TY - JOUR
T1 - The limited utility of multiunit data in differentiating neuronal population activity
AU - Keller, Corey J.
AU - Chen, Christopher
AU - Lado, Fred A.
AU - Khodakhah, Kamran
N1 - Publisher Copyright:
© 2016 Keller et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2016/4
Y1 - 2016/4
N2 - To date, single neuron recordings remain the gold standard for monitoring the activity of neuronal populations. Since obtaining single neuron recordings is not always possible, high frequency or 'multiunit activity' (MUA) is often used as a surrogate. Although MUA recordings allow one to monitor the activity of a large number of neurons, they do not allow identification of specific neuronal subtypes, the knowledge of which is often critical for understanding electrophysiological processes. Here, we explored whether prior knowledge of the single unit waveform of specific neuron types is sufficient to permit the use of MUA to monitor and distinguish differential activity of individual neuron types.We used an experimental and modeling approach to determine if components of the MUA can monitor medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) in the mouse dorsal striatum.We demonstrate that when well-isolated spikes are recorded, the MUA at frequencies greater than 100Hz is correlated with single unit spiking, highly dependent on the waveform of each neuron type, and accurately reflects the timing and spectral signature of each neuron. However, in the absence of well-isolated spikes (the norm in most MUA recordings), the MUA did not typically contain sufficient information to permit accurate prediction of the respective population activity of MSNs and FSIs. Thus, even under ideal conditions for the MUA to reliably predict the moment-to-moment activity of specific local neuronal ensembles, knowledge of the spike waveform of the underlying neuronal populations is necessary, but not sufficient.
AB - To date, single neuron recordings remain the gold standard for monitoring the activity of neuronal populations. Since obtaining single neuron recordings is not always possible, high frequency or 'multiunit activity' (MUA) is often used as a surrogate. Although MUA recordings allow one to monitor the activity of a large number of neurons, they do not allow identification of specific neuronal subtypes, the knowledge of which is often critical for understanding electrophysiological processes. Here, we explored whether prior knowledge of the single unit waveform of specific neuron types is sufficient to permit the use of MUA to monitor and distinguish differential activity of individual neuron types.We used an experimental and modeling approach to determine if components of the MUA can monitor medium spiny neurons (MSNs) and fast-spiking interneurons (FSIs) in the mouse dorsal striatum.We demonstrate that when well-isolated spikes are recorded, the MUA at frequencies greater than 100Hz is correlated with single unit spiking, highly dependent on the waveform of each neuron type, and accurately reflects the timing and spectral signature of each neuron. However, in the absence of well-isolated spikes (the norm in most MUA recordings), the MUA did not typically contain sufficient information to permit accurate prediction of the respective population activity of MSNs and FSIs. Thus, even under ideal conditions for the MUA to reliably predict the moment-to-moment activity of specific local neuronal ensembles, knowledge of the spike waveform of the underlying neuronal populations is necessary, but not sufficient.
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U2 - 10.1371/journal.pone.0153154
DO - 10.1371/journal.pone.0153154
M3 - Article
C2 - 27111446
AN - SCOPUS:84964981015
SN - 1932-6203
VL - 11
JO - PloS one
JF - PloS one
IS - 4
M1 - e0153154
ER -