Modelling NMDA channels in large-scale neural network model of primary visual cortex

• Thesis title in Czech: Modelování NMDA kanálů ve velkém spajkujícím modelu neuronových sítí
• Thesis title in English: Modelling NMDA channels in large-scale neural network model of primary visual cortex
• Academic year of topic announcement: 2021/2022
• Thesis type: diploma thesis
• Thesis language: angličtina
• Department: Department of Software and Computer Science Education (32-KSVI)
• Supervisor: Mgr. Ján Antolík, Ph.D.
• Author: hidden - assigned and confirmed by the Study Dept.
• Date of registration: 20.05.2022
• Date of assignment: 20.05.2022
• Confirmed by Study dept. on: 25.05.2023

Guidelines

The goal of this project is to upgrade our model of the primary visual
cortex so that NMDA receptors can be implemented in it. Currently, the
only type of excitatory synaptic receptors existing in our model are
AMPA, which are transient, whereas NMDA receptors have a longer rise
time and decay time and would allow us to model some more sustained
dynamics. Implementing them in our model would require some modifications
in the python module we developed in our group, so that it allows the
creation of different categories of excitatory synapses with different
temporal dynamics. As a different neuron model would be have to be used,
it would be also necessary to make some parameters search to match
qualitatively the results we obtain with the current neuron model we’re using.

References

Roth, A., & van Rossum, M. C. (2009). Modeling synapses. Computational modeling methods for neuroscientists, 6, 139-160.
J Antolík, C Monier, A Davison, Y Frégnac; A comprehensive data-driven model of cat primary visual cortex. bioRxiv, 416156