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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.

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.

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.

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