Dynamic causal modelling (DCM) is a biophysically informed Bayesian framework for comparing hypotheses or network models of (neurophysiological) timeseries. It is an established procedure in the analysis of functional magnetic resonance timeseries nd is now used increasingly for the characterisation of electrophysiological measurements. There is an extensive literature on the validation of DCM ranging from face validation studies to construct validation in terms of multimodal measurements, pharmacological manipulations and psychophysical constructs; for example, predictive coding. Predictive validity has been established in studies of pathophysiology.
The anatomical and functional evidence that is summarized above suggests that spatial signals from multiple cell types in MEC or from other parallel pathways, such as the lateral division of the entorhinal cortex, might have redundant roles in sustaining a robust spatial representation in hippocampus