Ultra Low Power Implantable Platform for Next Generation Neural Interfaces

Lead Research Organisation: Imperial College London
Department Name: Institute of Biomedical Engineering

Abstract

For over half a century scientists have recorded the tiny electrical potentials generated by neurons in the brains of awake animals performing specific behaviours, using large racks of power-hungry equipment. These experiments have yielded profound insights into how sensory information is represented and transformed by the brain into the signals that control purposeful movements, as well as revealing how this complex system is affected by neurological injuries and disease. However, until recently the therapeutic avenues available to neurologists have been limited to gross interventions such as systemic drug applications and neurosurgical lesions.In recent years, small electronic devices have been developed that deliver specific patterns of stimulation via small electrodes implanted in the nervous system. Devices such as Deep Brain Stimulators and Cochlear Implants have helped many thousands of patients worldwide. The next generation of neural implants will use similar electrodes to detect the activity of neurons, paving the way for new treatments for conditions that currently weigh a heavy clinical burden. For example, by using the activity of neurons in motor areas of the brain to control electrical stimulation of muscles, it is possible that voluntary movements could be restored to patients paralysed by spinal cord injuries. However, despite considerable advances in electrode technologies, our ability to interface digital microelectronics with the brain at the level of individual neurons is at present severely limited. Each electrode detects the signal from multiple cells in its vicinity, and the small, brief 'spike' events they generate can be hard to distinguish beneath the background noise.To solve this problem we have assembled a cross-disciplinary team with expertise in three key areas: the computational algorithms required to detect and sort spike events, low power integrated electronics to perform real-time, reliable spike identification, and the techniques to record long-term activity from the brain using neural implants in order to evaluate real-world performance. The aim is to deliver a platform technology that will convert the raw signal from electrodes into a stream of identified spike events suitable for subsequent processing by conventional digital microelectronics, and be suitable for incorporation into a range of wireless, implantable devices. The availability of such a technology would revolutionise the development of devices to treat a wide variety of nervous system disorders.

Planned Impact

The proposed research will have significant economic, clinical and scientific impact. It will be also of large relevance for the participating organizations. 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. Our 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. The participating organisations (University of Leicester, Imperial College London and Newcastle University) and the project teams will be a significant beneficiary of the proposed research. The project teams will directly benefit from research outcomes through experience gained, papers published and also the availability of new technologies which can filter in to their other research activities. The post-doctoral research associates and PhD students will have valuable interdisciplinary training contributing towards the knowledge economy. This research will generate a stepping stone in the UK's contribution to the field of neural interfaces. The successful completion of this work will make available a technological platform far in excess of the international state-of-the-art. The topic of this proposal is at the forefront of science, as shown by the large number of high profile papers published in this area in the last years, some of them by the investigators of this proposal, and massive media attention. We are therefore confident that results arising from this project will have a large scientific impact leading to high profile journal publications, keynote and public lectures, and media attention.

Publications

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Barsakcioglu DY (2014) An analogue front-end model for developing neural spike sorting systems. in IEEE transactions on biomedical circuits and systems

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Liu Y (2018) Event-driven processing for hardware-efficient neural spike sorting. in Journal of neural engineering

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Liu Y (2017) A 64-Channel Versatile Neural Recording SoC With Activity-Dependent Data Throughput. in IEEE transactions on biomedical circuits and systems

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Luan S (2014) A charge-metering method for voltage-mode neural stimulation. in Journal of neuroscience methods

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Luan S (2014) Neuromodulation: present and emerging methods. in Frontiers in neuroengineering

 
Description For over half a century scientists have recorded the tiny electrical potentials generated by neurons in the brains of awake animals performing specific behaviours, using large racks of power-hungry equipment. These experiments have yielded profound insights into how sensory information is represented and transformed by the brain into the signals that control purposeful movements, as well as revealing how this complex system is affected by neurological injuries and disease. However, until recently the therapeutic avenues available to neurologists have been limited to gross interventions such as systemic drug applications and neurosurgical lesions. In recent years, small electronic devices have been developed that deliver specific patterns of stimulation via small electrodes implanted in the nervous system. Devices such as Deep Brain Stimulators and Cochlear Implants have helped many thousands of patients worldwide. The next generation of neural implants will use similar electrodes to detect the activity of neurons, paving the way for new treatments for conditions that currently weigh a heavy clinical burden. For example, by using the activity of neurons in motor areas of the brain to control electrical stimulation of muscles, it is possible that voluntary movements could be restored to patients paralysed by spinal cord injuries. However, despite considerable advances in electrode technologies, our ability to interface digital microelectronics with the brain at the level of individual neurons is at present severely limited. Each electrode detects the signal from multiple cells in its vicinity, and the small, brief 'spike' events they generate can be hard to distinguish beneath the background noise.

