One of the most popular tacks taken to explain cognitive processes likens them to the operations of a digital computer. Indeed, the tasks for the cognitive scientist and the artificial intelligence scientist are often seen as indistinguishable: to understand how a machine or a brain “can store past information about the world and use that memory to abstract meaning from its percepts” (Solso, 1979, p. 425). The fact that there are machines that appear to do this, to varying degrees of success, is often taken to imply, almost by default, that cognition would have to embody the same steps in order to achieve the same results. In what folIows, we outline our objections to this attitude and briefly consider some alternatives.

Seth extends predictive processing with counterfactuals: Encoded probabilities of what would occur given a repertoire of possible (but unexecuted) actions. He thereby provides a neat mathematical formulation of the sensorimotor account of perceptual presence, i.e., of the fact that we perceive a whole object while being limited to seeing it from a perspective. Synesthetic concurrents are explained in terms of impoverished counterfactuals. I argue that this explanation misses its target, because it only accounts for a lack of objecthood. Enactive theory is better suited to explain concurrents’ lack of subjectivity veridicality. The world itself shapes experience only during veridical perception.

Recent accounts of delusions involve either top-down or bottom-up, or some hybrid version of theories that rely on internalist, brain-based, or purely belief-based approaches. My intent in this chapter is to explore an alternative explanatory framework, to raise some questions that lead in a different, externalist, and existentialist direction, and to provide a broader account that treats other factors – body, affect, social, and environmental factors – as important in the constitution of delusional realities. This account makes use of the concept of multiple realities, deriving from William James and developed by Alfred Schutz. The account does not provide a causal explanation of delusions, but aims to work out a more adequate characterization of delusions that would provide a framework for any such explanation.

Can perceptual presence be explained by counterfactually-rich predictive models linking perception and action? Considering an unusually rich range of responses to this idea has led me to (1) re-emphasize the core conceptual commitment of “predictive processing of sensorimotor contingencies” (PPSMC) to predictive model-based perception, (2) reconsider the relationship between presence and objecthood, and (3) refine the phenomenological target by differentiating between perceptual presence and the phenomenology of absence-of-presence, or “phenomenal unreality.” It turns out that this requires blue-sky thinking.

Key words: perceptual presence, objecthood, predictive processing, active inference

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 synesthesia, 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 synesthesia. Here, I describe a theory of predictive perception of sensorimotor contingencies which (1) accounts for perceptual presence in normal perception, as well as its absence in synesthesia, and (2) 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 synesthetic concurrents are hypothesized to be counterfactually poor. In addition to accounting for the phenomenology of synesthesia, 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.

Key words: Predictive coding, Presence, Sensorimotor contingencies, Veridicality, Counterfactuals, Synesthesia, Active inference, Bayesian brain.

Taking the first-person perspective (1PP) centered upon one’s own body as opposed to the third-person perspective (3PP), which enables us to take the viewpoint of someone else, is constitutive for human self-consciousness. At the underlying representational or cognitive level, these operations are processed in an egocentric reference frame, where locations are represented centered around another person’s (3PP) or one’s own perspective (1PP). To study 3PP and 1PP, both operating in egocentric frames, a virtual scene with an avatar and red balls in a room was presented from different camera viewpoints to normal volunteers (n = 11) in a functional magnetic resonance imaging experiment. The task for the subjects was to count the objects as seen either from the avatar’s perspective (3PP) or one’s own perspective (1PP). The scene was presented either from a ground view (GV) or an aerial view (AV) to investigate the effect of view on perspective taking. The factors perspective (3PP vs. 1PP) and view (GV vs. AV) were arranged in a two-factorial way. Reaction times were increased and percent correctness scores were decreased in 3PP as opposed to 1PP. To detect the neural mechanisms associated with perspective taking, functional magnetic resonance imaging was employed. Data were analyzed using SPM’99 in each subject and non-parametric statistics on the group level. Activations common to 3PP and 1PP (relative to baseline) were observed in a network of occipital, parietal, and prefrontal areas. Deactivations common to 3PP and 1PP (relative to baseline) were observed predominantly in mesial (i.e., parasagittal) cortical and lateral superior temporal areas bilaterally. Differential increases of neural activity were found in mesial superior parietal and right premotor cortex during 3PP (relative to 1PP), whereas differential increases during 1PP (relative to 3PP) were found in mesial prefrontal cortex, posterior cingulate cortex, and superior temporal cortex bilaterally. The data suggest that in addition to joint neural mechanisms, for example, due to visuospatial processing and decision making, 3PP and 1PP rely on differential neural processes. Mesial cortical areas are involved in decisional processes when the spatial task is solved from one’s own viewpoint, whereas egocentric operations from another person’s perspective differentially draw upon cortical areas known to be involved in spatial cognition.