Investigators at Boston University Target Neural Computation

摘要

According to the authors of recent research published in the journal Neural Computation, "We develop a ngeneral likelihood-based framework for use in the estimation of neural firing rates, which is designed to nchoose the temporal smoothing parameters that maximize the likelihood of missing data. This general nframework is algorithm-independent and thus can be applied to a multitude of established methods for nfiring rate or conditional intensity estimation."