Empowering Next Generation Implantable Neural Interfaces

Being able to control devices with our thoughts is a concept that has for long captured the imagination. Neural Interfaces or Brain Machine Interfaces (BMIs) are devices that aim to do precisely this. Next generation devices will be distributed like the brain itself. It is currently estimated that if we were able to record electrical activity simultaneously from between 1,000 and 10,000 neurons, this would enable useful prosthetic control (e.g. of a prosthetic arm). However, rather than relying on a single, highly complex implant and trying to cram more and more channels in this (the current paradigm), the idea here is to develop a simpler, smaller, well-engineered primitive and deploy multiple such devices. It is essential these are each compact, autonomous, calibration-free, and completely wireless. It is envisaged that each device will be mm-scale, and be capable of recording only a few channels (i.e. up to 20), but also perform real-time signal processing. This processing will achieve data reduction so as to wirelessly communicate only useful information, rather than raw data, which can most often be just noise and of no use. Making these underlying devices "simpler" will overcome many of the common challenges that are associated with scaling of neural interfaces, for example, wires breaking, biocompatibility of the packaging, thermal dissipation and yield. By distributing tens to hundreds of these in a "grid" of neural interfaces, many of the desirable features of distributed networks come into play; for example, redundancy and robustness to single component failure. A first tangible application for this platform will see these devices embedded in a uniform array within a flexible substrate for electrocorticography (i.e. recording from the surface of the brain). It will however, also be investigated how the underlying devices can be made applicable to other formats, for instance, in penetrating intracortical devices (recording from within the cortex). Such devices will communicate the neural "control signals" to an external prosthetic device. These can then, for example, be used for: an amputee to control a robotic prosthetic; a paraplegic to control a mobility aid; or an individual with locked in syndrome to communicate with the outside world.

This Fellowship will consolidate expertise and build a core capability that can deliver such devices. This will be achieved by working together with researchers and professionals across multiple disciplines including ICT, engineering, healthcare technologies, medical devices and neuroscience. The research is extremely well aligned with the current quest to understand the brain; for example, US presidential BRAIN initiative, and the EU human brain project. It will impact neuroscience research, by extending current capabilities by at least an order of magnitude, but also medical devices by inventing and demonstrating a radically new approach.

The proposed research will have significant economic, clinical and scientific impact. It will profoundly impact my career, team, department, organisation (Imperial College London), collaborators, and the UK.

In terms of economic impact, a key long-term goal of this research is to develop new technologies to be incorporated into neuroscientific tools and clinical devices such as neural prostheses and Brain-Machine Interfaces (BMIs). Neural devices now constitute a $2 billion/year industry that is predicted to grow twice as fast as the cardiac implant market. The EPSRC has recognised the importance of this area in its initiative 'Developing a Common Vision for UK Research in Microelectronic Design' which describes the interface of electronics to biology and in particular the brain as a Grand Challenge for UK microelectronics. With respect to clinical relevance, the outcomes of this research stand to impact several clinical applications. In the past, treatments for brain disorders have largely been limited to gross psychopharmacological interventions or neurosurgical resections. My proposed research will deliver an autonomous, implantable platform enabling the next-generation of devices also to monitor the activity of large numbers of individual neurons in the brain. This will significantly increase the scope of neuroprosthetic applications. More significantly, a promising future direction for neuroprosthetics will be to combine neural sensing and stimulation in a single device that can operate 'closed-loop' protocols. Such devices have obvious application as artificial connections between areas that might be disconnected by injury (for example between the motor cortex and the spinal cord). The ability to replace or modify specific connections in the nervous system could revolutionise neurological rehabilitation and impact the lives of a considerable patient population. For example, spinal cord injury affects 35,000 individuals in the UK and is particularly prevalent in young adults (the most common age at injury is just 19 years). Over 300,000 stroke survivors living with moderate to severe disabilities in England alone.

This Fellowship will establish a self-sustaining critical mass of researchers at Imperial College around my research vision, enabling us to move from our current status of international recognition within the broad field of implantable neural interface technology to international leadership in the field.

Through the programme I have detailed, this will allow me to build capacity and consolidate capability to allow for chip-scale neural implants to be a reality. While there are several groups working in relevant areas, there is no individual that currently has the expertise, capability, and knowhow to integrate a fully-autonomous chip-scale neural implant. This will put myself, my institution and the UK at the forefront of this field that will have wide-reaching impacts both in the tangibles (i.e. academic, scientific, economic, etc) and the non-tangibles (e.g. esteem) value added.

My team will directly benefit from research outcomes (e.g. experience, publications, exploitation, etc) and the postdoctoral research associates and PhD students will have valuable interdisciplinary training contributing towards the knowledge economy. My collaborators (and their organisations) will also benefit through us working together and the prospect of future research and commercialisation opportunities.

The research will generate a cornerstone in the UK's contribution to the field of neural interfaces. This research work will empower the field with a technological platform far in excess of the international state-of-the-art, generating new research and clinical applications and enabling new commercial opportunities.