Andreas Stöckel. Finding tuning curves for point neurons with conductance-based synapses. Technical Report, Centre for Theoretical Neuroscience, Waterloo, ON, 10 2017. URL: https://www.researchgate.net/publication/320508781_Finding_Tuning_Curves_for_Point_Neurons_with_Conductance-Based_Synapses, doi:10.13140/RG.2.2.30152.83202.
@techreport{stoeckel2017a,
title = {Finding Tuning Curves for Point Neurons with Conductance-Based Synapses},
year = {2017},
month = {10},
institution = {Centre for Theoretical Neuroscience},
address = {Waterloo, ON},
abstract = {In the Neural Engineering Framework (NEF), individual neuron tuning curves are often characterized in terms of a maximum firing rate and an $x$-intercept. However, for LIF neurons with conductance-based synapses it is not immediately clear how maximum rate and $x$-intercept should be mapped to excitatory and inhibitory conductance input functions $g_\mathrm{E}(x)$, $g_\mathrm{I}(x)$. In this technical report we describe a method for deriving such functions and compare the resulting conductance-based tuning curves to current-based tuning curves with equivalent parameters. For large maximum rates and $x$-intercepts the conductance-based tuning curves possess a significantly steeper spike-rate onset compared to their current-based counterparts.},
issn = {CTN-TR-20171019-014},
author = {Andreas St\"ockel},
pdf = {/files/publications/stoeckel.2017a.pdf},
doi = {10.13140/RG.2.2.30152.83202},
url = {https://www.researchgate.net/publication/320508781_Finding_Tuning_Curves_for_Point_Neurons_with_Conductance-Based_Synapses}
}