TY - JOUR
T1 - Online Variational Inference for State-Space Models with Point-Process Observations
AU - Mangion, Andrew Zammit
AU - Yuan, Ke
AU - Kadirkamanathan, Visakan
AU - Niranjan, Mahesan
AU - Sanguinetti, Guido
PY - 2011/8
Y1 - 2011/8
N2 - We present a variational Bayesian (VB) approach for the state and parameter inference of a state-space model with point-process observations, a physiologically plausible model for signal processing of spike data. We also give the derivation of a variational smoother, as well as an efficient online filtering algorithm, which can also be used to track changes in physiological parameters. The methods are assessed on simulated data, and results are compared to expectation-maximization, as well as Monte Carlo estimation techniques, in order to evaluate the accuracy of the proposed approach. The VB filter is further assessed on a data set of taste-response neural cells, showing that the proposed approach can effectively capture dynamical changes in neural responses in real time.
AB - We present a variational Bayesian (VB) approach for the state and parameter inference of a state-space model with point-process observations, a physiologically plausible model for signal processing of spike data. We also give the derivation of a variational smoother, as well as an efficient online filtering algorithm, which can also be used to track changes in physiological parameters. The methods are assessed on simulated data, and results are compared to expectation-maximization, as well as Monte Carlo estimation techniques, in order to evaluate the accuracy of the proposed approach. The VB filter is further assessed on a data set of taste-response neural cells, showing that the proposed approach can effectively capture dynamical changes in neural responses in real time.
UR - http://www.scopus.com/inward/record.url?scp=79959658819&partnerID=8YFLogxK
U2 - 10.1162/NECO_a_00156
DO - 10.1162/NECO_a_00156
M3 - Article
SN - 1530-888X
VL - 23
SP - 1967
EP - 1999
JO - Neural Computation
JF - Neural Computation
IS - 8
ER -