Journal ArticleDOI
Modelling and analysis of local field potentials for studying the function of cortical circuits
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TLDR
Careful mathematical modelling and analysis are needed to take full advantage of the opportunities that this signal offers in understanding signal processing in cortical circuits and, ultimately, the neural basis of perception and cognition.Abstract:
Local field potentials (LFPs) provide a wealth of information about synaptic processing in cortical populations but are difficult to interpret. Einevoll and colleagues consider the neural origin of cortical LFPs and discuss LFP modelling and analysis methods that can improve the interpretation of LFP data.read more
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Journal ArticleDOI
Hybrid Scheme for Modeling Local Field Potentials from Point-Neuron Networks.
Espen Hagen,Espen Hagen,David Dahmen,Maria L. Stavrinou,Maria L. Stavrinou,Henrik Lindén,Henrik Lindén,Tom Tetzlaff,Sacha J. van Albada,Sonja Grün,Sonja Grün,Markus Diesmann,Markus Diesmann,Gaute T. Einevoll,Gaute T. Einevoll +14 more
TL;DR: The generic nature of the hybrid scheme and its public implementation in hybridLFPy form the basis for LFP predictions from other and larger point-neuron network models, as well as extensions of the current application with additional biological detail.
Journal ArticleDOI
Modelling and Analysis of Electrical Potentials Recorded in Microelectrode Arrays (MEAs)
Torbjørn V. Ness,Chaitanya Chintaluri,Jan Potworowski,Szymon Łęski,Helena Głąbska,Daniel K. Wójcik,Gaute T. Einevoll,Gaute T. Einevoll +7 more
TL;DR: A biophysical forward-modelling formalism based on the finite element method (FEM) is used to establish quantitatively accurate links between neural activity in the slice and potentials recorded in the MEA set-up, and methods for estimation of current-source density (CSD) from MEA potentials are explored.
Journal ArticleDOI
Toward More Versatile and Intuitive Cortical Brain–Machine Interfaces
TL;DR: This review will focus on several new topics in the arena of cortical prosthetics using: recordings from cortical areas outside motor cortex; local field potentials as a source of recorded signals; somatosensory feedback for more dexterous control of robotics; and new decoding methods that work in concert to form an ecology of decode algorithms.
Journal ArticleDOI
Hippocampal Place Cells Couple to Three Different Gamma Oscillations during Place Field Traversal
TL;DR: It is shown that spike timing of place cells can tune to all three gamma oscillations, but phase coupling to the mid-frequency gamma oscillation conveyed from the entorhinal cortex was restricted to leaving a place field.
Journal ArticleDOI
Optimal Electrode Size for Multi-Scale Extracellular-Potential Recording From Neuronal Assemblies
TL;DR: It is demonstrated that the noise and signal attenuation depend more on the electrode impedance than on electrode size, per se, especially for electrodes <10 μm in width or diameter to achieve high-spatial-resolution readout.
References
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Learning the parts of objects by non-negative matrix factorization
TL;DR: An algorithm for non-negative matrix factorization is demonstrated that is able to learn parts of faces and semantic features of text and is in contrast to other methods that learn holistic, not parts-based, representations.
Learning parts of objects by non-negative matrix factorization
TL;DR: In this article, non-negative matrix factorization is used to learn parts of faces and semantic features of text, which is in contrast to principal components analysis and vector quantization that learn holistic, not parts-based, representations.
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