" ... Here, we study computational models of neurons to investigate the functional effects of dendritic spikes. In agreement with previous studies, we found that point neurons or neurons with passive dendrites increase their somatic firing rate in response to the correlation of synaptic bombardment for a wide range of input conditions, i.e. input firing rates, synaptic conductances, or refractory periods. However, neurons with active dendrites show the opposite behavior: for a wide range of conditions the firing rate decreases as a function of correlation. We found this property in three types of models of dendritic excitability: a Hodgkin-Huxley model of dendritic spikes, a model with integrate and fire dendrites, and a discrete-state dendritic model. We conclude that fast dendritic spikes confer much broader computational properties to neurons, sometimes opposite to that of point neurons."
Model Type: Neuron or other electrically excitable cell
Cell Type(s): Abstract integrate-and-fire neuron; Hodgkin-Huxley neuron
Currents: I Sodium; I Potassium
Model Concept(s): Influence of Dendritic Geometry; Synaptic Integration
Simulation Environment: Brian 2
Implementer(s): Górski, Tomasz [gorski at inaf.cnrs-gif.fr]
References:
Górski T et al. (2018). Dendritic sodium spikes endow neurons with inverse firing rate response to correlated synaptic activity. Journal of computational neuroscience. 45 [PubMed]