The representation of neural data using visualization

Abstract

Currently, the focus of research within Information Visualisation is steering towards genomic data visualisation [21] due to the level of activity that the Human Genome Project [11] has generated. However, the Human Brian project [10], renowned within Neuroinformatics, is equally challenging and exciting. Its main aim is to increase current understanding of brain function such as memory, learning, attention, emotions and consciousness. It is understood that this task will require the “integration of information from the level of the gene to the level of behaviour”. The work presented in this paper focuses on the visualisation of neural data. More specifically, the data being analysed is multi-dimensional spike train data. Traditional methods, such as the ‘raster plot’ and the ‘crosscorrelogram’, are still useful but they do not scale up for larger assemblies of neurons. In this paper, a new innovative method called the Tunnel is defined. Its design is based on the principles of Information Visualisation; overview the data, zoom and filter data, data details on demand [18]. The features of this visualisation environment are described. This includes data filtering, navigation and a ‘flat map’ overview facility. Additionally, a ‘coincidence overlay map’ is presented. This map washes the Tunnel with colour, which encodes the coincidence of spikes.

DOI: 10.1057/palgrave.ivs.9500071

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Cite this paper

@article{Walter2004TheRO, title={The representation of neural data using visualization}, author={Martin A. Walter and Liz J. Stuart and Roman Borisyuk}, journal={Information Visualization}, year={2004}, volume={3}, pages={245-256} }