This research has developed a platform technology that converts the raw signal observed at the electrodes into a stream of identified spike events suitable for subsequent processing by conventional digital microelectronics. This means that neural activity can be used to directly control (in real time) an external device. This could in the future, for example, be used in a brain machine interface to control a prosthetic arm via thought.

Specific project outcomes include:

- Investigating the effect of front-end electronics on spike sorting performance (classification accuracy) and determining the different component parameter sensitivities.

- Optimizing spike sorting parameters to achieve good computational efficiency (minimizing complexity whilst maintaining good accuracy).

- Prototyping several novel integrated devices, circuits and systems for neural recording and real-time, hardware efficient spike processing (spike detection, feature extraction and classification) and power management.

- Developing a standalone, bespoke integrated platform for facilitating spike streaming (i.e. interfacing to electrodes and recording neural spikes together with real time spike detection, feature extraction, clustering).

- Securing the background intellectual property to this invention.


All the project outcomes listed above have/are in process of been disseminated in peer reviewed publications (available open access via our institutional library portal).

Ongoing and future research will concentrate on further optimizing the platform that have already been developed for a wider deployment in neuroscience laboratories.
Exploitation Route We are currently in the process of licensing our technology to commercial partners such that our research outcomes can directly benefit the community.
Sectors Digital/Communication/Information Technologies (including Software),Electronics,Healthcare,Manufacturing, including Industrial Biotechology,Pharmaceuticals and Medical Biotechnology,Other

URL http://www.imperial.ac.uk/next-generation-neural-interfaces/projects/ngni/
 
Description Research outcomes have been disseminated through journal publication, at a number of conferences, workshops, etc. Any results will be useful to the wider community (biomedical circuits and systems, neurotechnology) to develop next generation neural interfaces. The specific platform that has been developed is currently been optimized and targeted towards a wider deployment as a neuroscience research tool. The underlying intellectual property is in process of being secured (via patent protection) and then we'd seek to license to industry for commercialisation. I have additionally recently been awarded further EPSRC IAA funding to investigate feasibility of developing some of the project outcomes into a product.
First Year Of Impact 2014
Sector Digital/Communication/Information Technologies (including Software),Electronics,Pharmaceuticals and Medical Biotechnology,Other
Impact Types Economic

 
Description "CANDO: Controlling Abnormal Network Dynamics with Optogenetics" (Innovative Engineering for Health)
Amount £1,328,437 (GBP)
Funding ID WT 140515 
Organisation Wellcome Trust 
Sector Charity/Non Profit
Country United Kingdom
Start 08/2014 
End 08/2021
 
Description "ENGINI: Empowering Next Generation Implantable Neural Interfaces" (Early Career Fellowship)
Amount £1,016,559 (GBP)
Funding ID EP/M020975/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Academic/University
Country United Kingdom
Start 08/2015 
End 07/2020
 
Description "iPROBE: in-vivo Platform for the Real-time Observation of Brain Extracellular activity" (Responsive Mode)
Amount £367,521 (GBP)
Funding ID EP/K015060/1 
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Academic/University
Country United Kingdom
Start 10/2013 
End 09/2016
 
Description Application Specific ICs for Neural Interfacing - Commercialisation and Market Evaluation
Amount £60,786 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Academic/University
Country United Kingdom
Start 01/2018 
End 06/2019
 
Description Impact Accelerator Award for "Spike Streaming Platform: Community Engagement & Early-Stage Commercialization"
Amount £44,219 (GBP)
Organisation Engineering and Physical Sciences Research Council (EPSRC) 
Sector Academic/University
Country United Kingdom
Start 10/2016 
End 03/2017
 
Title Methods for computationally-efficient spike sorting (for hardware implementation) 
Description Have developed a number of methods for neural spike processing including feature extraction and classification, adaptive spike detection, template building/training and spike denoising. Also proposed new hardware architectures for implementing online, realtime spike sorting. 
Type Of Material Data analysis technique 
Year Produced 2013 
Provided To Others? Yes  
Impact Other researchers around the world are using/applying our methods to their data. 
 
