Towards neuromorphic neurotechnologies: integrating brain-inspired computing with brain-computer interfaces
Neurological disorders pose a growing global health burden, motivating advances in neural interfacing and artificial intelligence (AI). This review surveys state-of-the-art approaches for neural recording, stimulation and signal decoding and encoding across brain-computer interfaces, neuroprosthetics, and neuromodulation systems aimed at restoring function and treating neurological disorders. It highlights recent progress in AI, particularly neuromorphic computing and spiking neural networks (SNNs), and introduces Brain-Inspired Brain-Computer Interfaces (BI-BCIs) as a unifying framework for low-power, closed-loop, and miniaturized neuromorphic neurotechnologies.
Authors
- Michela Chiappalone (ORCID: https://orcid.org/0000-0003-1427-5147)
- Margherita Ronchini (ORCID: https://orcid.org/0000-0003-3261-9644)
- Hooman Farkhani (ORCID: https://orcid.org/0000-0002-8632-2240)
- Hoda Fares (ORCID: https://orcid.org/0000-0003-0460-7611)
- Milad Zamani (ORCID: https://orcid.org/0000-0002-8718-7095)
- Farshad Moradi
- Emre Neftci
Institutions
- Forschungszentrum Jülich (DE)
- University of Southern Denmark (DK)
- Aarhus University (DK)
- University of Genoa (IT)
- RWTH Aachen University (DE)
- Stanford University (US)
Publication Details
- Journal
- npj Biomedical Innovations.
- Published
- 2026-08-20
- DOI
- https://doi.org/10.1038/s44385-026-00074-w
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- European Commission
- Lundbeckfonden
- H. Lundbeck A/S