NeurIPS 2020

A new inference approach for training shallow and deep generalized linear models of noisy interacting neurons

Meta Review

This paper presents a novel methodology to fit generalized linear models to neural data, overcoming the various limitations of existing models which are prevalent in the literature. The paper received 4 thoughtful and thorough reviews. There was significant discussion following the author response. One reviewer found that the authors did not provide significant intuition or evidence why their method prevents "runaway excitation". However, the other three reviewers believed this was secondary and argued strongly for acceptance, considering this a significant advance in GLM modeling of neural data.