Assessment of synchrony in multiple neural spike trains using loglinear point process models

Assessment of synchrony in multiple neural spike trains using loglinear point process models

10.1214/10-AOAS429

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Bibliographic Details
Main Authors: Kass, R.E., Kelly, R.C., Loh, W.-L.
Other Authors: STATISTICS & APPLIED PROBABILITY
Format: Article
Published: 2014
Subjects:
Discrete-time approximation
Loglinear model
Marked process
Nonstationary point process
Simultaneous events
Spike train
Synchrony detection
Online Access:http://scholarbank.nus.edu.sg/handle/10635/105013
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Institution: National University of Singapore
Description
Summary:10.1214/10-AOAS429

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