Estimation of neural network model parameters from local field potentials (LFPs)
Fig 1
Overview of hybrid scheme for computing local field potentials (LFPs).
Top row: First, the dynamics of a network is simulated using a point-neuron simulation (A), and the resulting spike times are saved to file. Orange and blue color indicate excitatory and inhibitory neurons, respectively. In a separate simulation, the obtained spike times are replayed as synaptic input currents onto reconstructed neuron morphologies representing postsynaptic target neurons (B, only one excitatory in orange and one inhibitory neuron in blue are shown). Based on the resulting transmembrane currents of the postsynaptic target neurons in this second simulation, the LFP is calculated (C). Bottom row: Prediction of LFPs from population firing histograms. Instead of running the full hybrid scheme, the LFP can be predicted by the convolution of the population firing histograms (lower figure in A) with kernels representing the average contribution to the LFP by a single spike in each population (lower figure in B). These kernels are computed using the hybrid scheme [29], see Methods.