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 orienta- tion 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 orienta- tion), and report the results obtained using different kernel algorithms.

Authors

• Jan Eichhorn
• Andreas Tolias
• Alexander Zien
• Malte Kuss
• Jason Weston
• Nikos Logothetis
• Bernhard Schölkopf
• Carl Rasmussen

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