Joel Lecture Series | Fast neural Electrical Impedance Tomography

You are warmly invited to join us for our annual Joel Lecture. This year, we will be celebrating the career and research of Professor David Holder:

• 17:30 - 17:40: Introduction by Professor Robert Speller
• 17:40 - 18:30: Joel Lecture by Professor David Holder
• 18:30 - 18:35: Closing remarks by Professor Peter Munro
• 18:35 - 20:00: Evening reception

Abstract

Neural Engineering – the discipline of using modern electronics to image and then modulate the human nervous system has become topical with widespread publicity for projects such as Elon Musk’s Neuralink. Unfortunately, the brain has many billions of neurones, each with thousands of synaptic connections, and functions with millisecond-scale graded depolarisation; there are substantial limitations in sampling this adequately, even with advanced modern electronic and imaging approaches. In the 1990s, I set out to add to this technology by developing an imaging technique able to image fast electrical activity in the brain or nerve over milliseconds but at a mesoscopic scale of mm in the rat or several mm in the human brain. The hope was that we could enable quantitative imaging of fast electrical envelope function in the few score of major functional circuits in the brain or traffic in the internal fascicle channels in the peripheral nerve. If possible, this would provide data to refine models of such activity generated in computational neuroscience. The technique was EIT (Electrical Impedance Tomography). This was a new imaging technique which enables tomographic images of the electrical properties of a subject to be produced with arrays of external electrodes. A small, safe, insensible electrical current at a few kHz is applied, usually serially, to pairs of electrodes. Images are reconstructed from the many transfer impedances recorded by measuring resulting voltages at other electrodes. It was initially mainly employed for imaging lung ventilation in the thorax over seconds. However, it had the unique potential to produce tomographic images of the small impedance decreases of ~1% which occur in the brain over milliseconds as ion channels open during neuronal depolarisation.

We aimed to produce a non-invasive system with scalp electrodes able to image fast neural activity in the human brain in real time with a resolution of ~5mm over milliseconds. Unfortunately, this proved to be technically demanding as the signal-to-noise is limited by a small local impedance change in the brain and obstruction of applied current by the resistive skull. We were able to show proof of principle but with restrictions. The approach with electrodes alone requires invasive electrode arrays placed surgically on the brain or around the peripheral nerve. It also needs averaging to a repeated stimulus – such as a flashing visual pattern or rat whisker movement - over a few minutes. However, this still has unique advantages: fnEIT can produce images of neural activity anywhere in rat cerebral cortex or internally in pig vagus nerve with a resolution of 200µm and 2 msec. This could have significant advantages over current methods. In medicine, this could be in imaging epileptic seizures in patients being considered for surgery or improving treatment of epilepsy, depression or immune conditions like rheumatoid arthritis by selective vagal nerve stimulation. It could also be used in cognitive neuroscience in animals.  Our group's current goal is to translate the existing techniques to human clinical use in pilot studies or animal neuroscience. Work is in progress to realise the original vision or real-time scalp imaging with technical advances such as use of FDM (frequency division multiplexing, speeding up recording with use of many simultaneous frequencies) and quantum physics by recording with atomic magnetometers.

Live Streaming

This will be an in-person event and open to the public, if you are unable to attend the UCL campus, please register for the online stream via Zoom.

Register to attend online

Meet the Expert 

Prof David Holder, Professor of Biophysics and Clinical Neurophysiology 

David Holder holds joint qualifications in Clinical Medicine and Biophysics from Corpus Christi College, Cambridge, University College London, and the University of California, Berkeley. He is currently Professor of Biophysics and Clinical Neurophysiology in the Department of Medical Physics and Biomedical Engineering at UCL.

Since 1991, Professor Holder has led a pioneering interdisciplinary research group focused on the development and application of Electrical Impedance Tomography (EIT) for imaging brain and nerve function and pathology. Alongside his academic work, he maintains a clinical practice in neurophysiology—including EEG and EMG—at University College London Hospital (UCLH), now integrated with the National Hospital for Neurology and Neurosurgery at Queen Square. He also serves as a consultant at the Mayo Clinic, London.

Professor Holder chaired the International Steering Committee on Biomedical Electrical Impedance Tomography for two decades, until 2018, and has co-authored the three leading textbooks in the field. His extensive technology transfer work includes collaborations with the GE Global Research Centre (USA), Blackrock Neurotech, the Samsung Advanced Institute of Technology (SAIT) for EIT ASIC design, and Galvani Bioelectronics (a joint venture between GSK and Google Health), with whom UCL has jointly filed seven patents.
 

The Joel Chair

The Joel Chair is the oldest established Chair in Medical Physics in the world. It is currently held by Prof Robert Speller of UCL Medical Physics & Biomedical Engineering.

The Joel Lecture Series is free to attend and open to all. You don't have to be a UCL staff member or student to come along.

Lectures begin at 17:30 and are typically one hour long. A drinks reception will follow, to which everyone is welcome to join. We look forward to meeting you at one of our events!

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Please note photographs and recordings taken at this event may be included in future publications, on our website and on social media. You will have the opportunity to opt out at the event. If you have any questions, please contact medphys.comms@ucl.ac.uk

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