Stochastic Ion Channel Gating in Dendritic Neurons: Morphology Dependence and Probabilistic Synaptic Activation of Dendritic Spikes

Abstract

Neuronal activity is mediated through changes in the probability of stochastic transitions between open and closed states of ion channels. While differences in morphology define neuronal cell types and may underlie neurological disorders, very little is known about influences of stochastic ion channel gating in neurons with complex morphology. We introduce and validate new computational tools that enable efficient generation and simulation of models containing stochastic ion channels distributed across dendritic and axonal membranes. Comparison of five morphologically distinct neuronal cell types reveals that when all simulated neurons contain identical densities of stochastic ion channels, the amplitude of stochastic membrane potential fluctuations differs between cell types and depends on sub-cellular location. For typical neurons, the amplitude of membrane potential fluctuations depends on channel kinetics as well as open probability. Using a detailed model of a hippocampal CA1 pyramidal neuron, we show that when intrinsic ion channels gate stochastically, the probability of initiation of dendritic or somatic spikes by dendritic synaptic input varies continuously between zero and one, whereas when ion channels gate deterministically, the probability is either zero or one. At physiological firing rates, stochastic gating of dendritic ion channels almost completely accounts for probabilistic somatic and dendritic spikes generated by the fully stochastic model. These results suggest that the consequences of stochastic ion channel gating differ globally between neuronal cell-types and locally between neuronal compartments. Whereas dendritic neurons are often assumed to behave deterministically, our simulations suggest that a direct consequence of stochastic gating of intrinsic ion channels is that spike output may instead be a probabilistic function of patterns of synaptic input to dendrites.

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“…VCell [39] and NEURON [40] are more typical in that they allow many aspects of simulations to be constructed by GUI tools, but also allow more complicated simulations or added features to be entered by programmatic specification. PSICS [41] takes a slightly different approach by separating its GUI tool ICING from the simulator, allowing it to be used in other contexts.…”

“…VCell can import and export SBML reaction specifications [68] which then can be reproduced with other tools. STEPS [33], NeuroRD [69], and PSICS [41] provide stochastic reaction-diffusion simulations on relatively large morphologies corresponding to neuroanatomical morphologies [70], PSICS has partial support for the NeuroML model interchange format.…”

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“…This holds for ion channels of neurons [2], synaptic release [3], neural response to stimuli (trial-to-trial variability) [4], [5], and perception [6]. In fact, several experimental studies arrive at the conclusion that external stimuli only modulate the highly stochastic spontaneous firing activity of cortical networks of neurons [7], [8].…”

Spontaneous Action Potentials and Neural Coding in Unmyelinated Axons

“…Furthermore, using the HH model has the advantage that both its deterministic and stochastic variants have been studied extensively. The stochastic simulation were done using both the PSICS simulator (Cannon, O'Donnell, and Nolan, 2010), and the stochastic module in NEURON (Carnevale and Hines, 2006).…”