Cognitive Profiles and Functional Connectivity in First-Episode Schizophrenia Spectrum Disorders - Linking Behavioral and Neuronal Data.

The character of cognitive deficit in schizophrenia is not clear due to the heterogeneity in research results. In heterogeneous conditions, the cluster solution allows the classification of individuals based on profiles. Our aim was to examine the cognitive profiles of first-episode schizophrenia spectrum disorder (FES) subjects based on cluster analysis, and to correlate these profiles with clinical variables and resting state brain connectivity, as measured with magnetic resonance imaging. A total of 67 FES subjects were assessed with a neuropsychological test battery and on clinical variables. The results of the cognitive domains were cluster analyzed. In addition, functional connectivity was calculated using ROI-to-ROI analysis with four groups: Three groups were defined based on the cluster analysis of cognitive performance and a control group with a normal cognitive performance. The connectivity was compared between the patient clusters and controls. We found different cognitive profiles based on three clusters: Cluster 1: decline in the attention, working memory/flexibility, and verbal memory domains. Cluster 2: decline in the verbal memory domain and above average performance in the attention domain. Cluster 3: generalized and severe deficit in all of the cognitive domains. FES diagnoses were distributed among all of the clusters. Cluster comparisons in neural connectivity also showed differences between the groups. Cluster 1 showed both hyperconnectivity between the cerebellum and precentral gyrus, the salience network (SN) (insula cortex), and fronto-parietal network (FPN) as well as between the PreCG and SN (insula cortex) and hypoconnectivity between the default mode network (DMN) and seeds of SN [insula and supramarginal gyrus (SMG)]; Cluster 2 showed hyperconnectivity between the DMN and cerebellum, SN (insula) and precentral gyrus, and FPN and IFG; Cluster 3 showed hypoconnectivity between the DMN and SN (insula) and SN (SMG) and pallidum. The cluster solution confirms the prevalence of a cognitive decline with different patterns of cognitive performance, and different levels of severity in FES. Moreover, separate behavioral cognitive subsets can be linked to patterns of brain functional connectivity.

Theoretical Modeling of Cognitive Dysfunction in Schizophrenia by Means of Errors and Corresponding Brain Networks.

The current evidence of cognitive disturbances and brain alterations in schizophrenia does not provide the plausible explanation of the underlying mechanisms. Neuropsychological studies outlined the cognitive profile of patients with schizophrenia, that embodied the substantial disturbances in perceptual and motor processes, spatial functions, verbal and non-verbal memory, processing speed and executive functioning. Standardized scoring in the majority of the neurocognitive tests renders the index scores or the achievement indicating the severity of the cognitive impairment rather than the actual performance by means of errors. At the same time, the quantitative evaluation may lead to the situation when two patients with the same index score of the particular cognitive test, demonstrate qualitatively different performances. This may support the view why test paradigms that habitually incorporate different cognitive variables associate weakly, reflecting an ambiguity in the interpretation of noted cognitive constructs. With minor exceptions, cognitive functions are not attributed to the localized activity but eventuate from the coordinated activity in the generally dispersed brain networks. Functional neuroimaging has progressively explored the connectivity in the brain networks in the absence of the specific task and during the task processing. The spatio-temporal fluctuations of the activity of the brain areas detected in the resting state and being highly reproducible in numerous studies, resemble the activation and communication patterns during the task performance. Relatedly, the activation in the specific brain regions oftentimes is attributed to a number of cognitive processes. Given the complex organization of the cognitive functions, it becomes crucial to designate the roles of the brain networks in relation to the specific cognitive functions. One possible approach is to identify the commonalities of the deficits across the number of cognitive tests or, common errors in the various tests and identify their common "denominators" in the brain networks. The qualitative characterization of cognitive performance might be beneficial in addressing diffuse cognitive alterations presumably caused by the dysconnectivity of the distributed brain networks. Therefore, in the review, we use this approach in the description of standardized tests in the scope of potential errors in patients with schizophrenia with a subsequent reference to the brain networks.

The PsyLOG mobile application: development of a tool for the assessment and monitoring of side effects of psychotropic medication.

Mobile health interventions are regarded as affordable and accessible tools that can enhance standard psychiatric care. As part of the mHealth Psycho-Educational Intervention Versus Antipsychotic-Induced Side Effects (mPIVAS) project (www.psylog.eu), we developed the mobile application "PsyLOG" based on mobile "smartphone" technology to monitor antipsychotic-induced side effects. The aim of this paper is to describe the rationale and development of the PsyLOG and its clinical use. The PsyLOG application runs on smartphones with Android operating system. The application is currently available in seven languages (Croatian, Czech, English, French, German, Japanese and Serbian). It consists of several categories: "My Drug Effects", "My Life Styles", "My Charts", "My Medication", "My Strategies", "My Supporters", "Settings" and "About". The main category "My Drug Effects" includes a list of 30 side effects with the possibility to add three additional side effects. Side effects are each accompanied by an appropriate description and the possibility to rate its severity on a visual analogue scale from 0-100%. The PsyLOG application is intended to enhance the link between patients and mental health professionals, serving as a tool that more objectively monitors side-effects over certain periods of time. To the best of our knowledge, no such applications have so far been developed for patients taking antipsychotic medication or for their therapists.

Recruitment to psychiatry in the Czech Republic: 'waiting for resuscitation'?

Recruitment to psychiatry is becoming a serious obstacle in providing first-class mental health treatment in many countries worldwide. We attempt to address this burning issue by examining medical student's attitudes towards psychiatry and factors influencing their career choice in the Czech Republic. In 2010, 71 students in their last year of medical school at the First Faculty of Medicine, Charles University, Prague were recruited in this quantitative cross-sectional online study. From the sample, 16% (n = 11) of students were considering psychiatry as a career path. An important factor in choosing psychiatry as a career path was personal/family presence of mental illness. Longer experience with psychiatry placement also contributed to the choice of psychiatry, as well as participation in elective courses or psychiatric research projects. Students considering psychiatry were less systematic compared to the group not considering psychiatry. Low reported levels of recruitment to psychiatry present a problematic issue in the Czech Republic. To make psychiatry more appealing to medical students, proactive steps by the relevant stakeholders need to be implemented. These strategies should include steps such as allocating more time for psychiatry in the medical curriculum, better quality of lectures, and the inclusion of additional elective courses.