Classification of pleasantness of wind by electroencephalography.

Thermal comfort of humans depends on the surrounding environment and affects their productivity. Several environmental factors, such as air temperature, relative humidity, wind or airflow, and radiation, have considerable influence on the thermal comfort or pleasantness; hence, these are generally controlled by electrical devices. Lately, the development of objective measurement methods for thermal comfort or pleasantness using physiological signals is receiving attention to realize a personalized comfortable environment through the automatic control of electrical devices. In this study, we focused on electroencephalography (EEG) and investigated whether EEG signals contain information related to the pleasantness of ambient airflow reproducing natural wind fluctuations using machine learning methods. In a hot and humid artificial climate chamber, we measured EEG signals while the participants were exposed to airflow at four different velocities. Based on the reported pleasantness levels, we performed within-participant classification from the source activity of the EEG and obtained a classification accuracy higher than the chance level using both linear and nonlinear support vector machine classifiers as well as an artificial neural network. The results of this study showed that EEG is useful in identifying people's transient pleasantness when exposed to wind.

Binary Semantic Classification Using Cortical Activation with Pavlovian-Conditioned Vestibular Responses in Healthy and Locked-In Individuals.

To develop a more reliable brain-computer interface (BCI) for patients in the completely locked-in state (CLIS), here we propose a Pavlovian conditioning paradigm using galvanic vestibular stimulation (GVS), which can induce a strong sensation of equilibrium distortion in individuals. We hypothesized that associating two different sensations caused by two-directional GVS with the thoughts of "yes" and "no" by individuals would enable us to emphasize the differences in brain activity associated with the thoughts of yes and no and hence help us better distinguish the two from electroencephalography (EEG). We tested this hypothesis with 11 healthy and 1 CLIS participant. Our results showed that, first, conditioning of GVS with the thoughts of yes and no is possible. And second, the classification of whether an individual is thinking "yes" or "no" is significantly improved after the conditioning, even in the absence of subsequent GVS stimulations. We observed average classification accuracy of 73.0% over 11 healthy individuals and 85.3% with the CLIS patient. These results suggest the establishment of GVS-based Pavlovian conditioning and its usability as a noninvasive BCI.

Electroencephalography of completely locked-in state patients with amyotrophic lateral sclerosis.

Patients in completely locked-in state (CLIS) due to amyotrophic lateral sclerosis (ALS) lose the control of each and every muscle of their body rendering them motionless and without any means of communication. Though some studies have attempted to develop brain-computer interface (BCI)-based communication methods with CLIS patients, little information is available of the neuroelectric brain activity of CLIS patients. However, because of the difficulties with and often loss of communication, the neuroelectric signature may provide some indications of the state of consciousness in these patients. We recorded electroencephalography (EEG) signals from 10 CLIS patients during resting state and compared their power spectral densities with those of healthy participants in fronto-central, central, and centro-parietal channels. The results showed significant power reduction in the high alpha, beta, and gamma bands in CLIS patients, indicating the dominance of slower EEG frequencies in their oscillatory activity. This is the first study showing group-level EEG change of CLIS patients, though the reason for the observed EEG change cannot be concluded without any reliable communication methods with this population.

Independent Components of EEG Activity Correlating with Emotional State.

Among brain-computer interface studies, electroencephalography (EEG)-based emotion recognition is receiving attention and some studies have performed regression analyses to recognize small-scale emotional changes; however, effective brain regions in emotion regression analyses have not been identified yet. Accordingly, this study sought to identify neural activities correlating with emotional states in the source space. We employed independent component analysis, followed by a source localization method, to obtain distinct neural activities from EEG signals. After the identification of seven independent component (IC) clusters in a k-means clustering analysis, group-level regression analyses using frequency band power of the ICs were performed based on Russell's valence-arousal model. As a result, in the regression of the valence level, an IC cluster located in the cuneus predicted both high- and low-valence states and two other IC clusters located in the left precentral gyrus and the precuneus predicted the low-valence state. In the regression of the arousal level, the IC cluster located in the cuneus predicted both high- and low-arousal states and two posterior IC clusters located in the cingulate gyrus and the precuneus predicted the high-arousal state. In this proof-of-concept study, we revealed neural activities correlating with specific emotional states across participants, despite individual differences in emotional processing.

Nitrogen-Bridged Metallodiazaporphyrin Dimers: Synergistic Effects of Nitrogen Bridges and meso-Nitrogen Atoms on Structure and Properties.

NH-bridged and pyrazine-fused metallodiazaporphyrin dimers have been prepared from nickel(II) and copper(II) complexes of 3-amino-5,15-diazaporphyrin by Pd-catalyzed C-N cross-coupling and oxidative dimerization reactions, respectively. The synergistic effects of the nitrogen bridges and meso-nitrogen atoms play major roles in enhancing the light-harvesting properties and delocalization of an electron spin over the entire π-skeletons of the metallodiazaporphyrin dimers.

Optical, electrochemical, and magnetic properties of pyrrole- and thiophene-bridged 5,15-diazaporphyrin dimers.

The first examples of pyrrole- and thiophene-bridged 5,15-diazaporphyrin (DAP) dimers are prepared through Stille coupling reactions of nickel(II) and copper(II) complexes of 3-bromo-10,20-dimesityl-5,15-diazaporphyrin (mesityl=2,4,6-trimethylphenyl) with the respective 2,5-bis(tributylstannyl)heteroles. The effects of the heterole spacers and meso nitrogen atoms on the optical, electrochemical, and magnetic properties of the DAP dimers are investigated by UV/Vis absorption spectroscopy, density functional theory calculations, magnetic circular dichroism spectroscopy, cyclic voltammetry, and EPR spectroscopy. The heterole spacers are found to have a significant impact on the electronic transitions over the entire π-system. In particular, the pyrrole-bridged DAP dimers exhibit high light-harvesting potential in the low-energy visible/near-infrared region owing to the intrinsic charge-transfer character of the lowest excitation.