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The purpose of this paper is to examine the changes of brain functional network after electroconvulsive therapy (ECT) treatment in major depressive disorder (MDD).

In this study, resting electroencephalography (EEG) is used to explore the changes in spectral power density, functional connectivity and network topology elicited by an acute open-label course of ECT in a group of 19 MDD subjects. The brain functional network based on Pearson correlation is constructed in a continuous threshold space (0.38–0.59). Complex network theory is used to analyze the network characteristic such as the length of the characteristic path, clustering coefficient, degree, betweenness centrality, global efficiency and small-world architecture.

The results show that ECT increased the spectral power density of Delta, Theta and Alpha1 bands and the full frequency. ECT increases the functional connectivity in Delta and full frequency and reduces the functional connectivity in Alpha2 band. In the selected threshold space, the clustering coefficient, global efficiency and small-world attributes of the network are changed significantly after ECT.

The findings indicate that resting EEG could effectively characterize the changes of brain functional networks following ECT in MDD. The results provide a theoretical basis to explore the neurophysiological mechanism of ECT in the field of MDD treatment.

Reading represents a basic way by which humans understand the world and acquire knowledge; it is also central to learning and communicating. However, with the rapid development of mobile reading, an individual's cognition of objective facts may be affected by the reading environment and text genre, resulting in limited memorization and understanding of the reading material. Therefore, this study aimed to investigate the influence of the reading environment and text genre on individuals' cognitive activities from the perspective of motivational activation level using evidence from electroencephalography (EEG) signals.

The study employed a mixed design experiment with two reading environments (quiet and distracting) between subjects, two text genres (entertaining and scientific) within subjects and two reading tasks (memory recall and comprehension) within subjects. There were 50 participants in the experiment, and the data obtained from 44 participants while they read the materials and completed the reading tasks were analyzed.

The results showed that readers are more positively motivated to read in a quiet reading environment than in a distracting reading environment when facing the memory recall tasks of entertaining genre passages and comprehension tasks of scientific genre passages. Entertaining genres are more likely to arouse readers' reading interest but hinder the memory recall of the content details. While scientific genres are not easy to understand, they are helpful for working memory.

This study not only applies a new technology to mobile reading research in the field of library science and addresses the limitations of self-report data, but also provides suggestions for the further improvement of mobile reading service providers. Additionally, the results may provide useful information for learners with different learning demands.

An electroencephalography (EEG) examination may cause psychological stress in children with autism that can interfere with the examination results. The objective information on the presence or absence of psycho-emotional stress in patients can help interpret electroencephalograms. This paper aimed to demonstrate the potential of noninvasive objective diagnostics of emotional stress in autistic children undergoing an EEG examination based on analysis of saliva.

This study involved 19 children with autism spectrum disorder (ASD) (ICD-10 F84.0); the mean age was seven years. During EEG examination of the children, behavioral parameters were assessed. The activity of cytochrome P450 reductase (CYPOR) in saliva was measured before and after the EEG procedure using lucigenin-enhanced nicotinamide adenine dinucleotide phosphate-stimulated chemiluminescence assay.

Significant differences in CYPOR activity were found between the children who were distressed during an EEG examination and the children without behavioral disturbances (Mann–Whitney test, p = 0.002). Thus, the EEG examination resulted in an increase in CYPOR activity in saliva cells, which may prove the stressful effect of this procedure on autistic children.

The chemiluminescent indices reflecting the activity of microsomal CYPOR in cells presenting in saliva correlate with the absence or presence of psychological stress in children; this phenomenon can be explained by an increased metabolism of the stress hormone, cortisol, by the cytochrome P450 microsomal system. Furthermore, the proposed method is completely safe, noninvasive, rapid (recording time is 20 min), inexpensive and promising for an objective assessment of psycho-emotional stress in autistic children undergoing medical examinations.

This study aims to investigate the correlation between neural indexes of attention and behavioral indexes of attention and detect the most informative period of brain activity in which the strongest correlation with attentive performance (behavioral index) exists. Finally, to further validate the findings, this paper aims at the prediction of different levels of attention function based on the attention score obtained from repeatable battery for the assessment of neurophysiological status (RBANS).

