  Using a noise covariance model based on a single Kronecker product of spatial
and temporal covariance in the spatiotemporal analysis of MEG data was
demonstrated to provide improvement in the results over that of the commonly
used diagonal noise covariance model. In this paper we present a model that is
a generalization of all of the above models. It describes models based on a
single Kronecker product of spatial and temporal covariance as well as more
complicated multi-pair models together with any intermediate form expressed as
a sum of Kronecker products of spatial component matrices of reduced rank and
their corresponding temporal covariance matrices. The model provides a
framework for controlling the tradeoff between the described complexity of the
background and computational demand for the analysis using this model. Ways to
estimate the value of the parameter controlling this tradeoff are also
discussed
