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Human induced pluripotent stem cells (hiPSC) provide an attractive tool to study disease mechanisms of neurodevelopmental disorders such as schizophrenia. A pertinent problem is the development of hiPSC-based assays to discriminate schizophrenia (SZ) from autism spectrum disorder (ASD) models. Healthy control individuals as well as patients with SZ and ASD were examined by a panel of diagnostic tests. Subsequently, skin biopsies were taken for the generation, differentiation, and testing of hiPSC-derived neurons from all individuals. SZ and ASD neurons share a reduced capacity for cortical differentiation as shown by quantitative analysis of the synaptic marker PSD95 and neurite outgrowth. By contrast, pattern analysis of calcium signals turned out to discriminate among healthy control, schizophrenia, and autism samples. Schizophrenia neurons displayed decreased peak frequency accompanied by increased peak areas, while autism neurons showed a slight decrease in peak amplitudes. For further analysis of the schizophrenia phenotype, transcriptome analyses revealed a clear discrimination among schizophrenia, autism, and healthy controls based on differentially expressed genes. However, considerable differences were still evident among schizophrenia patients under inspection. For one individual with schizophrenia, expression analysis revealed deregulation of genes associated with the major histocompatibility complex class II (MHC class II) presentation pathway. Interestingly, antipsychotic treatment of healthy control neurons also increased MHC class II expression. In conclusion, transcriptome analysis combined with pattern analysis of calcium signals appeared as a tool to discriminate between SZ and ASD phenotypes in vitro.

A potential clinical and etiological overlap between schizophrenia (SZ) and bipolar disorder (BD) has long been a subject of discussion. Imaging studies imply functional and structural alterations of the hippocampus in both diseases. Thus, imaging this core memory region could provide insight into the pathophysiology of these disorders and the associated cognitive deficits. To examine possible shared alterations in the hippocampus, we conducted a multi-modal assessment, including functional and structural imaging as well as neurobehavioral measures of memory performance in BD and SZ patients compared with healthy controls. We assessed episodic memory performance, using tests of verbal and visual learning (HVLT, BVMT) in three groups of participants: BD patients (n = 21), SZ patients (n = 21) and matched (age, gender, education) healthy control subjects (n = 21). In addition, we examined hippocampal resting state functional connectivity, hippocampal volume using voxel-based morphometry (VBM) and fibre integrity of hippocampal connections using diffusion tensor imaging (DTI). We found memory deficits, changes in functional connectivity within the hippocampal network as well as volumetric reductions and altered white matter fibre integrity across patient groups in comparison with controls. However, SZ patients when directly compared with BD patients were more severely affected in several of the assessed parameters (verbal learning, left hippocampal volumes, mean diffusivity of bilateral cingulum and right uncinated fasciculus). The results of our study suggest a graded expression of verbal learning deficits accompanied by structural alterations within the hippocampus in BD patients and SZ patients, with SZ patients being more strongly affected. Our findings imply that these two disorders may share some common pathophysiological mechanisms. The results could thus help to further advance and integrate current pathophysiological models of SZ and BD.

Over the past decades, functional near-infrared spectroscopy (fNIRS) has become a valuable tool in the online assessment of brain function in psychological and neuropsychiatric research. Recently, fNIRS has also been employed in the context of neurofeedback (NF), with pilot studies indicating that hemodynamic responses can be deliberately regulated and that neuroplastic changes occur over the course of several training sessions. This review article provides a comprehensive overview of the recent implementation and development of fNIRS as an NF tool; specifically, we will outline initial studies in healthy participants as well as children and adults with attention deficit hyperactivity disorder and describe new protocols aimed at reducing auditory verbal hallucinations (schizophrenic patients) and anxiety symptoms (patients with social anxiety disorder), respectively. Finally, we will discuss recent methodological developments and concerns as well as potential future perspectives. We conclude that fNIRS is a useful tool for conducting NF, especially in terms of multi-session training. However, methodological details need to be considered when designing fNIRS-based NF studies, and future protocols should aim at training broader network structures and implementing implicit training protocols. Finally, future studies should focus not only on (clinical) effects of fNIRS-based NF, but also on the underlying mechanisms and activity changes in extended brain networks.

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Polygenic risk scores, based on risk variants identified in genome-wide-association-studies (GWAS), explain a considerable portion of the heritability for schizophrenia (SZ) and bipolar disorder (BD). However, little is known about the combined effects of these variants, although polygenic neuroimaging has developed into a powerful tool of translational neuroscience. In this study, we used genome wide significant SZ risk variants to test the predictive capacity of the polygenic model and explored potential associations with white matter volume, a key candidate in imaging phenotype for psychotic disorders.By calculating the combined additive schizophrenia risk of seven SNPs (significant hits from a recent schizophrenia GWAS study), we show that increased additive genetic risk for SZ was associated with reduced white matter volume in a group of participants (n = 94) consisting of healthy individuals, SZ first-degree relatives, SZ patients and BD patients. This effect was also seen in a second independent sample of healthy individuals (n = 89). We suggest that a moderate portion of variance (~4%) of white matter volume can be explained by the seven hits from the recent schizophrenia GWAS.These results provide evidence for associations between cumulative genetic risk for schizophrenia and intermediate neuroimaging phenotypes in models of psychosis. Our work contributes to a growing body of literature suggesting that polygenic risk may help to explain white matter alterations associated with familial risk for psychosis.

A flexible and dynamically adjustable behavior is crucial to adapt to a continuously changing environment. In order to optimally adapt, we need to learn from the consequences of our behavior. We usually learn through different kinds of prediction errors, which occur when we experience unexpected situations due to false predictions. With this literature review, we intended to contribute to current etiological models that ascribe various positive symptoms (particularly delusions and hallucinations) in patients with schizophrenia to false prediction errors and deficient predictive learning. We discuss alterations in the electrophysiological measure of the error‐related negativity/error negativity (ERN/Ne) as a global deficit and a trait in schizophrenia, as they have been observed in different samples of patients with schizophrenia, in individuals at high‐risk and individuals with subclinical schizotypal traits. As the ERN/Ne can itself be considered the result of predictive processes (evaluation of current action outcomes as worse than expected), we propose that the reported alterations indicate that patients suffering from schizophrenic illnesses fail to adequately classify the outcomes of their actions as better or worse than expected due to a deficit in self‐monitoring. Furthermore, we discuss results in further action‐monitoring components, such as the correct response negativity (CRN)—a smaller negativity elicited by correct responses; and error positivity (Pe)—a later positivity assumed to reflect conscious error processing. The reported results show normal Pe amplitudes and normal post‐error adjustments (adaptations after committed error to improve performance), indicating an intact later and conscious processing. From the results of diminished differences between ERN/Ne and CRN amplitudes, we conclude a general predictive deficit in early aspects of self‐monitoring associated with positive symptoms in patients with schizophrenia.

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