Description CANDO (Newcastle/UCL) 
Organisation Newcastle University
Country United Kingdom 
Sector Academic/University 
PI Contribution New £10m collaborative research project has been a direct result of collaboration on this grant.
Collaborator Contribution See above.
Impact Multidisciplinary - engineering (electronic, materials, microfabrication), neuroscience, medical regulatory, neurology, biosciences
Start Year 2010
 
Description CANDO (Newcastle/UCL) 
Organisation University College London
Department Department of Medical Physics and Biomedical Engineering
Country United Kingdom 
Sector Academic/University 
PI Contribution New £10m collaborative research project has been a direct result of collaboration on this grant.
Collaborator Contribution See above.
Impact Multidisciplinary - engineering (electronic, materials, microfabrication), neuroscience, medical regulatory, neurology, biosciences
Start Year 2010
 
Description ENGINI (UCL, GeorgiaTech, MSU, Newcastle) 
Organisation Georgia Institute of Technology
Country United States 
Sector Academic/University 
PI Contribution Developing a holistic methodology for the design, manufacture and test of mm-scale neural implants.
Collaborator Contribution UCL - micropackaging Newcastle University - experimental neuroscience Michigan State University - neural signal processing Georgia Institute of Technology - wireless/biotelemetry
Impact N/A
Start Year 2015
 
Description ENGINI (UCL, GeorgiaTech, MSU, Newcastle) 
Organisation Michigan State University
Country United States 
Sector Academic/University 
PI Contribution Developing a holistic methodology for the design, manufacture and test of mm-scale neural implants.
Collaborator Contribution UCL - micropackaging Newcastle University - experimental neuroscience Michigan State University - neural signal processing Georgia Institute of Technology - wireless/biotelemetry
Impact N/A
Start Year 2015
 
Description ENGINI (UCL, GeorgiaTech, MSU, Newcastle) 
Organisation Newcastle University
Department Institute of Neuroscience
Country United Kingdom 
Sector Academic/University 
PI Contribution Developing a holistic methodology for the design, manufacture and test of mm-scale neural implants.
Collaborator Contribution UCL - micropackaging Newcastle University - experimental neuroscience Michigan State University - neural signal processing Georgia Institute of Technology - wireless/biotelemetry
Impact N/A
Start Year 2015
 
Description ENGINI (UCL, GeorgiaTech, MSU, Newcastle) 
Organisation University College London
Department Department of Medical Physics and Biomedical Engineering
Country United Kingdom 
Sector Academic/University 
PI Contribution Developing a holistic methodology for the design, manufacture and test of mm-scale neural implants.
Collaborator Contribution UCL - micropackaging Newcastle University - experimental neuroscience Michigan State University - neural signal processing Georgia Institute of Technology - wireless/biotelemetry
Impact N/A
Start Year 2015
 
Description NGNI (Newcastle/Leicester) 
Organisation Newcastle University
Department Institute of Neuroscience
Country United Kingdom 
Sector Academic/University 
PI Contribution Integrated circuit design, hardware implementation, software development, system integration/overall system concept
Collaborator Contribution Newcastle - Experimental Neuroscience/Hardware test/Overall system concept Leicester - Algorithms for Spike Sorting/WaveClus/Software development/Overall system concept
Impact N/A
Start Year 2010
 
Description NGNI (Newcastle/Leicester) 
Organisation University of Leicester
Department Centre for Systems Neuroscience
Country United Kingdom 
Sector Academic/University 
PI Contribution Integrated circuit design, hardware implementation, software development, system integration/overall system concept
Collaborator Contribution Newcastle - Experimental Neuroscience/Hardware test/Overall system concept Leicester - Algorithms for Spike Sorting/WaveClus/Software development/Overall system concept
Impact N/A
Start Year 2010
 
Description NGNI Oxford 
Organisation University of Oxford
Department Institute of Biomedical Engineering
Country United Kingdom 
Sector Academic/University 
PI Contribution Making technology available to the community.
Collaborator Contribution co-funding manufacture of further devices.
Impact Too early.
Start Year 2018
 
