BibTex format

author = {Savolainen, OW and Constandinou, TG},
pages = {884--887},
publisher = {IEEE},
title = {Predicting single-unit activity from local field potentials with LSTMs},
url = {},
year = {2020}

RIS format (EndNote, RefMan)

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
PY - 2020///
SN - 1557-170X
SP - 884
TI - Predicting single-unit activity from local field potentials with LSTMs
UR -
UR -
ER -