By Topic

Kernel Analysis Of Multi-neuronal Spike Trains

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Masaki Nomura ; Department of Applied Analysis and Complex Dynamical Systems, Graduate School of Informatics, Kyoto University, Kyoto 606-8501, Japan; CREST, Japan Science and Technology Corporation, Kawaguchi, Saitama 332-0012, Japan ; Yoshio Sakurai ; Toshio Aoyagi

We recorded multi-neuronal spike activities from hippocampal CA1 regions of rats performing a conditional discrimination task. Separating single unit activities from multi-neuronal spike activities, we obtained spike count data. Then, we calculated kernel matrices from the spike count data. The kernel we used, called Spikernel, measures the similarities among spike count data. We performed the kernel k-means clustering and the kernel PCA with the kernel matrices. The data can be separated into two clusters, which represent the behaviors of rats. Our results suggest that spike activities of suitable length are crucial to predict the behaviors of rats.

Published in:

Complex Medical Engineering, 2007. CME 2007. IEEE/ICME International Conference on

Date of Conference:

23-27 May 2007