Optimization of astrocyte-neuron network simulator
Ladron De Guevara Ruiz, Antonio (2016)
Ladron De Guevara Ruiz, Antonio
2016
Master's Degree Programme in Biomedical Engineering
Tieto- ja sähkötekniikan tiedekunta - Faculty of Computing and Electrical Engineering
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Hyväksymispäivämäärä
2016-08-17
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:tty-201608034388
https://urn.fi/URN:NBN:fi:tty-201608034388
Tiivistelmä
In order to study how living systems work, it is often in in vivo experiments to alter the function of a system so that a better understanding of the underlying responses and the role of each of their components can be obtained when that physiological system tries to restore itself. On the other hand, there are several methods which allow to study the functions of different systems and their components without disturbing the normal function of a living system. One of these tools is in silico modelling of the systems.
In this work, we focus on modelling parts of the brain. The brain is composed of multiple cell types such as neurons or glia cells, each of them has its specific function which can be structural, immunological, signaling, etc. In particular, a certain type of glia cells called astrocytes has attracted great interest because of their modulating of the neuronal signaling through the release of neuroactive molecules.
In order to understand the function of astrocytes in the brain activity, we used the model called INEXA developed by Eero Räisänen et al. (Räisänen 2015) which combines existing models in order to bring together the function of neurons and astrocytes. Neuronal networks are modelled using INEX by Kerstin Lenk (Lenk 2011). Astrocytes are modelled by using Lallouette’s topology model (Lallouette, De Pittà, Ben-Jacob, & Berry, 2014) and a near synapse simulator interface together with De Pittà’s presynapse model (De Pittà, Volman, Berry, & Ben-Jacob, 2011).
Several simulations were run in order to study different parameters and understand how they can influence the performance of the whole model and the normal bursting behavior of the neuronal network. Connectivity, synaptic strength, calcium dynamics, number of astrocytes, etc. are parameters that have a great importance in the model. Based on the study of these parameters, we further improved the INEXA model developed by Eero Räisänen et al. and we also studied how to adjust them to simulate different scenarios apart from normal brain activity.
The final aim of this master’s thesis is to simulate the brain activity corresponding to some neurological diseases such as epilepsy so that we can obtain a better understanding of the role of astrocytes in the modulation of signal patterns towards normal bursting behavior while restricting the undesired brain activity.
In this work, we focus on modelling parts of the brain. The brain is composed of multiple cell types such as neurons or glia cells, each of them has its specific function which can be structural, immunological, signaling, etc. In particular, a certain type of glia cells called astrocytes has attracted great interest because of their modulating of the neuronal signaling through the release of neuroactive molecules.
In order to understand the function of astrocytes in the brain activity, we used the model called INEXA developed by Eero Räisänen et al. (Räisänen 2015) which combines existing models in order to bring together the function of neurons and astrocytes. Neuronal networks are modelled using INEX by Kerstin Lenk (Lenk 2011). Astrocytes are modelled by using Lallouette’s topology model (Lallouette, De Pittà, Ben-Jacob, & Berry, 2014) and a near synapse simulator interface together with De Pittà’s presynapse model (De Pittà, Volman, Berry, & Ben-Jacob, 2011).
Several simulations were run in order to study different parameters and understand how they can influence the performance of the whole model and the normal bursting behavior of the neuronal network. Connectivity, synaptic strength, calcium dynamics, number of astrocytes, etc. are parameters that have a great importance in the model. Based on the study of these parameters, we further improved the INEXA model developed by Eero Räisänen et al. and we also studied how to adjust them to simulate different scenarios apart from normal brain activity.
The final aim of this master’s thesis is to simulate the brain activity corresponding to some neurological diseases such as epilepsy so that we can obtain a better understanding of the role of astrocytes in the modulation of signal patterns towards normal bursting behavior while restricting the undesired brain activity.