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Classification and Visualization of Neural Patterns Using Subspace Analysis Statistical Methods
Xia, Jun Osan, Marius Titan, Emilia Nicolae, Riana Osan, Remus
Xia, Jun
Osan, Marius
Titan, Emilia
Nicolae, Riana
Osan, Remus
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Abstract
The size and complexity of neural data is increasing at a dramatic pace due to rapid advances in experimental technologies. As a result, the data analysis techniques are shifting their focus from single-units to neural populations. The goal is to investigate complex temporal and spatial patterns, as well as to present the results in an intuitive way, allowing for detection and monitoring of relevant neural patterns.
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<p>This poster presentation was originally published in <em><a href="http://www.biomedcentral.com/bmcneurosci" title="BMC Neuroscience">BMC Neuroscience</a></em>. It is posted here with the permission of the author.</p>
<p>Copyright © 2012 Xia et al; licensee BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.</p>
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2012-01-01
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Keywords
neural data, classification, visualization, subspace analysis
Citation
Xia <em>et al.</em>: Classification and visualization of neural patterns using subspace analysis statistical methods. <em>BMC Neuroscience</em> 2012 13(Suppl 1):P74. doi: 10.1186/1471-2202-13-S1-P74