scholarly journals Cortical thickness across the cingulate gyrus in schizophrenia and its association to illness duration and memory performance

2022 ◽  
Author(s):  
J.-W. Thielen ◽  
B. W. Müller ◽  
D.-I. Chang ◽  
A. Krug ◽  
S. Mehl ◽  
...  
Keyword(s):  
Cortical Thickness ◽  
Cognitive Deficits ◽  
Neural Plasticity ◽  
Memory Performance ◽  
Posterior Part ◽  
Cingulate Gyrus ◽  
Schizophrenia Spectrum Disorder ◽  
Course Of Illness ◽  
Illness Duration ◽  
Schizophrenia Spectrum

AbstractSchizophrenia has been associated with structural brain abnormalities and cognitive deficits that partly change during the course of illness. In the present study, cortical thickness in five subregions of the cingulate gyrus was assessed in 44 patients with schizophrenia-spectrum disorder and 47 control persons and related to illness duration and memory capacities. In the patients group, cortical thickness was increased in the posterior part of the cingulate gyrus and related to illness duration whereas cortical thickness was decreased in anterior parts unrelated to illness duration. In contrast, cortical thickness was related to episodic and working memory performance only in the anterior but not posterior parts of the cingulate gyrus. Our finding of a posterior cingulate increase may point to either increased parietal communication that is accompanied by augmented neural plasticity or to effects of altered neurodegenerative processes in schizophrenia.

scholarly journals F95. DISRUPTION IN HIPPOCAMPAL-PREFRONTAL WHITE MATTER PATHWAYS AND MEMORY PERFORMANCE ACROSS STAGES OF SCHIZOPHRENIA-SPECTRUM DISORDER

2019 ◽  
Vol 45 (Supplement_2) ◽  
pp. S290-S290
Author(s):  
Cassandra Wannan ◽  
Cali Bartholomeusz ◽  
Mallar Chakravarty ◽  
Tamsyn Van Rheenen ◽  
Chad Bousman ◽  
...  
Keyword(s):  
White Matter ◽  
Memory Performance ◽  
Spectrum Disorder ◽  
Schizophrenia Spectrum Disorder ◽  
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.

MOTIVATION AND PLEASURE IN THE SCHIZOPHRENIA SPECTRUM–FINDINGS FROM THE PRODROME

2008 ◽  
Vol 31 (4) ◽  
pp. 10
Author(s):  
G Foussias ◽  
G Remington ◽  
R Mizrahi
Keyword(s):  
Cognitive Deficits ◽  
Negative Symptoms ◽  
Sampling Method ◽  
Personal Digital Assistant ◽  
Prodromal Phase ◽  
Daily Lives ◽  
Schizophrenia Spectrum ◽  
Influence Functional ◽  
The Moment ◽  
Positive And Negative Symptoms

Background: Schizophreniais a chronic and debilitating illness that affects approximately one percent of the population. The symptoms of schizophrenia are typically thought of in separate domains, including positive symptoms (hallucinations and delusions), negative symptoms (diminished emotional expression and amotivation), and cognitive deficits. Importantly, the negative symptoms have been consistently found to adversely influence functional outcomes, in particular due to markedamotivation.^1 There have been suggestions that these individuals also experience deficits in the experience of pleasure, especially in their capacity to anticipate pleasure.^2 However, such investigations have not included the examination of these symptoms in those in the prodromal phase ofthis illness, a time that holds promise for early intervention and altering thecourse of schizophrenia.^3 Methods: In an effort to examine deficits in motivation and pleasure in the prodromal phase of schizophrenia, we have used an experience sampling method to assess “in the moment” motivation and pleasure in individuals at high risk of developing schizophrenia and healthy controls. Subjects completed baseline assessments including evaluation of their positive and negative symptoms. Subsequently, through the use of a personal digital assistant, subjects rated their motivation and experience of consummatory and anticipatory pleasure in their daily lives, multiple times over the course of four days. Results and Conclusions: Preliminary data will be presented, as well as the importance of these findings in the context of understanding the underlying pathobiology of this illness, and guiding our search for effective treatments to improvefunctional outcomes in schizophrenia. References: 1. Sayers SL, Curran PJ, Mueser KT. Psychol Assessment 1996;8:269-80. 2. Gard DE, Kring AM, Gard GM, et al.. Schizophr Res 2007;93:253-60.

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.

