In this section
@article{Ahmadi:2021:10.1038/s41598-021-98021-9,
author = {Ahmadi, N and Constandinou, T and Bouganis, C},
doi = {10.1038/s41598-021-98021-9},
journal = {Scientific Reports},
pages = {1--13},
title = {Inferring entire spiking activity from local field potentials},
url = {http://dx.doi.org/10.1038/s41598-021-98021-9},
volume = {11},
year = {2021}
}
TY - JOUR
AB - Extracellular recordings are typically analysed by separating them into two distinct signals: local field potentials (LFPs) andspikes. Previous studies have shown that spikes, in the form of single-unit activity (SUA) or multiunit activity (MUA), can beinferred solely from LFPs with moderately good accuracy. SUA and MUA are typically extracted via threshold-based techniquewhich may not be reliable when the recordings exhibit a low signal-to-noise ratio (SNR). Another type of spiking activity, referredto as entire spiking activity (ESA), can be extracted by a threshold-less, fast, and automated technique and has led to betterperformance in several tasks. However, its relationship with the LFPs has not been investigated. In this study, we aim toaddress this issue by inferring ESA from LFPs intracortically recorded from the motor cortex area of three monkeys performingdifferent tasks. Results from long-term recording sessions and across subjects revealed that ESA can be inferred from LFPswith good accuracy. On average, the inference performance of ESA was consistently and significantly higher than those of SUAand MUA. In addition, local motor potential (LMP) was found to be the most predictive feature. The overall results indicate thatLFPs contain substantial information about spiking activity, particularly ESA. This could be useful for understanding LFP-spikerelationship and for the development of LFP-based BMIs.
AU - Ahmadi,N
AU - Constandinou,T
AU - Bouganis,C
DO - 10.1038/s41598-021-98021-9
EP - 13
PY - 2021///
SN - 2045-2322
SP - 1
TI - Inferring entire spiking activity from local field potentials
T2 - Scientific Reports
UR - http://dx.doi.org/10.1038/s41598-021-98021-9
UR - https://www.nature.com/articles/s41598-021-98021-9
UR - http://hdl.handle.net/10044/1/91559
VL - 11
ER -
Established in 2017 by its principal funder the Medical Research Council, in partnership with Alzheimer's Society and Alzheimer’s Research UK, The UK Dementia Research Institute (UK DRI) is the UK’s leading biomedical research institute dedicated to neurodegenerative diseases.
