SigMate: A Matlab-based automated tool for extracellular neuronal signal processing and analysis (original) (raw)
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Analysis of spike and local field potential (LFP) data is an essential part of neuroscientific research. Today there exist many open-source toolboxes for spike and LFP data analysis implementing various functionality. Here we aim to provide a practical guidance for neuroscientists in the choice of an open-source toolbox best satisfying their needs. We overview major open-source toolboxes for spike and LFP data analysis as well as toolboxes with tools for connectivity analysis, dimensionality reduction and generalized linear modeling. We focus on comparing toolboxes functionality, statistical and visualization tools, documentation and support quality. To give a better insight, we compare and illustrate functionality of the toolboxes on open-access dataset or simulated data and make corresponding MATLAB scripts publicly available.
Local field potentials (LFPs) sampled with extracellular electrodes are frequently used as a measure of population neuronal activity. However, relating such measurements to underlying neuronal behaviour and connectivity is non-trivial. To help study this link, we developed the Virtual Electrode Recording Tool for EXtracellular potentials (VERTEX). We first identified a reduced neuron model that retained the spatial and frequency filtering characteristics of extracellular potentials from neocortical neurons. We then developed VERTEX as an easy-to-use Matlab tool for simulating LFPs from large populations (>100,000 neurons). A VERTEX-based simulation successfully reproduced features of the LFPs from an in vitro multi-electrode array recording of macaque neocortical tissue. Our model, with virtual electrodes placed anywhere in 3D, allows direct comparisons with the in vitro recording setup. We envisage that VERTEX will stimulate experimentalists, clinicians, and computational neuroscientists to use models to understand the mechanisms underlying measured brain dynamics in health and disease.
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Modelling and analysis of local field potentials for studying the function of cortical circuits
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Electrical signals from the cortical surface of animals were recorded as early as 1875 (REF. 1), 50 years before the advent of electroencephalography (EEG) 2 . Subsequent work revealed that the high-frequency part (above ~500 Hz) of the recorded potentials provides information about the spiking activity of neurons located around the electrode 3 . By contrast, the part of the signal that has frequencies below ~500 Hz, the so-called 'local field potential' (LFP), was found more difficult to interpret in terms of the underlying neural activity. Although the introduction of current source density (CSD) analysis in the 1950s 4 rejuvenated the use of the LFP in the following decades 5-7 , interest decreased in the 1980s and 1990s, probably owing to the focus on new single-neuron techniques (for example, patch-clamp recordings) and on understanding the link between single-neuron activity and perception.