Before revision:  Here we show that a broad class of high-dimensional linear networks of recurrently connected units exhibits the properties needed for transient coding. We first identify a general criterion that distinguishes two classes of networks depending on properties of the connectivity matrix : networks in which all inputs lead to weak, decaying transients, and networks in which specific inputs elicit strongly amplified transient responses and are mapped onto orthogonal output states during the dynamics.
After revision:  Here we show that a broad class of high-dimensional linear networks of recurrently connected units . We start by reviewing a well-known result that leads to a distinction between two classes of networks depending on properties of the connectivity matrix : networks in which all inputs lead to weak, decaying transients, and networks in which specific inputs elicit strongly amplified transient responses and are mapped onto orthogonal output states during the dynamics.