The present paper analyzes electroencephalogram (EEG) signals recorded by a single prefrontal channel from 105 elderly subjects while they were responding to Stroop color test which is an attention-demanded task. Beside Stroop test, subjects also performed RBANS which provides their level of functionality in different domains including attention. After data acquisition (EEG during Stroop test and RBANS attention score), the authors extract the spectral features of EEG as neural indexes of attention and subjects’ reaction time in response to Stroop test as behavioral index of attention. Then, they explore the correlation between these post-cue frequency band oscillations of EEG with elderly response time (RT). Next, the authors exploit these findings to classify RBANS attention score.

The observations of this study suggest that there is significant negative correlation between alpha gamma ratio (AGR) and RT (p < 0.0001), theta beta ratio (TBR) is positively correlated with subjects’ RT (p < 0.0001), these correlations are stronger in a 500ms period right after triggering the cue (question onset in Stroop test), and 4) TBR and AGR can be effectively used to predict RBANS attention score.

Because of the experiment design, the pre-cue EEG of the next trail was very much overlapped with the post-cue EEG of the current trail. Therefore, the authors could analyze only post-cue EEG. In future study, it would be interesting to investigate the predictability of subject’s future performance from pre-cue EEG and mental preparation.

This study provides an insight into the research on detection of human attention level from EEG instead of conventional neurophysiological tests. It has also potential to be used in implementation of feasible and efficient EEG-based brain computer interface training systems for elderly.

To the best of the authors’ knowledge, this study is among very few attempts for early prediction of cognitive decline in the domain of attention from brain activity (EEG) instead of conventional tests which are prone to human errors.

Suggests that the probability of transmission errors in the central neural system (CNS) is a major factor determining intelligence. That is, the smaller this probability, the larger is the intelligence of the subject. Explains the observation that Hendrickson’s AEP measures, which are supposed to measure this probability, are sometimes correlated positively and sometimes correlated negatively with IQ.

Suggests that the arousability theory of intelligence and personality of Robinson (1996) lacks two important factors: the influence of neural transmission errors and of hemisphericity on intelligence and personality. It is considered that at least two factors contribute to intelligence. The first factor is the potential energetic level of Hebb’s engrams, which may be related to arousability. The second factor is the probability of neural transmission errors. It is suggested that the theory of H.J. Eysenck, that a neural message is sent repeatedly until it is accepted identically a certain number of times, which is smaller for more intelligent subjects, is correct.

This paper aims to propose a new upper limb movement classification with two phases like pre-processing and classification. Investigation of human limb movements is a significant topic in biomedical engineering, particularly for treating patients. Usually, the limb movement is examined by analyzing the signals that occurred by the movements. However, only few attempts were made to explore the correlations among the movements that are recognized by the human brain.

The initial process is the pre-processing that is performed for detecting and removing noisy channels. The artifacts are marked by band-pass filtering that discovers the values below and above thresholds of 200 and –200 µV, correspondingly. It also discovers the trials with unusual joint probabilities, and the trials with unusual kurtosis are also determined using this method. After this, the pre-processed signals are subjected to a classification process, where the neural network (NN) model is used. The model finally classifies six movements like “elbow extension, elbow flexion, forearm pronation, forearm supination, hand open, and hand close,” respectively. To make the classification more accurate, this paper intends to optimize the weights of NN by a new hybrid algorithm known as bypass integrated jaya algorithm (BI-JA) that hybrids the concept of rider optimization algorithm (ROA) and JA. Finally, the performance of the proposed model is proved over other conventional models concerning certain measures like accuracy, sensitivity, specificity, and precision, false positive rate, false negative rate, false discovery rate, F₁-score and Matthews correlation coefficient.

From the analysis, the adopted BI-JA-NN model in terms of accuracy was high at 80th population size was 7.85%, 3.66%, 7.53%, 2.09% and 0.52% better than Levenberg–Marquardt (LM)-NN, firefly (FF)-NN, JA-NN, whale optimization algorithm (WOA)-NN and ROA-NN algorithms. On considering sensitivity, the proposed method was 2%, 0.2%, 5.01%, 0.29% and 0.3% better than LM-NN, FF-NN, JA-NN, WOA-NN and ROA-NN algorithms at 50th population size. Also, the specificity of the implemented BI-JA-NN model at 80th population size was 7.47%, 4%, 7.05%, 2.1% and 0.5% better than LM-NN, FF-NN, JA-NN, WOA-NN and ROA-NN algorithms. Thus, the betterment of the presented scheme was proved.

