Action and behavior: a free-energy formulation

We have previously tried to explain perceptual inference and learning under a free-energy principle that pursues Helmholtz's agenda to understand the brain in terms of energy minimization. It is fairly easy to show that making inferences about the causes of sensory data can be cast as the minim...

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Veröffentlicht in:Biological cybernetics Jg. 102; H. 3; S. 227 - 260
Hauptverfasser: Friston, Karl J, Daunizeau, Jean, Kilner, James, Kiebel, Stefan J
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Berlin/Heidelberg Berlin/Heidelberg : Springer-Verlag 01.03.2010
Springer-Verlag
Springer Nature B.V
Schlagworte:
Afferent Pathways - physiology
Animals
Bayes Theorem
Bayesian
Bayesian analysis
Behavior - physiology
Bioinformatics
Biomedical and Life Sciences
Biomedicine
Brain
Brain - physiology
Complex Systems
Computational
Computer Appl. in Life Sciences
Computer Simulation
Control
Cybernetics
Energy
Entropy
Hierarchical
Humans
Learning - physiology
Models, Neurological
Motor
Motor ability
Motor Activity - physiology
Neurobiology
Neurosciences
Original Paper
Perception - physiology
Priors
Sensory perception
Hierarchical
Control
Priors
Motor
Computational
Bayesian
ISSN:0340-1200, 1432-0770, 1432-0770
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Zusammenfassung:We have previously tried to explain perceptual inference and learning under a free-energy principle that pursues Helmholtz's agenda to understand the brain in terms of energy minimization. It is fairly easy to show that making inferences about the causes of sensory data can be cast as the minimization of a free-energy bound on the likelihood of sensory inputs, given an internal model of how they were caused. In this article, we consider what would happen if the data themselves were sampled to minimize this bound. It transpires that the ensuing active sampling or inference is mandated by ergodic arguments based on the very existence of adaptive agents. Furthermore, it accounts for many aspects of motor behavior; from retinal stabilization to goal-seeking. In particular, it suggests that motor control can be understood as fulfilling prior expectations about proprioceptive sensations. This formulation can explain why adaptive behavior emerges in biological agents and suggests a simple alternative to optimal control theory. We illustrate these points using simulations of oculomotor control and then apply to same principles to cued and goal-directed movements. In short, the free-energy formulation may provide an alternative perspective on the motor control that places it in an intimate relationship with perception.
Bibliographie:http://dx.doi.org/10.1007/s00422-010-0364-z
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ISSN:0340-1200
1432-0770
1432-0770
DOI:10.1007/s00422-010-0364-z