Description iProbe (MSU - Spike Sorting) 
Organisation Michigan State University
Country United States 
Sector Academic/University 
PI Contribution Sharing methods we have developed- co-supervising students.
Collaborator Contribution Applying their expertise to further develop new methods.
Impact Research publication - "Computationally efficient feature denoising filter and selection of optimal features for noise insensitive spike sorting", IEEE EMBC 2014.
Start Year 2013
 
Title System for a brain-computer interface 
Description The invention provides a two-step approach to providing a BCI system. In a first step the invention provides a low-power implantable platform for amplifying and filtering the extracellular recording, performing analogue to digital conversion (ADC) and detecting action potentials in real-time, which is connected to a remote device capable of performing the processor-intensive tasks of feature extraction and spike classification, thus generating a plurality of predetermined templates for each neuron to be used in a second processing step. In the second step the low-power implantable platform amplifies and filters the extracellular recording, performs ADC and detects action potentials, which can be matched on-chip to the predetermined templates generated by the external receiver in the first step. This two-step approach exploits the advantages of both offline and online processing, providing an effective and safe method for performing multiple recordings of single-neuron activity, for research or monitoring applications or for control of a remote device. 
IP Reference GB1401613.3 
Protection Patent application published
Year Protection Granted
Licensed No
Impact N/A
 
Title NGNI Hardware Spike Sorting Platform 
Description Spike Sorting is the process of deinterleaving a recorded neural signal in order to determine the firing patterns of individual neurons from the aggregate spike stream. The NGNI platform is an end-to-end solution for on-node, real-time spike sorting. By using a compact, onboard (template based) spike sorting engine, together with offline training (WaveClus-based), a low power real-time solution is achievable. 
Type Of Technology Systems, Materials & Instrumental Engineering 
Year Produced 2017 
Impact N/A 
URL http://www.imperial.ac.uk/next-generation-neural-interfaces/resources/spike-sorting-platform/
 
Description "Neural Interfaces & Microsystems: from State-of-the-Art to the Next Generation", CNRS Workshop on Bioelectronics (Paris, France), 20 June 2016 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Invited speaker at workshop in the CNRS headquarters in Paris, France on Bioelectronics. I gave a talk to an audience of approximately 100 professionals.
Year(s) Of Engagement Activity 2016
URL http://www.cnrs.fr/insis/recherche/evenements/workshop-electronique-vivant.htm
 
Description COSMOS magazine article 
Form Of Engagement Activity A magazine, newsletter or online publication
Part Of Official Scheme? Yes
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact Not known - external visibility for sure. have had several members of public contacting me after this.

see above
Year(s) Of Engagement Activity 2012
URL https://cosmosmagazine.com/
 
Description Participation in eFutures event 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? Yes
Geographic Reach National
Primary Audience Other academic audiences (collaborators, peers etc.)
Results and Impact Talk increased awareness about my research in other communities (UK microelectronics community)

Regularly invited to participate in more such events.
Year(s) Of Engagement Activity 2013
URL http://efutures.ac.uk/
 
Description School visit (Westminster School) 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Schools
Results and Impact Talk sparked several questions and generally caught the imagination of the 6th form students.

Increased interest from A-Level students in our research - directly contacting our Centre for work-experience, etc.
Year(s) Of Engagement Activity 2011
 
Description Science Museum Festival "You have been Upgraded" 
Form Of Engagement Activity Participation in an activity, workshop or similar
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Public/other audiences
Results and Impact Science Museum Festival "You have been upgraded" on the topic of human enhancement in 25-29 March 2015. Researchers from the Centre for Bio-Inspired Technology (Ian Williams, Deren Barsakcioglu, Benjamin Evans, Nora Gaspar, Konstantin Nikolic, Timothy Constandinou) hosted the section on "implantable devices".
Year(s) Of Engagement Activity 2015
URL http://www.sciencemuseum.org.uk/visitmuseum/plan_your_visit/events/festivals/you-have-been-upgraded
 
Description Talk at Sutton Trust Summer School (6th form students with interest in EEE) entitled: \Microchips and Brain Implants", 4 August 2016. 
Form Of Engagement Activity Participation in an open day or visit at my research institution
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Schools
Results and Impact 12 students enrolled on the "Sutton Trust" scheme attended a week long event at Imperial College EEE Department which involved various activities such as talks, lab sessions, tours, etc- which I gave a talk entitles "Microchips and Brain Implants".
Year(s) Of Engagement Activity 2016
URL http://www.suttontrust.com/programmes/summer-schools/