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An important question in information processing is the extent to which neural ÿring patterns remain consistent while processing representations. Transient changes in representational consistency can provide clues to the dynamics of neural processing. We present a generalized framework for measuring the consistency of a neuronal representation that does not require explicit knowledge of the parameters encoded by the ensemble. It requires only neuronal ensembles and a training set of neuronaldoi:10.1016/s0925-2312(04)00023-2 fatcat:lb6zok2slfeavdfhdkhhjpplru