Brain Plasticity, Cognitive Training and Mental States Assessment: Series II
A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Neuropsychology".
Deadline for manuscript submissions: closed (15 March 2022) | Viewed by 11483
Special Issue Editors
Interests: cognitive neuroscience; machine learning; neuroscience; signal processing
Special Issues, Collections and Topics in MDPI journals
Interests: brain-computer interface; neuroscience; signal-processing; machine learning
Special Issues, Collections and Topics in MDPI journals
Interests: brain networks; hyperscanning; signal-processing
Special Issues, Collections and Topics in MDPI journals
Interests: cognitive neuroscience; behavioural neuroscience; neuropsychology, biosignals processing; brain-computer interface; human-machine interaction; human factor; road safety
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Following the success of the first release, this Special Issue of Brain Sciences titled “Brain Plasticity, Cognitive Training and Mental States Assessment: Series II” aims to collect studies detailing the most recent advancements in the field of brain plasticity and learning research. Authors are invited to submit cutting-edge research and review articles that address a broad range of topics related to the evaluation of the capacity of the brain to change itself under clinical (e.g., patients going through rehab sessions) or working contexts (e.g., users learning new tasks). In this regard, being able to measure such brain capabilities and the related changes would be very useful. For example, the outcomes could be used to better assess the therapist–patient empathy, patients’ learning progress, variations of mental states throughout sessions, or to better tailor the training program on the basis of each patient attitude. In this regard, neuroimaging technology like EEG, fMRI, fNIRS, MEG, wearable sensors, VR, and robotic research appear to be the most appropriate means of gathering such information and directly employing it for the optimization of users and training schedules.
This Special Issue is also dedicated to new methodologies and technologies to infer objective information about brain changes and user mental state variations during training/rehabilitation sessions. Studies that may have a significant translational effect on the field of clinical services and research on technologies to improve or accelerate learning processes are also welcome.
Dr. Gianluca Borghini
Dr. Pietro Aricò
Dr. Alessandra Anzolin
Dr. Gianluca Di Flumeri
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 plasticity
- learning processing
- cognitive training
- mental states assessment
- cognitive rehabilitation
- human interaction
- high-resolution EEG
- machine learning
- brain connectivity
- cognitive control behavior
