TY - GEN
T1 - Predicting local field potentials with recurrent neural networks
AU - Kim, Louis
AU - Harer, Jacob
AU - Rangamani, Akshay
AU - Moran, James
AU - Parks, Philip D.
AU - Widge, Alik
AU - Eskandar, Emad
AU - Dougherty, Darin
AU - Chin, Sang Peter
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/10/13
Y1 - 2016/10/13
N2 - We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.
AB - We present a Recurrent Neural Network using LSTM (Long Short Term Memory) that is capable of modeling and predicting Local Field Potentials. We train and test the network on real data recorded from epilepsy patients. We construct networks that predict multi-channel LFPs for 1, 10, and 100 milliseconds forward in time. Our results show that prediction using LSTM outperforms regression when predicting 10 and 100 millisecond forward in time.
UR - http://www.scopus.com/inward/record.url?scp=85009110562&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85009110562&partnerID=8YFLogxK
U2 - 10.1109/EMBC.2016.7590824
DO - 10.1109/EMBC.2016.7590824
M3 - Conference contribution
C2 - 28268448
AN - SCOPUS:85009110562
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 808
EP - 811
BT - 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016
Y2 - 16 August 2016 through 20 August 2016
ER -