Computational Intelligence and Brain Plasticity—2nd Edition
A special issue of Brain Sciences (ISSN 2076-3425). This special issue belongs to the section "Computational Neuroscience, Neuroinformatics, and Neurocomputing".
Deadline for manuscript submissions: 25 December 2026
Special Issue Editor
Interests: cognitive neuroscience; machine learning; neuroscience; signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The ability of the nervous system to change its activity in response to intrinsic or extrinsic stimuli and to reorganize its structure, functions, or connections is known as brain plasticity. Plasticity is crucial for recovering cognitive and motor functions after severe injuries, as well as for navigating unfamiliar situations while learning new tasks or skills. Recently, artificial intelligence (AI) and innovative computational methods have provided important tools for a quantitative assessment of brain plasticity. These measures can be used in clinical applications, for example, to assess patient progress during rehabilitation treatments and to develop patient-specific training sessions based on trainees’ performance and brain responses. Important examples of industrial applications include neuroimaging technology, wearable sensors, and advanced data processing. AI-based methodologies are some of the most appropriate tools for discovering the wide range of mechanisms underlying brain plasticity.
Following the success of the first issue of “Computational Intelligence and Brain Plasticity,” we are pleased to announce a second edition and invite contributions from investigators and innovators at the forefront of the field.
This Special Issue includes both methodological and experimental studies aimed at identifying changes in subjects’ brain activation patterns or mental states (e.g., learning, mental workload, stress, attention, mental fatigue, post-stroke, etc.) due to plasticity aspects. Studies on wearable sensors and associated technologies are also encouraged. All types of manuscripts will be taken into consideration, including original basic science reports, translational research, clinical studies, review articles, and methodology papers.
We welcome innovative research in the following fields: neuroscience, neurosurgery, neurorehabilitation, neural networks, and brain neuroplasticity with human–machine interactions at work.
Dr. Gianluca Borghini
Guest Editor
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 250 words) can be sent to the Editorial Office for assessment.
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 process
- cognitive training
- mental state assessment
- cognitive rehabilitation
- high-resolution EEG
- brain connectivity
- cognitive control behaviour
- artificial intelligence
- hyperscanning
- multivariate autoregressive models.
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