A roadmap to navigate the future of neural engineering

Clinical Snapshot

Key Findings

• Effect Size: Not applicable — no empirical effect sizes generated; this is a conceptual roadmap document

• Primary Outcome: Identification of current status, key challenges, and required advances across seven neural engineering domains: brain-machine interfaces, neural modeling, artificial intelligence and machine learning, neural interfaces, neural imaging, augmented rehabilitation, and neuromaterials

• Nnt Or Sensitivity: Not applicable — no clinical trial data or diagnostic accuracy data generated by this paper

• Confidence Interval: Not applicable — no quantitative results with uncertainty estimates

Clinical Application

The roadmap itself is not directly implementable in clinical practice. Its value lies in informing research strategy, funding priorities, and long-term clinical translation planning. Individual technologies discussed (e.g., implantable BMIs, closed-loop neurostimulation) are at varying stages of clinical readiness, from early-phase trials to established therapies. Clinicians should treat this as a horizon-scanning document rather than a practice-change guide. Australia has a growing neural engineering research ecosystem, with relevant activity at institutions including the University of Melbourne (Bionic Vision Australia, Graeme Clark Institute), UNSW Sydney, and the University of Queensland. The TGA regulates implantable neural devices under the therapeutic goods framework, and several neural stimulation devices (e.g., deep brain stimulators, spinal cord stimulators) are already TGA-approved and MBS-listed. The NDIS provides a potential funding pathway for assistive neurotechnology for eligible participants. RACGP and specialist college guidelines do not yet address most emerging neural engineering technologies, reflecting their early translational status. Australian clinicians should monitor TGA horizon-scanning communications and engage with the Medical Services Advisory Committee (MSAC) processes as novel neural engineering technologies approach clinical translation. The paper's coverage of augmented rehabilitation is particularly relevant to Australian allied health and rehabilitation medicine practice. Clinicians and researchers working in neurology, neurosurgery, rehabilitation medicine, biomedical engineering, and related fields who are engaged in or considering adoption of neural engineering technologies for patients with nervous system disorders including spinal cord injury, stroke, epilepsy, Parkinson's disease, and other neurological conditions

Abstract

A group of leaders in neural engineering collaborated to develop a roadmap to navigate the future of neural engineering. We covered a range of themes, including brain machine interfaces, neural modeling, artificial intelligence and machine learning, neural interfaces, neural imaging, augmented rehabilitation, and neuromaterials. For each topic we reviewed the current status, identified current and future challenges, and speculated on the emerging and necessary advances in science and technology to meet these challenges. Neural engineering will continue to yield the approaches and insights that advance the diagnosis and treatment of nervous system disorders, as well as provide new understanding of neural function.

References

1. 1.Grill, W. M., Chestek, C., Wang, Y., Aberra, A. S., Destexhe, A., Chan, R. H. M., Lu, B.-L., Hanein, Y., Robinson, J. T., Whitmire, C., Song, A., Farina, D., Ferris, D. P., Green, R. A., Goding, J., & Asplund, M. (2026). A roadmap to navigate the future of neural engineering. Journal of Neural Engineering. Advance online publication. https://doi.org/10.1088/1741-2552/ae78c2