Prediction on Spike Data Using Kernel Algorithms

We report and compare the performance of different learning algorithms based on data from cortical recordings. The task is to predict the orientation of visual stimuli from the activity of a population of simultaneously recorded neurons. We compare several ways of improving the coding of the input (i.e., the spike data) as well as of the output (i.e., the orientation), and report the results obtained using different kernel algorithms.

• Type: Conference
• Year: 2003
• Where: NIPS
• Authors: Jan Eichhorn, Andreas S. Tolias, Alexander Zien, Malte Kuss, Carl Edward Rasmussen, Jason Weston, Nikos Logothetis, Bernhard Schölkopf
• Keywords: Cortical Recordings, NIPS 2003, NIPS 2007, Spike Data, Visual Stimuli