We address the issue of the normativity of representation and how Grush might address it for emulations as constituting representations. We then proceed to several more detailed issues concerning the learning of emulations, a possible empirical counterexample to Grush's model, and the choice of Kalman filters as the form of model-based control.

In his article Grush proposes a potentially useful framework for explaining motor control, imagery, and perception. In our commentary we will address two issues that the model does not seem to deal with appropriately: one concerns motor control, and the other, the visual and motor imagery domains. We will consider these two aspects in turn.

Although the application of the emulation model to the control of simple positioning movements is relatively straightforward, extending the scheme to actions requiring multisegmental, interlimb coordination complicates matters a bit. Special consideration of the demands in this case, both on sensory processing and on the process model (two key elements of the Kalman filter), are discussed.

Mental representations are more than emulations. Different types of representations, including external representations, various mental models (distorted and abstract), and emulative models, can all play important roles in human cognition. To explain cognitive performance in a specific task, a systematic analysis of the underlying representational structures and their interactions is needed.

Many of Grush's arguments should apply equally to animals with small brains, for which the capacity to internally model the body and environment must be limited. The dilemma may be solved by making only very approximate predictions, or only attempting to derive a “high-level” prediction from “high-level” output. At the extreme, in either case, the “emulation” step becomes trivial.

The target article distinguishes between modal and amodal emulators (the former predict future sensory states from current sensory states and motor actions, the latter operate on more abstract descriptions of the environment), and motor and environment emulators (the former predict the results of one's own actions, the latter predict all changes in the environment). I question the applicability of modal emulators, and the generalization to environment emulators.

“Articulate models” subservient to formal intelligence are imagined to be heterarchies of automata capable of performing the “symbolic (quasi-spatial) syntheses” of Luria (1973), where “quasi-spatial” points to the abstract core of spatiality: the symbol productions, combinations, and substitutions of algebraic reckoning. The alleged cognitive role of internal “topographic images” and of “efference copies” is confronted with this background and denied.

First, I note three questions that need further exploration: how fast the emulator operates, compared to the real-time events it models; what exactly perceptual emulation, with no motor component, consists of; and whether images are equivalent to raw sensations. Next, I propose that Grush's framework can explain the role of motor activation in processing “imitable” stimuli.

The emulation theory of representation articulated in the target article is further explained and explored in this response to commentaries. Major topics include: the irrelevance of equilibrium-point and related models of motor control to the theory; clarification of the particular sense of “representation” which the emulation theory of representation is an account of; the relation between the emulation framework and Kalman filtering; and addressing the empirical data considered to be in conflict with the emulation theory. In addition, I discuss the further empirical support for the emulation theory provided by some commentators, as well as a number of suggested theoretical applications.