Ideonamic: An integrative computational dynamic model of ideomotor learning and effect-based action control.
Psychol Rev
; 131(1): 79-103, 2024 Jan.
Article
em En
| MEDLINE
| ID: mdl-38346045
ABSTRACT
According to ideomotor theory, actions are represented, controlled, and retrieved in terms of the perceptual effects that these actions experientially engender. When agents perform a motor action, they observe its subsequent perceptual effects and establish action-effect associations. When they want to achieve this effect at a later time, they use the action-effect associations to preactivate the action by internally activating the effect representation. Ideomotor theory has received extensive support in recent years. To capture this particular effect-based view on action control and goal-directed behavior, we developed IDEONAMIC, an integrative computational model based on dynamic field theory that represents the specific components of the action control process as dynamic neural fields. We show that IDEONAMIC applies conveniently to different types of experimental ideomotor settings, simulates key findings, generates novel predictions from the dynamics of data, and allows reapproaching the underlying cognitive mechanisms from a computational point of view. We encourage the application of IDEONAMIC to more types of ideomotor settings to gain insights into effect-based action control. The model is available at https//osf.io/hbc6n. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Desempenho Psicomotor
/
Aprendizagem
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Psychol Rev
Ano de publicação:
2024
Tipo de documento:
Article
País de publicação:
Estados Unidos