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An Analogue Front-End Model for Developing Neural Spike Sorting Systems

Lookup NU author(s): Professor Andrew Jackson



This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


In spike sorting systems, front-end electronics is a crucial pre-processing step that not only has a direct impact on detection and sorting accuracy, but also on power and silicon area. In this work, a behavioural front-end model is proposed to assess the impact of the design parameters (including signal-to-noise ratio, filter type/order, bandwidth, converter resolution/rate) on subsequent spike processing. Initial validation of the model is provided by applying a test stimulus to a hardware platform and comparing the measured circuit response to the expected from the behavioural model. Our model is then used to demonstrate the effect of the Analogue Front-End (AFE) on subsequent spike processing by testing established spike detection and sorting methods on a selection of systems reported in the literature. It is revealed that although these designs have a wide variation in design parameters (and thus also circuit complexity), the ultimate impact on spike processing performance is relatively low (10-15%). This can be used to inform the design of future systems to have an efficient AFE whilst also maintaining good processing performance.

Publication metadata

Author(s): Barsakcioglu DY, Liu Y, Bhunjun P, Navajas J, Eftekhar A, Jackson A, Quiroga RQ, Constandinou TG

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Biomedical Circuits and Systems

Year: 2014

Volume: 8

Issue: 2

Pages: 216-227

Print publication date: 28/04/2014

Acceptance date: 19/03/2014

Date deposited: 05/08/2015

ISSN (print): 1932-4545

ISSN (electronic): 1940-9990

Publisher: Institute of Electrical and Electronics Engineers


DOI: 10.1109/TBCAS.2014.2313087


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