This paper adopts the latest optimization algorithm called BI-JA to introduce a new upper limb movement classification with two phases like pre-processing and classification. This is the first work that uses BI-JA based optimization for improving the upper limb movement detection using electroencephalography signals.

The purpose of this study is to investigate the effects of the remote training process on distance learning with the application of neurometrics and investigate the features of the training that promote better synchronization between trainers and trainees in terms of cognitive and emotional processes favorable to learning, during a condition of remote professional training.

The authors proposed a hyperscanning paradigm together with a conversational analysis to assess remote online training by collecting neurophysiological measures (frequency band analysis: delta, theta, alpha and beta) via multiple wearable electroencephalograms (EEGs) during a session of remote training.

Results showed increased delta activity in the trainer when he was leading the session and when the participants were exchanging feedback. The delivery of feedback was also linked to increased theta activity compared with the normal activity of the trainees. Finally, synchronization of EEG between trainer and trainee groups was found for the beta band.

This study proposes to adopt a new multi-methodological approach that combines conversational analysis with the detection of remote neurometric parameters, in the field of educational neuroscience applied to organizational contexts.

Findings can help trainers in the development of their skills as trainers and in modeling remote training in organizations.

Findings highlight the crucial role of particular phases of the e-learning process, such as the feedback phase and the interaction trainer group, and they pointed out the relevance of neurophysiological measures to test the e-learning process.

Visual stimulation affects the taste of food and beverages. This study aimed to understand how latte art affects coffee consumption by collecting participants' brainwave data and their taste responses.

Seventy subjects participated in a two-stage experiment. Electroencephalography (EEG) was employed to measure brainwave activity. With an interval of one week, each stage involved coffee consumption with and without latte art. The responses to the taste of the coffee were also collected for analysis.

Significant differences were found in the participants' alpha and beta brainwave bands. When drinking coffee with latte art, the participants' alpha bands were significantly lower, whereas the beta bands were higher. These findings were supported by Bayesian statistics. A significant increase was found in the participants' taste of sweetness and acidity with latte art, and Bayesian statistics confirmed the results for sweetness although the evidence on the increase in acidity was anecdotal. No difference was found in the taste of bitterness.

This study highlights the effect of latte art on coffee consumption. The authors analysed the empirical evidence from this two-stage experimental study in the form of the participants' brainwave data and their responses to taste. This study's original contribution is that it explored the crossmodal effects of latte art on consumers' taste of coffee from a neuroscientific perspective. The results of this study can provide empirical evidence on how to effectively use latte art in practical business environments.

One limitation of research that assesses the effectiveness of physical activity interventions for people with dementia is that most do not describe the intervention in sufficient detail to ascertain a theoretical basis or mechanism of action that determines the effective components. This paper aims to identify studies which evaluate the mechanisms of action of physical activity interventions for people with dementia, to further inform effective intervention development.

Papers were screened for evidence of evaluation of specific forms of physical activity, using pre-defined inclusion criteria. Analysis was conducted to ascertain if mechanisms of action were corroborated by data within and between studies.

The authors identified 26 studies with a measured mechanism of action; these related to the effects of physical activity on either neurological structure or endocrinal markers, including hormones. Physical activity had potential to reduce hippocampal atrophy, increase neural recruitment, activate the noradrenergic system and improve anti-inflammatory responses. While individual studies were hampered by small sample sizes, the body of evidence indicated that physical activity may have potential to delay cognitive decline.

Mechanisms of action in relation to dementia and physical activity are likely to be multifaceted, and physical activity may be protective against progression in the early stages of cognitive decline. Physical activity may be of greatest benefit if incorporated into on-going lifestyle, rather than engaged in for short periods, and combined with social interaction.

This paper is unique in its focus on the mechanisms of action of physical activity interventions for people with dementia.