Psychomotor Predictive Processing

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Psychomotor experience can be based on what people predict they will experience, rather than on sensory inputs. It has been argued that disconnects between human experience and sensory inputs can be addressed better through further development of predictive processing theory. In this paper, the scope of predictive processing theory is extended through three developments. First, by going beyond previous studies that have encompassed embodied cognition but have not addressed some fundamental aspects of psychomotor functioning. Second, by proposing a scientific basis for explaining predictive processing that spans objective neuroscience and subjective experience. Third, by providing an explanation of predictive processing that can be incorporated into the planning and operation of systems involving robots and other new technologies. This is necessary because such systems are becoming increasingly common and move us farther away from the hunter-gatherer lifestyles within which our psychomotor functioning evolved. For example, beliefs that workplace robots are threatening can generate anxiety, while wearing hardware, such as augmented reality headsets and exoskeletons, can impede the natural functioning of psychomotor systems. The primary contribution of the paper is the introduction of a new formulation of hierarchical predictive processing that is focused on psychomotor functioning
Original languageEnglish
Article number806
Issue number7
Publication statusPublished - 24 Jun 2021
MoE publication typeA1 Journal article-refereed


  • active inference
  • critical realism
  • embodiment
  • experience
  • human-robot
  • pain
  • hierarchical predictive processing
  • predictive global neuronal workspace
  • psychomotor
  • society 5.0
  • Human–robot
  • Hierarchical predictive processing
  • Psychomotor
  • Critical realism
  • Embodiment
  • Society 5.0
  • Experience
  • Pain
  • Active inference
  • Predictive global neuronal workspace


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