Abstract

Recent advances in “developmental” approach (combining experimental study with computational modelling) of neural networks produces increasingly large data sets, in both complexity and size. This poses a significant challenge in analyzing, visualizing and understanding not only the spatial structure but also the behavior of such networks. This paper describes a Virtual Reality application for visualization of two biologically accurate computational models that model the anatomical structure of a neural network comprised of 1,500 neurons and over 80,000 connections. The visualization enables a user to observe the complex spatio-temporal interplay between seven unique types of neurons culminating in an observable swimming pattern. We present a detailed description of the design approach for the virtual environment, based on a set of initial requirements, followed up by the implementation and optimization steps. Lastly, the results of a pilot usability study are being presented on how confident participants are in their ability to understand how the alternating firing pattern between the two sides of the tadpole’s body generate swimming motion.

DOI

10.1007/s10055-020-00431-z

Publication Date

2020-02-28

Publication Title

Virtual Reality

ISSN

1359-4338

Embargo Period

2021-03-14

Organisational Unit

School of Art, Design and Architecture

Keywords

Data visualization, Neuroscience, Virtual Reality, Visualization, Scientific Visualization, Immersive

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