Estimation of Sparse Dynamical Model of Neural Functional Connectivity Using Group Lasso and Laguerre Basis Functions
نویسندگان
چکیده
2This paper describes a novel method for estimating the sparse dynamical model of neural functional connectivity. This method combines the group Lasso and Laguerre expansion techniques to achieve model sparsity. It has been applied to the identification of neural functional connectivity of hippocampal CA3-CA1. Results show that the sparse model out-performs the full model estimated with the standard maximum likelihood method in terms of out-of-sample prediction accuracy.
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