Effect of ionic diffusion on extracellular potentials (Halnes et al 2016)

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Accession:225311
"Recorded potentials in the extracellular space (ECS) of the brain is a standard measure of population activity in neural tissue. Computational models that simulate the relationship between the ECS potential and its underlying neurophysiological processes are commonly used in the interpretation of such measurements. Standard methods, such as volume-conductor theory and current-source density theory, assume that diffusion has a negligible effect on the ECS potential, at least in the range of frequencies picked up by most recording systems. This assumption remains to be verified. We here present a hybrid simulation framework that accounts for diffusive effects on the ECS potential. ..."
Reference:
1 . Halnes G, Mäki-Marttunen T, Keller D, Pettersen KH, Andreassen OA, Einevoll GT (2016) Effect of Ionic Diffusion on Extracellular Potentials in Neural Tissue. PLoS Comput Biol 12:e1005193 [PubMed]
Model Information (Click on a link to find other models with that property)
Model Type: Extracellular; Neuron or other electrically excitable cell;
Brain Region(s)/Organism:
Cell Type(s): Neocortex U1 L6 pyramidal corticalthalamic GLU cell;
Channel(s):
Gap Junctions:
Receptor(s):
Gene(s):
Transmitter(s):
Simulation Environment: MATLAB; NEURON;
Model Concept(s): Extracellular Fields;
Implementer(s): Halnes, Geir [geir.halnes at nmbu.no]; Maki-Marttunen, Tuomo [tuomo.maki-marttunen at tut.fi];
Search NeuronDB for information about:  Neocortex U1 L6 pyramidal corticalthalamic GLU cell;
function [freq_signal, f] = Nfreq5(v,tv)
% Finds frequecy spectrum of time series v (at time pts tv)

v = v-mean(v);

% Interpolation
difftv = diff(tv); % In some cases the same data point occurs twice. Remove duplicates:
keepind = find(difftv);
tv = tv(keepind);
v = v(keepind);

NFFT = 2^(nextpow2(length(v)));    % Next power of 2 from length of y. This optimizes the fft.

tin = linspace(min(tv), max(tv), NFFT); % interpolate the signal so it has this length
v = interp1(tv, v, tin);
dt = tin(5)-tin(4); % All time points were equally spaced

% Sample
samp_freq = 1/dt;
freq_signal = fft(v);
freq_signal = fft(v,NFFT)/length(v);


% TO ONLY LOOK AT FIRST HALF OF FREQ. SPEC.
f = samp_freq/2*linspace(0,1,NFFT/2+1);
freq_signal = abs(freq_signal(1:NFFT/2+1));

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