Methods for inferring neural circuit interactions and neuromodulation from local field potential and electroencephalogram measures
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Methods for inferring neural circuit interactions and neuromodulation from local field potential and electroencephalogram measures. / Martínez-Cañada, Pablo; Noei, Shahryar; Panzeri, Stefano.
In: Brain informatics, Vol. 8, No. 1, 15.12.2021, p. 27.Research output: SCORING: Contribution to journal › SCORING: Review article › Research
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TY - JOUR
T1 - Methods for inferring neural circuit interactions and neuromodulation from local field potential and electroencephalogram measures
AU - Martínez-Cañada, Pablo
AU - Noei, Shahryar
AU - Panzeri, Stefano
N1 - © 2021. The Author(s).
PY - 2021/12/15
Y1 - 2021/12/15
N2 - Electrical recordings of neural mass activity, such as local field potentials (LFPs) and electroencephalograms (EEGs), have been instrumental in studying brain function. However, these aggregate signals lack cellular resolution and thus are not easy to be interpreted directly in terms of parameters of neural microcircuits. Developing tools for a reliable estimation of key neural parameters from these signals, such as the interaction between excitation and inhibition or the level of neuromodulation, is important for both neuroscientific and clinical applications. Over the years, we have developed tools based on neural network modeling and computational analysis of empirical data to estimate neural parameters from aggregate neural signals. This review article gives an overview of the main computational tools that we have developed and employed to invert LFPs and EEGs in terms of circuit-level neural phenomena, and outlines future challenges and directions for future research.
AB - Electrical recordings of neural mass activity, such as local field potentials (LFPs) and electroencephalograms (EEGs), have been instrumental in studying brain function. However, these aggregate signals lack cellular resolution and thus are not easy to be interpreted directly in terms of parameters of neural microcircuits. Developing tools for a reliable estimation of key neural parameters from these signals, such as the interaction between excitation and inhibition or the level of neuromodulation, is important for both neuroscientific and clinical applications. Over the years, we have developed tools based on neural network modeling and computational analysis of empirical data to estimate neural parameters from aggregate neural signals. This review article gives an overview of the main computational tools that we have developed and employed to invert LFPs and EEGs in terms of circuit-level neural phenomena, and outlines future challenges and directions for future research.
U2 - 10.1186/s40708-021-00148-y
DO - 10.1186/s40708-021-00148-y
M3 - SCORING: Review article
C2 - 34910260
VL - 8
SP - 27
JO - Brain informatics
JF - Brain informatics
SN - 2198-4018
IS - 1
ER -