Open AccessWhat we can and what we cannot see with extracellular multielectrodes
Author(s) -
Chaitanya Chintaluri,
Marta Bejtka,
Władysław Średniawa,
Michał Czerwiński,
Jakub M. Dzik,
Joanna Jędrzejewska-Szmek,
Kacper Kondrakiewicz,
Ewa Kublik,
Daniel K. Wójcik
Publication year - 2021
Publication title -
plos computational biology/plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1008615
Subject(s) - unobservable , kernel density estimation , computer science , current (fluid) , timeline , artificial intelligence , neuroscience , physics , biology , mathematics , statistics , econometrics , estimator , thermodynamics
Extracellular recording is an accessible technique used in animals and humans to study the brain physiology and pathology. As the number of recording channels and their density grows it is natural to ask how much improvement the additional channels bring in and how we can optimally use the new capabilities for monitoring the brain. Here we show that for any given distribution of electrodes we can establish exactly what information about current sources in the brain can be recovered and what information is strictly unobservable. We demonstrate this in the general setting of previously proposed kernel Current Source Density method and illustrate it with simplified examples as well as using evoked potentials from the barrel cortex obtained with a Neuropixels probe and with compatible model data. We show that with conceptual separation of the estimation space from experimental setup one can recover sources not accessible to standard methods.