The representation of neural data using visualization
Information Visualization
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The current ability to record neural activity within thebrains of mammals has led to the production of a largebody of experimental data. The analysis andcomprehension of this data is key to the understanding ofmany basic brains functions, for example learning andmemory.The main constituent of this data is multi-dimensionalspike train recordings. As the analysis of these datasets, bytraditional means, becomes more complex and timeconsuming the need for better methods of data analysisincreases.This paper presents an innovative method for analysis ofthe relationships within large multi-dimensional spiketrain datasets. This method, called the Correlation Grid,'is based on the Information Visualisation principles;overview the data, filter and zoom the data and obtaindetails-on-demand [1]. The features of the CorrelationGrid are described, including filtering and statisticalsorting methods.