Conductance-based models and the fragmentation problem: A case study based on hippocampal CA1 pyramidal cell models and epilepsy

Iara Frondana, Rodrigo R.S. Carvalho, Florencia Leonardi

Epilepsy has been a central topic in computational neuroscience, and in silico models have shown to be excellent tools to integrate and evaluate findings from animal and clinical settings. Among the different languages and tools for computational modeling development, NEURON stands out as one of the most used and mature neurosimulators. However, despite the vast quantity of models developed with NEURON, a fragmentation problem is evident in the great majority of models related to the same type of cell or cell properties. This fragmentation causes a lack of interoperability between the models because of differences in parameters.

A Numerical Study of the Time of Extinction in a Class of Systems of Spiking Neurons

Cecilia Romaro, Fernando Araujo Najman, Morgan André

In this paper we present a numerical study of a mathematical model of spiking neurons introduced by Ferrari et al. in an article entitled Phase transition forinfinite systems of spiking neurons. In this model we have a countable number of neurons linked together in a network, each of them having a membrane potential taking value in the integers, and each of them spiking over time at a rate which depends on the membrane potential through some rate function ϕ. Beside being affected by a spike each neuron can also be affected by leaking. At each of these leak times, which occurs for a given neuron at a fixed rate γ, the membrane potential of the neuron concerned is spontaneously reset to 0.

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The Research, Innovation and Dissemination Center on Neuromathematics (RIDC NeuroMat) is offering a scholarship for information technology professionals interested in being part of a breakthrough and innovative scientific project.

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