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Active Dendrites Enhance Neuronal Dynamic Range

Figure 1

Morphology and dynamics of the model.

(A) Definition of dynamical states: each dendritic branchlet can be in one of three states (represented by circles): quiescent (blue), active (red) or refractory (grey). A quiescent state becomes active due to integrated synaptic input (with probability ) or transmission from an active neighbor (with probability , also called the coupling parameter). The active state has a fixed duration, changing to the refractory state after a single time step (). The refractory state returns to the quiescent state with probability ( = 0.5 unless otherwise stated). (B) Example of an active dendritic tree with : branchlets connected in a binary tree topology. The probability that activity in one branchlet activates its neighbour is (if the neighbor is in a quiescent state). (C) Apical activity as a function of the number of dendritic branchlets. Due to integrated synaptic input, each branchlet becomes excited with a probability distribution modeled as an independent Poisson process with rate h, as well as deterministic propagation from active neighbors (). From bottom to top: activations per second at each branchlet.

Figure 1

doi: https://doi.org/10.1371/journal.pcbi.1000402.g001