Neural interfaces

Research neural interfaces, implantable neurotechnology, neural decoding and closed-loop brain-computer interfaces. Topics include electrode and sensor design, biocompatible materials, high-channel-count recording and stimulation, neurophotonic probes combining optical stimulation with electrophysiology, and adaptive or deep-learning decoders. The appointment includes independent research, teaching and mentoring. Priority review is 15 November 2026.

Neural Interfaces brings together researchers, clinicians, engineers and other stakeholders working on neurotechnology, brain-computer interfaces, neuroprosthetics and neuromodulation. The programme is developed through community proposals and original research abstracts. Its scope spans clinical applications, neuroscience and neural engineering, data and AI, device technology, translation and outcomes, and ethics, policy and workforce questions. The meeting connects foundational research with implementation and adoption of neural technologies. The speaker-proposal deadline was 12 October 2026

…possible roles for quantum physics, neural interfaces, alignment and the philosophical assumptions behind claims about general intelligence.

Graphene could address some challenges which current neural interfaces are facing. For instance, graphene-based field effect transistors (gFETs) can record brain signals at infraslow frequencies while reduced graphene oxide (rGO) microelectrodes display high charge injection enabling focal electrical stimulation. Here, we assessed the potential of different graphene-based electrodes for recording and stimulation in rodents, with functional ultrasound imaging (fUS) to quantify cerebral neural activity as read-out on visual cortex activity. In our first project we investigated how fast and slow

Neural interfaces to peripheral nerves are increasingly employed for basic research, neuroprosthetics, and bioelectronic medicine (‘electroceuticals’). We previously established a pipeline for hybrid electromagnetic-electrophysiology modeling of nerve stimulation on the o2S2PARC platform for collaborative, FAIR, and reproducible computational neurosciences. It leverages histological data to generate a detailed anatomical model of the nerve microstructure and to functionalize it with populations of fiber neuro-dynamics models (myelinated/unmyelinated, statistical distributions of fiber types an