undefined

Psychomotor Predictive Processing

Publiceringsår

2021

Upphovspersoner

Fox, Stephen

Abstrakt

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
Visa mer

Organisationer och upphovspersoner

Publikationstyp

Publikationsform

Artikel

Moderpublikationens typ

Tidning

Artikelstyp

En originalartikel

Målgrupp

Vetenskaplig

Kollegialt utvärderad

Kollegialt utvärderad

UKM:s publikationstyp

A1 Originalartikel i en vetenskaplig tidskrift

Publikationskanalens uppgifter

Journal

Entropy

Volym

23

Nummer

7

Artikelnummer

806

Publikationsforum

55320

Publikationsforumsnivå

1

Öppen tillgång

Öppen tillgänglighet i förläggarens tjänst

Ja

Öppen tillgång till publikationskanalen

Helt öppen publikationskanal

Licens för förläggarens version

CC BY

Parallellsparad

Nej

Publiceringsavgift för öppen tillgång €

1500

Betalningsår för den öppen tillgång publiceringsavgiften

2021

Övriga uppgifter

Vetenskapsområden

Fysik; Medie- och kommunikationsvetenskap

Nyckelord

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Språk

engelska

Internationell sampublikation

Nej

Sampublikation med ett företag

Nej

DOI

10.3390/e23070806

Publikationen ingår i undervisnings- och kulturministeriets datainsamling

Ja