Hardware-efficient VLSI design for large scale neural signal processing

Leuven - PhD
More than two weeks ago

Deciphering the brain with advanced CMOS circuitry and more powerful neural probes

The brain is the most complex organ in the human body and, to be able to understand how it works, large-scale in-vivo sensing of neuron populations has emerged as a key research technique. Microfabricated silicon neural probes have been established as the dominant technology in this field and have achieved ever increasing densities and numbers of simultaneous recording electrodes. imec is the leader in the design and development of CMOS neural probes that achieve minimum probe-shank dimensions, high electrode density and large number of simultaneous recording channels with low-noise and low-power performances. With these probes, it is currently possible to record from many neurons spanning multiple brain regions. However, future neural probes will require even higher numbers of simultaneous recording sites to enable the study of much larger neuron populations in the brain. In addition, wireless data transmission is becoming an important requirement to allow experiments with free-moving animals without tethering cables. Thus, on-chip neural signal processing is compulsory in such system to compress the enormous raw data which take way too much power to be transmitted wirelessly. The ideal solution would be to sort the recorded neural spikes before transmission, so that only the identifiers of the recorded neurons and their spike timings need to be transmitted.
This PhD will explore the neural signal processing algorithms and architectures that will potentially achieve the optimal balance between hardware overhead and the usability for certain neuroscientific and clinical applications. The research will seek the best system approach to implement a neural signal processor for close to 1000 parallel recording channels. The candidate will develop novel analog and mixed-signal VLSI circuitry to fulfill these tasks and test the functionality and performance in a real-case scenario.


Required background: Master in Electrical Engineering with focus on analog & mixed signal integrated circuit design

Type of work: 70% circuit design, 20% experimental, 10% literature

Supervisor: Chris Van Hoof

Daily advisor: Shiwei Wang

The reference code for this position is 2020-105. Mention this reference code on your application form.
Chinese nationals who wish to apply for the CSC scholarship, should use the following code when applying for this topic: CSC2020-54.


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