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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.

Inhibitory control (IC) is a central executive function that shows significant development throughout the preschool years. IC is known as a factor that underlies the ability to self-regulate in daily situations. This ability is challenged when a child faces negative emotions; a challenge that is seen in children’s IC performance and brain activity. This chapter elaborates on the effects that negative emotional experiences have on children’s IC functioning. Moreover, previous studies regarding the way emotional experiences are reflected in brain activity are included. Additionally, this chapter will offer a comprehensive review of the factors affecting individual differences in IC, including the role of children’s temperamental effortful control and negative affectivity. Further, the role of parenting behaviors will be discussed, focusing on the way in which maternal self-regulation influences child inhibitory control, including related educational implications.

This paper explores the possibility of adding user‐oriented class associations to hierarchical library classification schemes. Some highly associated classes not grouped in the same subject hierarchies, yet relevant to users’ knowledge, are automatically obtained by analyzing a two‐year log of book circulation records from a university library in Taiwan. The library uses the Chinese Decimal Classification scheme, which has similar structure and notation to the Dewey Decimal Classification. Methods, from both collaborative filtering and information retrieval research, were employed and their performance compared based on similarity estimation of classes. The results show that classification schemes can, therefore, be made more adaptable to changes of users and the uses of different library collections by analyzing the circulation patterns of similar users. Limitations of the methods and implications for applications are also discussed.

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.

The purpose of this paper is to assess whether or not electroencephalography (EEG) provides a valuable and substantial contribution to the prediction of consumer behaviour and their preferences during product consumption. In this study, the authors especially focus on individual preferences during a wine tasting experience.

A consumer neuroscience experiment was carried out with 26 participants that evaluated different red wines while their brain activity was recorded with EEG. A within-subjects design was employed and the experiment was carried out in two sessions. All participants took part in a blind taste session (no label session), in which information about the wine was not disclosed, and a normal taste session (label session), during which the bottle and its label were visible.

The findings suggest that EEG is a useful tool to study brain activity during product experience. EEG has high temporal resolution, low costs, small dimensions and superior manoeuvrability compared to other consumer neuroscience tools. However, it is noticed that there is a lack of solid theoretical background regarding brain areas (e.g. frontal cortex) and brain activity (e.g. brain waves) related to consumer preferences during product experience. This lack of knowledge causes several difficulties in replicating and validating the findings of other consumer neuroscience experiments for studying consumer behaviour.

The experiment presented in this paper is an exploratory study. It provides insights into the possible contribution of EEG data to the prediction of consumer behaviour during product experience.

This paper aims to investigate the influence of map design characteristics on users’ cognitive load and search performance. Two design conditions (symbolic vs non-symbolic) were used to evaluate users’ ability to locate a place of interest.

A total of 19 students (10 male and 9 female, 20-23 years old) participated in this study. The time required for subjects to find a place in the two conditions was used to estimate their searching performance. An electroencephalogram (EEG) device was used to examine students’ cognitive load using event-related desynchronization percentages of alpha, beta and theta brain wave rhythms.

The results showed that subjects needed more time to find a place in the non-symbolic condition than the symbolic condition. The EEG data, however, revealed that users experienced higher cognitive load when searching for a place in the symbolic condition. The authors found that the design characteristics of the map significantly influenced users’ brain activity, thus impacting their search performance.

Outcomes from this study can be used by cartographic designers and scholars to understand how certain design characteristics can trigger cognitive activity to improve users' searching experience and efficiency.

Neuroarchitecture is a new interdisciplinary research field combining neuroscience and architecture that has developed and expanded since 2000. Neuroarchitecture originated from the divergence of previous multidisciplinary studies on the relationship between humans and the environment. However, scoping reviews of neuroarchitecture in relation to the experience of the built environment are lacking. Thus, this study aimed to provide the background and research trends of neuroarchitecture to contribute to discussions on the built environment.

A general form of scoping review was adopted, following the PRISMA-ScR checklist. For this scoping review emphasizing the embodied implication of neuroarchitecture for the built environment, an evaluation framework was developed consisting of four categories: health, performance, aesthetics and emotion.

This study explores objective techniques, including electroencephalography and functional magnetic resonance imaging, electrocardiogram, electrodermal activity and saliva cortisol, to measure neurophysiological impacts, adopting real, virtual and images of environmental settings. An in-depth review of 25 selected papers revealed the existing empirical research on neuroarchitecture using human physiological measurement tools and representational environment settings to examine the impact of human–environment relationships.

A meta-analysis of theoretical and intervention studies on neuroarchitecture that investigates the multisensory characteristics of the environment is lacking. In addition, the development and application of wearable tools to meet the needs of real environment settings can improve the effectiveness of neurophysiological measurement tools.

To solve problems of low intelligence and poor robustness of traditional navigation systems, the purpose of this paper is to propose a brain-inspired localization method of the unmanned aerial vehicle (UAV).

First, the yaw angle of the UAV is obtained by modeling head direction cells with one-dimension continuous attractor neural network (1 D-CANN) and then inputs into 3D grid cells. After that, the motion information of the UAV is encoded as the firing of 3 D grid cells using 3 D-CANN. Finally, the current position of the UAV can be decoded from the neuron firing through the period-adic method.

Simulation results suggest that continuous yaw and position information can be generated from the conjunctive model of head direction cells and grid cells.

The proposed period-adic cell decoding method can provide a UAV with the 3 D position, which is more intelligent and robust than traditional navigation methods.

This study aims to investigate the neurocognitive status of people with different moods (depressed and non-depressed) both in a typical urban environment (TUE) and in an urban green environment (UGE).

The study was conducted with the participation of 210 individuals in a real environment. Heart rates of the participants were measured together with EEG and eye-tracking measurements while they were walking in a real urban environment (TUE and UGE). The participants were divided into depressed and non-depressed groups according to different moods. Movements within the city based on these two distinctions and different cognitive moods were investigated, together with the effects of the city plan on these people.

As a result, the green urban fabric was found to have a positive effect even on people with depression. Yet, it was found that the non-depressed group also spent more time in a green urban environment.

The study shows that urban planners and designers should assume an important role in the design of green spaces, which have a more intense visual and cognitive impact than structures.