AI-Driven Brain–Computer Interfaces: Multimodal Sensing, Imaging, and Multi-Omics
A special issue of Biomimetics (ISSN 2313-7673). This special issue belongs to the section "Biological Optimisation and Management".
Deadline for manuscript submissions: 25 November 2026 | Viewed by 184
Special Issue Editor
2. Institute of Science and Technology for Brain-Inspired Intelligence (ISTBI), Fudan University, Shanghai, China
Interests: neural probes; bioelectronics; brain-machine interface; neural interface; soft materials; additive manufacturing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to invite you to contribute to this Special Issue, “AI-Driven Brain–Computer Interfaces: Multimodal Sensing, Imaging, and Multi-Omics”, which highlights next-generation research investigating brain–machine connectivity at the intersection of biomimetics, neuroengineering, and artificial intelligence (AI). By enabling direct communication between neural activity and digital systems, brain–computer interfaces (BCIs) open new avenues for restoring and increasing function, supporting rehabilitation, and improving quality of life. At the same time, they raise critical challenges in biocompatibility, long-term stability, signal fidelity, adaptive decoding, usability, safety, and ethics.
A particular emphasis of this Special Issue is the growing impact of AI-driven and data-centric paradigms in BCI research and translation. Modern BCIs increasingly rely on machine learning and deep learning for robust decoding, multimodal fusion, personalized adaptation, and real-time closed-loop control under real-world noise, drift, and inter-subject variability. We especially welcome contributions that integrate biomimetic principles with AI-enabled neurotechnology, including neuromorphic/energy-efficient computing, intelligent sensing, and scalable deployment.
In addition, this Special Issue encourages work that connects BCIs with early detection and precision medicine in brain disease, a field where neurotechnology can support risk stratification, monitoring, and intervention optimization. Submissions that incorporate multi-omics, including metabolomics, genomics, transcriptomics, proteomics, and spatial omics, are of particular interest, especially those contributing to revealing mechanisms, improving biomarker discovery, enabling patient stratification, or informing personalized BCI/neuromodulation strategies. Studies combining neurophysiological signals with clinical, imaging, and multi-omics data to build interpretable and clinically actionable models are highly aligned with this Special Issue’s scope.
This multidisciplinary Special Issue aims to foster collaboration among neuroscientists, clinicians, engineers, computer scientists, and technologists. By integrating diverse perspectives, we seek not only to identify key bottlenecks in BCI development but also to advance sustainable, safe, and ethically responsible solutions that accelerate translation from laboratory prototypes to real-world clinical and consumer applications.
This Special Issue welcomes original research articles and reviews. Research areas may include (but are not limited to) the following:
- AI-driven BCI and neural decoding: deep learning, foundation models, self-/weakly supervised learning, domain adaptation, uncertainty estimation, explainability, and privacy-preserving learning.
- Biomimetic and neuromorphic neurotechnology: bio-inspired sensing/actuation, neuromorphic hardware, edge AI, low-power embedded BCI systems, and closed-loop control.
- Implantable and wearable microdevices: materials, packaging, chronic stability, biocompatibility, high-density interfaces, and fully integrated systems for neuroprosthetics.
- Multimodal acquisition and imaging: advanced imaging and sensing (e.g., electrophysiology, optical, ultrasound, and fNIRS/fMRI integration), real-time monitoring, and computational neuroimaging.
- Early detection and monitoring in brain disease: AI-enabled screening/stratification and longitudinal monitoring for neurological disorders, and digital biomarkers and predictive modeling.
- Multi-omics and mechanism-informed BCI/neuromodulation: metabolomics, genomics, transcriptomics, proteomics, spatial omics, biomarker discovery, mechanism-driven stratification and personalized intervention.
We invite researchers from all backgrounds to share their insights and findings in this vital area. Your participation will contribute to advancing the field of BCIs and fostering a collaborative community dedicated to exploring the future possibilities and addressing the scientific, clinical, and societal challenges of brain–machine interfacing.
We look forward to your valuable submissions.
Dr. Shumao Xu
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. Biomimetics 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
- artificial intelligence
- machine learning
- neural interfaces
- brain–machine connectivity
- implantable microdevices
- signal decoding and processing
- neurotechnology
- biomimetics
- brain disease early detection
- metabolomics
- genomics
- transcriptomics
- proteomics
- spatial omics
- biomedical engineering
- interface engineering
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