Combining Order Statistics with Bayes Theorem for Millisecond-by-Millisecond Decoding of Spike Trains
Combining Order Statistics with Bayes Theorem for Millisecond-by-Millisecond Decoding of Spike Trains
This chapter, which discusses the application of order statistics with Bayes theorem in decoding instant-by-instant neuronal spike trains, first considers the response latency or the time at which the neuronal response to a stimulus begins. Statistics are then developed to decode the responses based on the first spike and then consider each subsequent spike as the “first next spike.” Order statistics describe the distribution of a spike time when the total number of spikes is known. The probability of the stimulus given the outcome of whether or not a spike has arrived can be determined using the Bayes theorem.
Keywords: order statistics, Bayes theorem, response latency, neuronal response, spike
MIT Press Scholarship Online requires a subscription or purchase to access the full text of books within the service. Public users can however freely search the site and view the abstracts and keywords for each book and chapter.
Please, subscribe or login to access full text content.
If you think you should have access to this title, please contact your librarian.
To troubleshoot, please check our FAQs, and if you can't find the answer there, please contact us.