Brain–computer interfaces (BCIs) have demonstrated the potential to provide paralyzed individuals with new means of communication, but an electroencephalography (EEG)-based endogenous BCI has never been successfully used for communication with a patient in a completely locked-in state (CLIS). In this study, we investigated the possibility of using an EEG-based endogenous BCI paradigm for online binary communication by a patient in CLIS. A female patient in CLIS participated in this study. She had not communicated even with her family for more than one year with complete loss of motor function. Offline and online experiments were conducted to validate the feasibility of the proposed BCI system. In the offline experiment, we determined the best combination of mental tasks and the optimal classification strategy leading to the best performance. In the online experiment, we investigated whether our BCI system could be potentially used for real-time communication with the patient. An online classification accuracy of 87.5% was achieved when Riemannian geometry-based classification was applied to real-time EEG data recorded while the patient was performing one of two mental-imagery tasks for 5 s. Our results suggest that an EEG-based endogenous BCI has the potential to be used for online communication with a patient in CLIS.

Structural covariance is described as coordinated variation in brain morphological features, such as cortical thickness and volume, among brain structures functionally or anatomically interconnected to one another. Structural covariance networks, based on graph theory, have been studied in mental disorders. This analysis can help in understanding the brain mechanisms of schizophrenia and bipolar disorder. We investigated cortical thickness-based individualized structural covariance networks in patients with schizophrenia and bipolar disorder. T1-weighted magnetic resonance images were obtained from 39 patients with schizophrenia, 37 patients with bipolar disorder type I, and 32 healthy controls, and cortical thickness was analyzed via a surface-based morphometry analysis. The structural covariance of cortical thickness was calculated at the individual level, and covariance networks were analyzed based on graph theoretical indices: strength, clustering coefficient (CC), path length (PL) and efficiency. At the global level, both patient groups showed decreased strength, CC and efficiency, and increased PL, compared to healthy controls. In bipolar disorder, we found intermediate network measures among the groups. At the nodal level, schizophrenia patients showed decreased CCs in the left suborbital sulcus and the right superior frontal sulcus, compared to bipolar disorder patients. In addition, patient groups showed decreased CCs in the right insular cortex and the left superior occipital gyrus. Global-level network indices, including strength, CCs and efficiency, positively correlated, while PL negatively correlated, with the positive symptoms of the Positive and Negative Syndrome Scale for patients with schizophrenia. The nodal-level CC of the right insular cortex positively correlated with the positive symptoms of schizophrenia, while that of the left superior occipital gyrus positively correlated with the Young Mania Rating Scale scores for bipolar disorder. Altered cortical structural networks were revealed in patients, and particularly, the prefrontal regions were more altered in schizophrenia. Furthermore, altered cortical structural networks in both patient groups correlated with core pathological symptoms, indicating that the insular cortex is more vulnerable in schizophrenia, and the superior occipital gyrus is more vulnerable in bipolar disorder. Our individualized structural covariance network indices might be promising biomarkers for the evaluation of patients with schizophrenia and bipolar disorder.

(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.

Precise and timely evaluation of an individual’s hearing loss plays an important role in determining appropriate treatment strategies, including medication and aural rehabilitation. However, currently available hearing assessment systems do not satisfy the need for an objective assessment tool with a simple and non-invasive procedure. In this paper, we propose a new method for pure-tone audiometry, which may potentially be used to assess an individual’s hearing ability objectively and quantitatively, without need for the user’s active response. The proposed method is based on the auditory oculogyric reflex, where the eyes involuntary rotate towards the source of a sound, in response to spatially moving pure-tone audio stimuli modulated at specific frequencies and intensities. We quantitatively analyzed horizontal electrooculograms (EOG) recorded with a pair of electrodes under two conditions—when pure-tone stimuli were (1) “inaudible” or (2) “audible” to a participant. Preliminary experimental results showed significantly increased EOG amplitude in the audible condition compared to the inaudible condition for all ten healthy participants. This demonstrates potential use of the proposed method as a new non-invasive hearing assessment tool.