Methods for inferring neural circuit interactions and neuromodulation from local field potential and electroencephalogram measures

Brain Informatics

Stefano Panzeri¹  Shahryar Noei²  Pablo Martínez-Cañada³ 

[1] Department of Excellence for Neural Information Processing, Center for Molecular Neurobiology (ZMNH), University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany;Neural Computation Laboratory, Istituto Italiano Di Tecnologia, Genova and Rovereto, Italy;Neural Computation Laboratory, Istituto Italiano Di Tecnologia, Genova and Rovereto, Italy;CIMeC, University of Trento, Rovereto, Italy;Neural Computation Laboratory, Istituto Italiano Di Tecnologia, Genova and Rovereto, Italy;Optical Approaches To Brain Function Laboratory, Istituto Italiano Di Tecnologia, Genova, Italy;

关键词: Local field potential (LFP);    Electroencephalogram (EEG);    Neural oscillation;    Information theory;    Neural network model;    Leaky integrate-and-fire (LIF) neuron model;    Neuromodulation;   

DOI  :  10.1186/s40708-021-00148-y

来源: Springer

【 摘 要 】

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.

【 授权许可】

CC BY