I have a new ‘Discussion’ paper just out in the journal Cognitive Neuroscience. Right now there is just the target paper – eventually it will appear with published commentaries and my response. The basic idea is to bring together, in a formal theoretical framework, ideas from Bayesian predictive processing and ‘enactive’ sensorimotor theory. The new theory explains ‘perceptual presence’ in terms of the counterfactual richness of predictive representations, and it can also explain the absence of such presence in important cases like synaesthesia.
A predictive processing theory of sensorimotor contingencies: Explaining the puzzle of perceptual presence and its absence in synaesthesia
(A pre-copy-edit version can be obtained here)
ABSTRACT: Normal perception involves experiencing objects within perceptual scenes as real, as existing in the world. This property of “perceptual presence” has motivated “sensorimotor theories” which understand perception to involve the mastery of sensorimotor contingencies. However, the mechanistic basis of sensorimotor contingencies and their mastery has remained unclear. Sensorimotor theory also struggles to explain instances of perception, such as synaesthesia, that appear to lack perceptual presence and for which relevant sensorimotor contingencies are difficult to identify. On alternative “predictive processing” theories, perceptual content emerges from probabilistic inference on the external causes of sensory signals, however this view has addressed neither the problem of perceptual presence nor synaesthesia. Here, I describe a theory of predictive perception of sensorimotor contingencies which (i) accounts for perceptual presence in normal perception, as well as its absence in synaesthesia, and (ii) operationalizes the notion of sensorimotor contingencies and their mastery. The core idea is that generative models underlying perception incorporate explicitly counterfactual elements related to how sensory inputs would change on the basis of a broad repertoire of possible actions, even if those actions are not performed. These “counterfactually-rich” generative models encode sensorimotor contingencies related to repertoires of sensorimotor dependencies, with counterfactual richness determining the degree of perceptual presence associated with a stimulus. While the generative models underlying normal perception are typically counterfactually rich (reflecting a large repertoire of possible sensorimotor dependencies), those underlying synaesthetic concurrents are hypothesized to be counterfactually poor. In addition to accounting for the phenomenology of synaesthesia, the theory naturally accommodates phenomenological differences between a range of experiential states including dreaming, hallucination, and the like. It may also lead to a new view of the (in)determinacy of normal perception.