Propagation of action potentials in dendrites depends on dendritic morphology.
Action potential propagation links information processing in different regions of the dendritic tree. To examine the contribution of dendritic morphology to the efficacy of propagation, simulations were performed in detailed reconstructions of eight different neuronal types. With identical complements of voltage-gated channels, different dendritic morphologies exhibit distinct patterns of propagation. Remarkably, the range of backpropagation efficacies observed experimentally can be reproduced by the variations in dendritic morphology alone. Dendritic geometry also determines the extent to which modulation of channel densities can affect propagation. Thus in Purkinje cells and dopamine neurons, backpropagation is relatively insensitive to changes in channel densities, whereas in pyramidal cells, backpropagation can be modulated over a wide range. We also demonstrate that forward propagation of dendritically initiated action potentials is influenced by morphology in a similar manner. We show that these functional consequences of the differences in dendritic geometries can be explained quantitatively using simple anatomical measures of dendritic branching patterns, which are captured in a reduced model of dendritic geometry. These findings indicate that differences in dendritic geometry act in concert with differences in voltage-gated channel density and kinetics to generate the diversity in dendritic action potential propagation observed between neurons. They also suggest that changes in dendritic geometry during development and plasticity will critically affect propagation. By determining the spatial pattern of action potential signaling, dendritic morphology thus helps to define the size and interdependence of functional compartments in the neuron.
Vetter
P
P
Department of Physiology, University College London, London WC1E 6BT, United Kingdom.
Roth
A
A
Häusser
M
M
D000200:Action Potentials / Q000502:physiology; D000818:Animals; D003198:Computer Simulation; D003712:Dendrites / Q000502:physiology* / Q000648:ultrastructure*; D008433:Mathematics; D008959:Models, Neurological; D009474:Neurons / Q000145:classification / Q000502:physiology; D015221:Potassium Channels / Q000378:metabolism; D051381:Rats; D015222:Sodium Channels / Q000378:metabolism
D015221:Potassium Channels; D015222:Sodium Channels