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Sunday, July 19 • 9:00pm - 10:00pm
P44: 3D modeling of Purkinje cell activity

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Alexey Martyushev, Erik De Schutter

The NEURON software remains the main neural physiology modeling tool for scientists. Its computational methods benefit from deterministic approximations of the cable equation solutions and 1-dimensional radial calcium diffusion in cylindrical neuron morphologies [1]. However, in real neurons ions diffuse in 3-dimensional volumes [2]and membrane channels get activated in a stochastic manner. Furthermore, NEURON does not suit to model nano-sized spine morphology. In contrast, the Stochastic Engine for Pathway Simulation (STEPS) uses fully stochastic 3-dimensional methods in tetrahedral morphologies that can provide realistic modeling of neurons at the nanoscale [3, 4].

In this work, we compare the modeling results between those two environments for the Purkinje cell model developed by Zang et al. [5]. This model considers a variety of calcium, potassium and sodium channels, and the resulting calcium concentrations affecting the membrane potential of a Purkinje cell. The results demonstrate that: (i) the used cylinder light microscopy morphology can not be identically transformed into a 3D mesh; (ii) the effect of stochastic channel activation determines the timing of membrane potential spikes; (iii) the kinetics of calcium activated potassium channels strongly depends on the specified sub-membrane volumes in both environments.

A further step in developing the model will be integration of a digital microscopy reconstruction of spines to the existing 3D tetrahedral mesh.

**References:**

1. Carnevale, N.T. and M.L. Hines, The NEURON Book. 2009: Cambridge University Press.

2. Anwar, H., et al., Dendritic diameters affect the spatial variability of intracellular calcium dynamics in computer models. Front Cell Neurosci, 2014. 8: p. 168.

3. Hepburn, I., et al., STEPS: efficient simulation of stochastic reaction-diffusion models in realistic morphologies. BMC Syst Biol, 2012. 6: p. 36.

4. Chen, W. and E. De Schutter, Time to Bring Single Neuron Modeling into 3D. Neuroinformatics, 2017. 15(1): p. 1-3.

5. Zang, Y., S. Dieudonne, and E. De Schutter, Voltage- and Branch-Specific Climbing Fiber Responses in Purkinje Cells. Cell Rep, 2018. 24(6): p. 1536-1549.

Speakers
AM

Alexey Martyushev

Computational Neuroscience Unit, Okinawa Institute of Science and Technology (OIST)


Sunday July 19, 2020 9:00pm - 10:00pm CEST
Slot 04