A precise diagnosis and a comprehensive assessment of symptom severity are important clinical issues in patients with schizophrenia (SZ). We investigated whether electroencephalography (EEG) features obtained from EEG source network analyses could be effectively applied to classify the SZ subtypes based on symptom severity. Sixty-four electrode EEG signals were recorded from 119 patients with SZ (53 males and 66 females) and 119 normal controls (NC, 51 males and 68 females) during resting-state with closed eyes. Brain network features (global and local clustering coefficient and global path length) were calculated from EEG source activities. According to positive, negative, and cognitive/disorganization symptoms, the SZ patients were divided into two groups (high and low) by positive and negative syndrome scale (PANSS). To select features for classification, we used the sequential forward selection (SFS) method. The classification accuracy was evaluated using 10 by 10-fold cross-validation with the linear discriminant analysis (LDA) classifier. The best classification accuracy was 80.66% for estimating SZ patients from the NC group. The best classification accuracy between low and high groups in positive, negative, and cognitive/disorganization symptoms were 88.10%, 75.25%, and 77.78%, respectively. The selected features well-represented the pathological brain regions of SZ. Our study suggested that resting-state EEG network features could successfully classify between SZ patients and the NC, and between low and high SZ groups in positive, negative, and cognitive/disorganization symptoms.

Reduced oxygenation changes in the prefrontal cortex during cognitive tasks have been reported in major depressive disorder (MDD). However, prefrontal asymmetry during cognitive tasks and its relation to suicide ideations have been less frequently examined in patients with MDD. This study investigated prefrontal asymmetry and its moderating effect on the relationship between depression severity and suicidal ideation in MDD patients during cognitive tasks. Forty-two patients with MDD and 64 healthy controls (HCs) were assessed for changes in oxygenated and deoxygenated hemoglobin (Hb) in the prefrontal cortex using functional near-infrared spectroscopy (fNIRS) during the verbal fluency task (VFT), Stroop task, and two-back task. Depression, anxiety, and suicide ideation were measured through self-report questionnaires. Relatively smaller left oxy-Hb changes during VFT, but not during the Stroop or two-back tasks, were found in MDD patients compared with HCs. Furthermore, prefrontal asymmetry during VFT moderated the effect of depression severity on suicide ideation, and was significantly and positively correlated with suicide ideation in patients with MDD. Specifically, relatively greater left oxy-Hb changes were associated with greater suicide ideation. These findings suggest fNIRS-measured prefrontal asymmetry as a potential biomarker for MDD and for the assessment of suicidal risk in patients with MDD.

Brain functional changes could be observed in people after an experience of virtual reality (VR). The present study investigated cyber sickness and changes of brain regional activity using electroencephalogram (EEG)-based source localization, before and after a VR experience involving a smartphone-assisted head mount display. Thirty participants (mean age = 25 years old) were recruited. All were physically healthy and had no ophthalmological diseases. Their corrected vision was better than 20/20. Resting state EEG and the simulator sickness questionnaire (SSQ) were measured before and after the VR experience. Source activity of each frequency band was calculated using the sLORETA program. After the VR experience, the SSQ total score and sub scores (nausea, oculomotor symptoms, and disorientation) were significantly increased, and brain source activations were significantly increased: alpha1 activity in the cuneus and alpha2 activity in the cuneus and posterior cingulate gyrus (PCG). The change of SSQ score (after–before) showed significant negative correlation with the change of PCG activation (after–before) in the alpha2 band. The study demonstrated increased cyber sickness and increased alpha band power in the cuneus and PCG after the VR experience. Reduced PCG activation in alpha band may be associated with the symptom severity of cyber sickness.

Computed tomography (CT) is a widely used medical imaging modality for diagnosing various diseases. Among CT techniques, 4-dimensional CT perfusion (4D-CTP) of the brain is established in most centers for diagnosing strokes and is considered the gold standard for hyperacute stroke diagnosis. However, because the detrimental effects of high radiation doses from 4D-CTP may cause serious health risks in stroke survivors, our research team aimed to introduce a novel image-processing technique. Our singular value decomposition (SVD)-based image-processing technique can improve image quality, first, by separating several image components using SVD and, second, by reconstructing signal component images to remove noise, thereby improving image quality. For the demonstration in this study, 20 4D-CTP dynamic images of suspected acute stroke patients were collected. Both the images that were and were not processed via the proposed method were compared. Each acquired image was objectively evaluated using contrast-to-noise and signal-to-noise ratios. The scores of the parameters assessed for the qualitative evaluation of image quality improved to an excellent rating (p < 0.05). Therefore, our SVD-based image-denoising technique improved the diagnostic value of images by improving their quality. The denoising technique and statistical evaluation can be utilized in various clinical applications to provide advanced medical services.

(1) Background: Prediction of treatment outcome has been one of the core objectives in clinical research of patients with major depressive disorder (MDD). This study explored the possibility of event-related potential (ERP) markers to predict antidepressant treatment outcomes among MDD patients; (2) Methods: Fifty-two patients with MDD were recruited and evaluated through Hamilton depression (HAM-D), Hamilton anxiety rating scale (HAM-A), and CORE. Patients underwent a battery of ERP measures including frontal alpha symmetry (FAA) in the low alpha band (8–10 Hz), mismatch negativity (MMN), and loudness-dependent auditory evoked potentials (LDAEP); (3) Results: During the eight weeks of study, 61% of patients achieved remission, and 77% showed successful treatment responsiveness. Patients with low FAA in F5/F6 demonstrated a significantly higher remission/response ratio and better treatment responsiveness (F (2.560, 117.755) = 3.84, p = 0.016) compared to patients with high FAA. In addition, greater FAA in F7/F8 EEG channels was significantly associated with greater melancholia scores (r = 0.34, p = 0.018). Other ERP markers lacked any significant effect; (4) Conclusions: Our results suggested low FAA (i.e., greater left frontal activity) could reflect a good treatment response in MDD patients. These findings support that FAA could be a promising index in understanding both MDD and melancholic subtype.

Objective: While impaired facial expression recognition has been closely associated with reduced temporal lobe volume in patients with schizophrenia, this study aimed at examining whether empathy and social attribution affect such a relationship. Methods: A total of 43 patients with schizophrenia and 43 healthy controls underwent a facial expression recognition task (FERT) and magnetic resonance imaging. Basic empathy scale and the social attribution task-multiple choice were used to measure empathy and social attribution. Results: Patients with schizophrenia showed significant positive correlations between the total temporal lobe volume and the FERT-accuracy (FERT-ACC). Diminished temporal lobe volume predicted the impaired facial emotion recognition ability. Both empathy and social attribution played roles as moderators of the path from the left amygdala volume, left fusiform gyrus volume, both sides of the superior temporal gyrus volume, and left middle temporal gyrus volume to the FERT-ACC. In contrast, empathy alone functioned as a moderator between the right fusiform gyrus volume, right middle temporal gyrus volume, and FERT-ACC. No significant interaction was found for healthy controls. Conclusion: Our results suggest that social cognition remediation training on empathy and social attribution, could buffer the negative effects of small temporal lobe volume on interpersonal emotional communication in patients with schizophrenia.