State-space analysis on time-varying correlations in parallel spike sequences
Name
Shimazaki-2009-State-space analysis on time-varying correlations in parallel spike sequences.pdf
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Author(s) • • •
Shimazaki, Hideaki
Amari, Shun-ichi
Brown, Emery N.
Grun, Sonja
Date Issued
April 2009
Journal
IEEE International Conference on Acoustics, Speech, and Signal Processing : [proceedings] (ICASSP)
Publisher
Institute of Electrical and Electronics Engineers
Citation
Shimazaki, H. et al. “State-space analysis on time-varying correlations in parallel spike sequences.” Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on. 2009. 3501-3504. © 2009, IEEE
Version
Final published version
Abstract
A state-space method for simultaneously estimating time-dependent rate and higher-order correlation underlying parallel spike sequences is proposed. Discretized parallel spike sequences are modeled by a conditionally independent multivariate Bernoulli process using a log-linear link function, which contains a state of higher-order interaction factors. A nonlinear recursive filtering formula is derived from a log-quadratic approximation to the posterior distribution of the state. Together with a fixed-interval smoothing algorithm, time-dependent log-linear parameters are estimated. The smoothed estimates are optimized via EM-algorithm such that their prior covariance matrix maximizes the expected complete data log-likelihood. In addition, we perform model selection on the hierarchical log-linear state-space models to avoid over-fitting. Application of the method to simultaneously recorded neuronal spike sequences is expected to contribute to uncover dynamic cooperative activities of neurons in relation to behavior.
MIT Department
Harvard University--MIT Division of Health Sciences and Technology
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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DOI of Published Version
https://doi.org/10.1109/ICASSP.2009.4960380