033 The effect of sleep disturbance on cognition in late-life depression

SLEEP ◽  
2021 ◽  
Vol 44 (Supplement_2) ◽  
pp. A15-A15
Author(s):  
Andrea Ricciardiello ◽  
Sharon Naismith ◽  
Angela D’Rozario ◽  
Fiona Kumfor ◽  
Rick Wassing
Keyword(s):  
Executive Function ◽  
Sleep Disturbance ◽  
Slow Wave ◽  
Cognitive Deficits ◽  
Memory Performance ◽  
Verbal Learning ◽  
Late Life ◽  
Control Group ◽  
Sleep Spindles ◽  
Late Life Depression

Abstract Introduction Late-life depression is the most common psychiatric disorder in older adults and is associated with cognitive deficits, however, the role of sleep disturbance in cognitive deficits is poorly defined. In the current study we aimed to examine sleep macro and micro-architecture differences between those with late-life depression and controls. Secondly, we sought to determine how sleep changes relate to clinical memory and executive function measures in those with late-life depression and controls. Methods Using prior clinical data, this retrospective study assessed adults >50 years who had completed an overnight PSG study and comprehensive psychiatric, neuropsychological, and medical assessment. Memory performance was measured using the Weschler Memory Scale logical Memory 1 and 2 components, Rey Auditory Verbal Learning Test (Senior) 30-minute recall and Rey Complex Figure 3-minute recall. Executive function was defined by z scores from Trail Making Test, D-KEFS Stroop Test and Controlled Oral Word Association Test. The sample comprised of 71 depressed participants, defined by a Geriatric Depression Scale score ≥6, and 101 non-depressed participants (GDS <6 and no lifetime history of depression using DSM-IV criteria). Results Contrary to our hypothesis no significant macroarchitectural differences were observed between the groups. Less time spent in slow-wave sleep (SWS) was associated with worse delayed memory recall scores in the depression group (z=.342, p=0.008) although this was not seen in the control group. SWS and slow wave activity (SWA) were not related to measures of executive function performance. Depressed participants demonstrated a reduced level of sleep spindles (Dep= 159 ±142.8, con= 213±163, p=.03) although there were no associations with memory outcomes. Conclusion Compared to younger adults with depression, macroarchitectural differences in those with late-life depression are not as pronounced, due to a reduction of SWS and SWA power as a function of ageing. The efficiency of SWS hippocampal dependent memory processes in depression may be reduced, therefore, more time spent in SWS is related to better memory performance. This study assessed the density of sleep spindles but not spindle and slow wave oscillation coupling which may be more important for hippocampal dependent memory. Support (if any):

Development of a suspicion index for secondary schizophrenia using the Delphi method

2021 ◽  
pp. 000486742110257
Author(s):  
Olivier Bonnot ◽  
Jose Luis Insua ◽  
Mark Walterfang ◽  
Juan Vincente Torres ◽  
Stefan Armin Kolb
Keyword(s):  
Clinical Practice ◽  
Sensitivity And Specificity ◽  
Delphi Method ◽  
Schizophrenia Spectrum Disorders ◽  
Differential Distribution ◽  
Schizophrenia Spectrum Disorder ◽  
Schizophrenia Spectrum ◽  
Spectrum Disorders ◽  
Aids Diagnosis ◽  
Suspicion Index

Aim: The aim of this study was to develop a suspicion index that aids diagnosis of secondary schizophrenia spectrum disorders in regular clinical practice. Method: We used the Delphi method to rate and refine questionnaire items in consecutive rounds. Differences in mean expert responses for schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders populations allowed to define low/middle/high predictive items, which received different weights. Algorithm performance was tested in 198 disease profiles by means of sensitivity and specificity. Results: Twelve experts completed the Delphi process, and consensus was reached in 19/24 (79.2%) items for schizophrenia spectrum disorders and 17/24 (70.8%) for secondary schizophrenia spectrum disorders. We assigned rounded values to each item category according to their predictive potential. A differential distribution of scores was observed between schizophrenia spectrum disorders and secondary schizophrenia spectrum disorders when applying the suspicion index for validation to 198 disease profiles. Sensitivity and specificity analyses allowed to set a >8/10/16 risk prediction score as a threshold to consider medium/high/very high suspicion of secondary schizophrenia spectrum disorders. Conclusion: Our final outcome was the Secondary Schizophrenia Suspicion Index, the first paper-based and reliable algorithm to discriminate secondary schizophrenia spectrum disorders from schizophrenia spectrum disorders with the potential to help improve the detection of secondary schizophrenia spectrum disorder cases in clinical practice.

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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