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
Sivylla Paraskevopoulou (Author)
(2011)
A sub-1_W Neural Spike-Peak Detection and Spike-Count Rate Encoding Circuit
Paraskevopoulou S
(2011)
A sub-1µW neural spike-peak detection and spike-count rate encoding circuit
Bard Haaheim (Co-Author)
(2012)
A Sub-1uW, 16kHz Current-Mode SAR-ADC for Neural Spike Recording
Paraskevopoulou S
(2012)
An ultra-low-power front-end neural interface with automatic gain for uncalibrated monitoring
Williams I
(2013)
An energy-efficient, dynamic voltage scaling neural stimulator for a proprioceptive prosthesis.
in IEEE transactions on biomedical circuits and systems
Williams I
(2013)
Modelling muscle spindle dynamics for a proprioceptive prosthesis.
in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Leene L
(2013)
A compact recording array for neural interfaces
Paraskevopoulou SE
(2013)
Feature extraction using first and second derivative extrema (FSDE) for real-time and hardware-efficient spike sorting.
in Journal of neuroscience methods
Barsakcioglu D
(2013)
Design optimisation of front-end neural interfaces for spike sorting systems
Navajas J
(2014)
Minimum requirements for accurate and efficient real-time on-chip spike sorting.
in Journal of neuroscience methods
Luan S
(2014)
A charge-metering method for voltage-mode neural stimulation.
in Journal of neuroscience methods
Yang Y
(2014)
Computationally efficient feature denoising filter and selection of optimal features for noise insensitive spike sorting.
in Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Luan S
(2014)
Neuromodulation: present and emerging methods.
in Frontiers in neuroengineering
Eftekhar A
(2014)
Ngram-derived pattern recognition for the detection and prediction of epileptic seizures.
in PloS one
Paraskevopoulou SE
(2014)
Hierarchical Adaptive Means (HAM) clustering for hardware-efficient, unsupervised and real-time spike sorting.
in Journal of neuroscience methods
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. There are several labs around the world now using the platform. The underlying intellectual property has been secured, with patents granted in several territories (Europe - EP3100138, US - US10820816B2, Japan - JP6617108B2, China - CN106062669A). |
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 | 07/2014 |
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 | Public |
Country | United Kingdom |
Start | 07/2015 |
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 | Public |
Country | United Kingdom |
Start | 09/2013 |
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 | Public |
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 | Public |
Country | United Kingdom |
Start | 09/2016 |
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 | 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 | ????????? |
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 | CN106062669 |
Protection | Patent granted |
Year Protection Granted | 2016 |
Licensed | No |
Impact | - |
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 neur |
IP Reference | EP3100138 |
Protection | Patent granted |
Year Protection Granted | 2016 |
Licensed | Commercial In Confidence |
Impact | - |
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/ |