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Brain Sciences
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The Use of the Brain-Computer Interface (BCI) in Applied Neuroscience:...
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The Use of the Brain-Computer Interface (BCI) in Applied Neuroscience: From the Single- to Multi-Brain Approach

A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Behavioral Neuroscience".

Deadline for manuscript submissions: closed (20 October 2023) | Viewed by 4901

Special Issue Editors

Dr. Claudio Lucchiari

E-Mail Website
Guest Editor
Department of Philosophy, University of Milan, 7, 20122 Milan, Italy
Interests: creativity; learning; cognitive flexibility; decision-making; EEG; tDCS; neuro modulation; neurofeedback; emotions; applied cognitive science; multi-brain neuroscience
Special Issues, Collections and Topics in MDPI journals
Dr. Maria Elide Vanutelli

E-Mail Website
Guest Editor
Department of Philosophy, University of Milan, 7, 20122 Milan, Italy
Interests: cognitive science; neuropsychology; brain computer interface; hyperscanning; fNIRS; EEG; emotions; creativity; neuroeconomics; affective neuroscience; social neuroscience

Special Issue Information

Dear Colleagues,

The BCI translates human brain activity into codes that can be used by a computer for many purposes. Traditionally, the BCI has been used to detect brain signals so as to translate intentions into commands for a machine. However, technological advancements have allowed the exploration of other BCI applications, thanks to improved wearability, flexibility and reliability, with high ecological validity. In particular, applied social neuroscience is a fascinating horizon that BCI-based studies have started to explore, moving from individual towards multi-brain applications. Thus, instead of studying one person at a time, more people may be connected to investigate what happens when brains work together. From this perspective, a paradigm called hyperfeedback has been developed as a way to extend BCI neurofeedback studies to multi-perspective neuroscience.

The aim of this Special Issue is to collect basic and applied BCI studies in heterogenous settings, which address single- and multi-brain applications. We aim to collect papers that can together demonstrate the innovative trends in BCI studies.

Papers reporting theoretical models, technical innovations, psychological research and artificial intelligence applications are welcome. Targeted reviews, original studies, clinical research and everyday life applications can be submitted.

Dr. Claudio Lucchiari
Dr. Maria Elide Vanutelli
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Brain Sciences is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • brain–computer interface
  • neurofeedback
  • hyperscanning
  • human–machine interaction
  • hyperfeedback
  • artificial intelligence
  • multi-brain neuroscience
  • psychological states
  • social neuroscience
  • affective neuroscience

Published Papers (2 papers)

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Research

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15 pages, 12328 KiB  
Article
Modulating Individual Alpha Frequency through Short-Term Neurofeedback for Cognitive Enhancement in Healthy Young Adults
by Ben-Zheng Li, Wenya Nan, Sio Hang Pun, Mang I. Vai, Agostinho Rosa and Feng Wan
Brain Sci. 2023, 13(6), 926; https://doi.org/10.3390/brainsci13060926 - 08 Jun 2023
Viewed by 1760
Abstract
Human alpha oscillation (7–13 Hz) has been extensively studied over the years for its connection with cognition. The individual alpha frequency (IAF), defined as the frequency that provides the highest power in the alpha band, shows a positive correlation with cognitive processes. The [...] Read more.
Human alpha oscillation (7–13 Hz) has been extensively studied over the years for its connection with cognition. The individual alpha frequency (IAF), defined as the frequency that provides the highest power in the alpha band, shows a positive correlation with cognitive processes. The modulation of alpha activities has been accomplished through various approaches aimed at improving cognitive performance. However, very few studies focused on the direct modulation of IAF by shifting the peak frequency, and the understanding of IAF modulation remains highly limited. In this study, IAFs of healthy young adults were up-regulated through short-term neurofeedback training using haptic feedback. The results suggest that IAFs have good trainability and are up-regulated, also that IAFs are correlated with the enhanced cognitive performance in mental rotation and n-back tests compared to sham-neurofeedback control. This study demonstrates the feasibility of self-regulating IAF for cognition enhancement and provides potential therapeutic benefits for cognitive-impaired patients. Full article
(This article belongs to the Special Issue The Use of the Brain-Computer Interface (BCI) in Applied Neuroscience: From the Single- to Multi-Brain Approach)
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Review

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15 pages, 5374 KiB  
Review
BCI Applications to Creativity: Review and Future Directions, from little-c to C2
by Maria Elide Vanutelli, Marco Salvadore and Claudio Lucchiari
Brain Sci. 2023, 13(4), 665; https://doi.org/10.3390/brainsci13040665 - 15 Apr 2023
Cited by 2 | Viewed by 1956
Abstract
BCI devices are increasingly being used to create interactive interfaces between users and their own psychophysiological signals. Over the years, these systems have seen strong development as they can enable people with limited mobility to make certain decisions to alter their environment. Additionally, [...] Read more.
BCI devices are increasingly being used to create interactive interfaces between users and their own psychophysiological signals. Over the years, these systems have seen strong development as they can enable people with limited mobility to make certain decisions to alter their environment. Additionally, their portability and ease of use have allowed a field of research to flourish for the study of cognitive and emotional processes in natural settings. The study of creativity, especially little creativity (little-c), is one example, although the results of this cutting-edge research are often poorly systematized. The purpose of the present paper, therefore, was to conduct a scoping review to describe and systematize the various studies that have been conducted on the application potential of BCI to the field of creativity. Twenty-two papers were selected that collect information on different aspects of creativity, including clinical applications; art experience in settings with high ecological validity; BCI for creative content creation, and participants’ engagement. Critical issues and potentialities of this promising area of study are also presented. Implications for future developments towards multi-brain creativity settings and C2 are discussed. Full article
(This article belongs to the Special Issue The Use of the Brain-Computer Interface (BCI) in Applied Neuroscience: From the Single- to Multi-Brain Approach)
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