Applications of Deep Learning and Generative AI in Neuro-Medicine and Brain-Centric Interfaces

Dear Colleagues,

Advancements in artificial intelligence—particularly deep learning, transformers, and generative AI—are rapidly transforming the landscape of neuro-medicine and brain–computer interfaces (BCI). These technologies now offer powerful tools for interpreting complex neural and behavioral signals across a variety of sensing modalities, such as EEG, fNIRS, MRI, eye-tracking, EMG, and even emerging in-ear EEG devices. This Special Issue aims to bring together high-quality studies that explore the intersection of AI and neuro-medicine and promote novel solutions for cognitive health, neurological disorders, and brain–computer interfacing.

This Special Issue will focus on original research and reviews that explore the use of deep learning and generative AI in applications such as epilepsy detection, stroke prediction and rehabilitation, autism spectrum disorder (ASD) analysis, cognitive workload modeling, neurodevelopmental and neurodegenerative disorder assessments, and real-time or wearable BCI systems. We welcome submissions that apply advanced AI methods to multi-modal neural datasets or that propose innovative frameworks for low-channel EEG prediction, subject-transfer learning, or explainable decision-making in clinical settings.

We are particularly interested in work that includes both methodological innovation and translational relevance, including hybrid architectures, pre-trained vision/language models, LLMs in neuro-diagnostics, and privacy-preserving or real-time inference systems.

In this Special Issue, we welcome original research articles, reviews, and short communications. Research areas may include (but are not limited to) the following themes:

• Brain–computer interfaces and neurofeedback systems;
• Epilepsy and seizure prediction;
• Stroke detection and rehabilitation tracking;
• Autism and neurodevelopmental disorder diagnosis;
• Cognitive state and workload estimation;
• Explainable AI and model interpretability in neuro-medicine;
• Domain adaptation, transfer learning, and few-shot learning for neural signals;
• Low-resource and wearable neuro-sensing technologies.

We look forward to receiving your contributions.

Dr. Adham Atyabi
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 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. AI 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 1600 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.

• deep learning
• brain–computer interface (BCI)
• EEG/fNIRS/MRI
• cognitive workload
• epilepsy detection
• stroke rehabilitation
• autism spectrum disorder
• generative AI
• multimodal neuroimaging
• explainable AI