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Vývoj webového rozhraní pro vizualizaci simulací biologických neuronových sítí
Thesis title in Czech: Vývoj webového rozhraní pro vizualizaci simulací biologických neuronových sítí
Thesis title in English: Development of a web-based framework for visualizing biological neural network simulations
Academic year of topic announcement: 2024/2025
Thesis type: Bachelor's thesis
Thesis language:
Department: Department of Software and Computer Science Education (32-KSVI)
Supervisor: Mgr. Ján Antolík, Ph.D.
Author:
Guidelines
Simulations of biological neural networks play a pivotal role in advancing our understanding of how the brain processes information. The Mozaik [1] framework is a an automated workflow for large-scale neural simulations. This project provides a tool for an interactive exploration and comparison of simulation results, based on the Arkheia [2] data visualization framework. The student will be responsible for developing a user-friendly web interface, updating the tech stack for compatibility and maintainability, and expanding the framework's capabilities. Extensive documentation and rigorous testing will ensure reliability and usability. This project contributes to computational neuroscience by advancing neural simulation tools.

Objectives:
1. Develop a user-friendly web interface for visualizing Mozaik simulation results, based on Arkheia and updated to a contemporary tech stack for maintainability.
2. Prepare extensive documentation and testing to ensure the reliability and usability of the developed framework.
3. Expand current Arkheia functionality by incorporating additional data visualization and analysis features, enhancing the interpretation of simulation results.
References
[1] Antolík, J., & Davison, A. P. (2013). Integrated workflows for spiking neuronal network simulations. Frontiers in Neuroinformatics, 7(December), 1–15. https://doi.org/10.3389/fninf.2013.00034
[2] Antolík, J., & Davison, A. P. (2018). Arkheia: Data Management and Communication for Open Computational Neuroscience. Frontiers in Neuroinformatics, 12, 6. https://doi.org/10.3389/fninf.2018.00006
 
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