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State-space analysis on time-varying correlations in parallel spike sequences

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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
Terms of Use
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.
Persistent DSpace Link
http://hdl.handle.net/1721.1/61621
DOI of Published Version
https://doi.org/10.1109/ICASSP.2009.4960380
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