DocumentCode :
1759994
Title :
An Analogue Front-End Model for Developing Neural Spike Sorting Systems
Author :
Barsakcioglu, Deren Y. ; Yan Liu ; Bhunjun, Pooja ; Navajas, Joaquin ; Eftekhar, Amir ; Jackson, Andrew ; Quian Quiroga, Rodrigo ; Constandinou, Timothy G.
Author_Institution :
Dept. of Electr. & Electron. Eng., Imperial Coll. London, London, UK
Volume :
8
Issue :
2
fYear :
2014
fDate :
41730
Firstpage :
216
Lastpage :
227
Abstract :
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.
Keywords :
bioelectric potentials; filters; medical signal detection; medical signal processing; neural nets; neurophysiology; noise; sorting; analogue front-end model; bandwidth; converter resolution; filter type; hardware platform; neural spike detection methods; neural spike processing; neural spike sorting systems; signal-to-noise ratio; Accuracy; Electrodes; Integrated circuit modeling; Mathematical model; Neurons; Noise; Sorting; Analogue Front-End (AFE); Brain-Machine Interfaces (BMI); neural interface; spike detection; spike sorting;
fLanguage :
English
Journal_Title :
Biomedical Circuits and Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1932-4545
Type :
jour
DOI :
10.1109/TBCAS.2014.2313087
Filename :
6807520
Link To Document :
بازگشت