Neuronify: An Educational Simulator for Neural Circuits
Abstract
Time: 11:30 - 11:50 Neurons are cells in the brain that are able to rapidly change the electric field across their cell membrane. These changes allow neurons to communicate with each other and is the basis for the complex... [ view full abstract ]
Time: 11:30 - 11:50
Neurons are cells in the brain that are able to rapidly change the electric field across their cell membrane. These changes allow neurons to communicate with each other and is the basis for the complex computations in the brain. Understanding how neurons communicate and the properties of neuronal networks is essential for neuroscience students. Traditionally, students draw networks with pen and paper and qualitatively deduce features of the network by analyzing the static drawings. Here, we present Neuronify, an app that allows students to draw the same networks on a computer or mobile device and run dynamic simulations without programming. The students can test their analysis by running the network and check their predictions against the outcome.
Educational software (apps) can improve science education by providing an interactive way of learning about complicated topics that are hard to explain with text and static illustrations. Such software is readily available in many areas of natural science such as physics and electrical engineering. However, few educational apps are available for simulation of neural networks. Neuronify allows the user to easily create and explore neural networks in a plug-and-play simulation environment. The user can drag and drop network elements such as neurons, electrical stimulation tools and recording devices. The components can then easily be connected to one another.
Building intuition for how neurons and neural networks behave has been a top priority in designing Neuronify. We aim to provide a low entry point to simulation-based neuroscience. Most undergraduate students do not have the computational experience to create their own neural simulator. Neuronify offers them an opportunity to build and experiment with neural networks in a graphical and easy-to-understand interface. By playing around with the networks, the students can develop a good understanding of their properties.
To facilitate the use of Neuronify in teaching, a set of premade common network motifs is provided, performing functions such as input summation and detection of direction of stimulus movement. Neuronify is developed in C++ and QML using the cross-platform application framework Qt. It has been downloaded more than 30,000 times since its launch and is available on smart phones (Android, iOS), tablet computers as well personal computers (Windows, Mac, Linux).
Authors
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Svenn-Arne Dragly
(University of Oslo)
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Milad Hobbi Mobarhan
(University of Oslo)
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Andreas Våvang Solbrå
(University of Oslo)
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Simen Tennøe
(University of Oslo)
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Anders Hafreager
(University of Oslo)
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Anders Malthe-Sørenssen
(University of Oslo)
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Marianne Fyhn
(University of Oslo)
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Torkel Hafting
(University of Oslo)
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Gaute Einevoll
(Norwegian University of Life Sciences)
Topic Area
Education in Computational Science and Engineering
Session
» Education in CSE - part I (10:40 - Tuesday, 24th October, 12th floor - Stratos)