Brain dynamic during landmark-based learning spatial navigation

In the current study, I investigated both human behavior and brain dynamics during spatial navigation to gain a better understanding of human navigational strategies and brain signals that underlie spatial cognition. To this end, a custom-built virtual reality task and a 64-channel scalp electroencephalogram (EEG) were utilized to study participants. At the first step, we presented a novel, straightforward, yet powerful tool to evaluate individual differences during navigation, comprising of a virtual radial-arm maze inspired to the animal experiments. The virtual maze is designed and furnished, similar to an art gallery, to provide a more realistic and exciting environment for subjects’ exploration. We investigated whether a different set of instructions (explicit or implicit) affects subjects’ navigational performance, and we assessed the effect of the set of instructions on exploration strategies during both place learning and recall. We tested 42 subjects and evaluated their way-finding ability. Individual differences were assessed through the analysis of the navigational paths, which permitted the isolation and definition of a few strategies adopted by both subjects who adopted a more explicit strategy, based on explicit instructions, and an implicit strategy, based on implicit instructions. The second step aimed to explore brain dynamics and neurophysiological activity during spatial navigation. More specifically, we aimed to figure out how navigational related brain regions are connected and how their interactions and electrical activity vary according to different navigational tasks and environment. This experiment was divided into two steps: learning phase and test phase. The same virtual maze (art gallery) as the behavioral part of the study was used so that subjects to perform landmark-based navigation. The main task of the experiment was finding and memorizing the position of some goals within the environment during the learning phase and retrieving the spatial information of the goals during the test phase. We recorded EEG signals of 20 subjects during the experiment, and both scalp-level and source-level analysis approaches were employed to figure out how the brain represents the spatial location of landmarks and targets and, more precisely, how different brain regions contribute to spatial orientation and landmark-based learning during navigation

User-Centred BCI Videogame Design

International audienceThis chapter aims to offer a user-centred methodological framework to guide the design and evaluation of Brain-Computer Interface videogames. This framework is based on the contributions of ergonomics to ensure these games are well suited for their users (i.e., players). It provides methods, criteria and metrics to complete the different phases required by ae human-centred design process. This aims to understand the context of use, specify the user needs and evaluate the solutions in order to define design choices. Several ergonomic methods (e.g., interviews, longitudinal studies, user based testing), objective metrics (e.g., task success, number of errors) and subjective metrics (e.g., mark assigned to an item) are suggested to define and measure the usefulness, usability, acceptability, hedonic qualities, appealingness, emotions related to user experience, immersion and presence to be respected. The benefits and contributions of the user centred framework for the ergonomic design of these Brain-Computer Interface Videogames are discussed

BCI Integration: Application Interfaces

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Chapter BCI Integration: Application Interfaces

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How Visual Stimuli Evoked P300 is Transforming the Brain–Computer Interface Landscape: A PRISMA Compliant Systematic Review

Non-invasive Visual Stimuli evoked-EEGbased P300 BCIs have gained immense attention in recent years due to their ability to help patients with disability using BCI-controlled assistive devices and applications. In addition to the medical field, P300 BCI has applications in entertainment, robotics, and education. The current article systematically reviews 147 articles that were published between 2006-2021*. Articles that pass the pre-defined criteria are included in the study. Further, classification based on their primary focus, including article orientation, participants’ age groups, tasks given, databases, the EEG devices used in the studies, classification models, and application domain, is performed. The application-based classification considers a vast horizon, including medical assessment, assistance, diagnosis, applications, robotics, entertainment, etc. The analysis highlights an increasing potential for P300 detection using visual stimuli as a prominent and legitimate research area and demonstrates a significant growth in the research interest in the field of BCI spellers utilizing P300. This expansion was largely driven by the spread of wireless EEG devices, advances in computational intelligence methods, machine learning, neural networks and deep learning

A Cooperative Game Using the P300 EEG-Based Brain-Computer Interface

In this paper, we present a cooperative game, Brainio Bros 300, using a brain-computer interface (BCI). The game is cooperatively controlled by two people using P300-generating color discrimination. The two users advance through the game together, one as the “player” and the other as the “supporter” providing assistance. We assumed that players would be able-bodied, while supporters would include people with severe disabilities. Through experiments using human subjects, we evaluated the subjects’ impressions of the game and its usefulness. The results of the impression evaluation showed that the subjects generally had good impressions, and there were many opinions that such cooperative games are interesting. We also discuss the possibilities of using the P300 BCI