the FDR, ROP, and CSZ groups relative to healthy controls, but not in HSZT. In the CSZ group, significant differences relative to healthy controls were also observed in non-perseverative errors, mean cluster size, and number of switches. The findings collectively suggest that SM deficits are present at each stage of the continuum and are exacerbated post-illness onset. They also support the centrality of SM impairments in schizophrenia and most elevated risk groups. Future studies with more diverse measures of SM function are needed to replicate and extend this research.

Comparisons of Voxel-Based Morphometric Brain Volumes of Individuals with Methamphetamine-Induced Psychotic Disorder and Schizophrenia Spectrum Disorder and Healthy Controls

2019 ◽  
Vol 79 (2) ◽  
pp. 170-178 ◽  
Author(s):  
Vahid Farnia ◽  
Firoozeh Farshchian ◽  
Nazanin Farshchian ◽  
Mostafa Alikhani ◽  
Dena Sadeghi Bahmani ◽  
...  
Keyword(s):  
Psychotic Disorder ◽  
Spectrum Disorder ◽  
Healthy Controls ◽  
Schizophrenia Spectrum Disorder ◽  
Brain Volumes ◽  
Schizophrenia Spectrum

scholarly journals Hippocampal subfields and visuospatial associative memory across stages of schizophrenia-spectrum disorder

2018 ◽  
Vol 49 (14) ◽  
pp. 2452-2462 ◽  
Author(s):  
Cassandra M. J. Wannan ◽  
Vanessa L. Cropley ◽  
M. Mallar Chakravarty ◽  
Tamsyn E. Van Rheenen ◽  
Sam Mancuso ◽  
...  
Keyword(s):  
Dentate Gyrus ◽  
Associative Memory ◽  
Memory Performance ◽  
Spectrum Disorder ◽  
Grey Matter Volume ◽  
Healthy Controls ◽  
Schizophrenia Spectrum Disorder ◽  
Recent Onset ◽  
Hippocampal Subfields ◽  
Schizophrenia Spectrum

AbstractBackgroundWhile previous studies have identified relationships between hippocampal volumes and memory performance in schizophrenia, these relationships are not apparent in healthy individuals. Further, few studies have examined the role of hippocampal subfields in illness-related memory deficits, and no study has examined potential differences across varying illness stages. The current study aimed to investigate whether individuals with early and established psychosis exhibited differential relationships between visuospatial associative memory and hippocampal subfield volumes.MethodsMeasurements of visuospatial associative memory performance and grey matter volume were obtained from 52 individuals with a chronic schizophrenia-spectrum disorder, 28 youth with recent-onset psychosis, 52 older healthy controls, and 28 younger healthy controls.ResultsBoth chronic and recent-onset patients had impaired visuospatial associative memory performance, however, only chronic patients showed hippocampal subfield volume loss. Both chronic and recent-onset patients demonstrated relationships between visuospatial associative memory performance and hippocampal subfield volumes in the CA4/dentate gyrus and the stratum that were not observed in older healthy controls. There were no group by volume interactions when chronic and recent-onset patients were compared.ConclusionsThe current study extends the findings of previous studies by identifying particular hippocampal subfields, including the hippocampal stratum layers and the dentate gyrus, that appear to be related to visuospatial associative memory ability in individuals with both chronic and first-episode psychosis.

scholarly journals Acoustic speech markers for schizophrenia-spectrum disorders: a diagnostic and symptom-recognition tool

2021 ◽  
pp. 1-11
Author(s):  
J. N. de Boer ◽  
A. E. Voppel ◽  
S. G. Brederoo ◽  
H. G. Schnack ◽  
K. P. Truong ◽  
...  
Keyword(s):  
Negative Symptoms ◽  
Structured Interview ◽  
Diagnostic Value ◽  
Spectrum Disorder ◽  
Psychotic Symptoms ◽  
Schizophrenia Spectrum Disorders ◽  
Schizophrenia Spectrum Disorder ◽  
Speech Technology ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders

Abstract Background Clinicians routinely use impressions of speech as an element of mental status examination. In schizophrenia-spectrum disorders, descriptions of speech are used to assess the severity of psychotic symptoms. In the current study, we assessed the diagnostic value of acoustic speech parameters in schizophrenia-spectrum disorders, as well as its value in recognizing positive and negative symptoms. Methods Speech was obtained from 142 patients with a schizophrenia-spectrum disorder and 142 matched controls during a semi-structured interview on neutral topics. Patients were categorized as having predominantly positive or negative symptoms using the Positive and Negative Syndrome Scale (PANSS). Acoustic parameters were extracted with OpenSMILE, employing the extended Geneva Acoustic Minimalistic Parameter Set, which includes standardized analyses of pitch (F0), speech quality and pauses. Speech parameters were fed into a random forest algorithm with leave-ten-out cross-validation to assess their value for a schizophrenia-spectrum diagnosis, and PANSS subtype recognition. Results The machine-learning speech classifier attained an accuracy of 86.2% in classifying patients with a schizophrenia-spectrum disorder and controls on speech parameters alone. Patients with predominantly positive v. negative symptoms could be classified with an accuracy of 74.2%. Conclusions Our results show that automatically extracted speech parameters can be used to accurately classify patients with a schizophrenia-spectrum disorder and healthy controls, as well as differentiate between patients with predominantly positive v. negatives symptoms. Thus, the field of speech technology has provided a standardized, powerful tool that has high potential for clinical applications in diagnosis and differentiation, given its ease of comparison and replication across samples.

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