Imperial College London
Portrait Picture

Professor Timothy Constandinou

Faculty of Engineering, Department of Electrical and Electronic Engineering

Professor of Bioelectronics
 
 
 
//

Contact

 

+44 (0)20 7594 0790t.constandinou Website

 
 
//

Assistant

 

Miss Izabela Wojcicka-Grzesiak +44 (0)20 7594 0701

 
//

Location

 

B407Bessemer BuildingSouth Kensington Campus

//

Summary

 

Publications

Citation

BibTex format

@inproceedings{Savolainen:2020,
author = {Savolainen, OW and Constandinou, TG},
pages = {884--887},
publisher = {IEEE},
title = {Predicting single-unit activity from local field potentials with LSTMs},
url = {http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000621592201053&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202},
year = {2020}
}
Download

RIS format (EndNote, RefMan)

TY  - CPAPER
AB  - This paper investigates to what extent Long ShortTerm Memory (LSTM) decoders can use Local Field Potentials (LFPs) to predict Single-Unit Activity (SUA) in Macaque Primary Motor cortex. The motivation is to determine to what degree the LFP signal can be used as a proxy for SUA, for both neuroscience and Brain-Computer Interface (BCI) applications. Firstly, the results suggest that the prediction quality varies significantly by implant location or animal. However, within each implant location / animal, the prediction quality seems to be correlated with the amount of power in certain LFP frequency bands (0-10, 10-20 and 40-50 Hz, standardised LFPs). Secondly, the results suggest that bipolar LFPs are more informative as to SUA than unipolar LFPs. This suggests common mode rejection aids in the elimination of non-local neural information. Thirdly, the best individual bipolar LFPs generally perform better than when using all available unipolar LFPs. This suggests that LFP channel selection may be a simple but effective means of lossy data compression in Wireless Intracortical LFP-based BCIs. Overall, LFPs were moderately predictive of SUA, and improvements can likely be made.
AU  - Savolainen,OW
AU  - Constandinou,TG
EP  - 887
PB  - IEEE
PY  - 2020///
SN  - 1557-170X
SP  - 884
TI  - Predicting single-unit activity from local field potentials with LSTMs
UR  - http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000621592201053&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
UR  - http://hdl.handle.net/10044/1/90714
ER  -
Download