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Action and behavior: a free-energy formulation

Overview of attention for article published in Biological Cybernetics, February 2010
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 504)
  • High Attention Score compared to outputs of the same age (89th percentile)
  • High Attention Score compared to outputs of the same age and source (85th percentile)

Mentioned by

blogs
1 blog
twitter
1 tweeter
googleplus
1 Google+ user

Citations

dimensions_citation
272 Dimensions

Readers on

mendeley
691 Mendeley
citeulike
4 CiteULike
Title
Action and behavior: a free-energy formulation
Published in
Biological Cybernetics, February 2010
DOI 10.1007/s00422-010-0364-z
Pubmed ID
Authors

Karl J. Friston, Jean Daunizeau, James Kilner, Stefan J. Kiebel

Abstract

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.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 691 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 16 2%
United States 14 2%
France 10 1%
Germany 7 1%
Switzerland 6 <1%
Portugal 4 <1%
Japan 4 <1%
Spain 3 <1%
Canada 3 <1%
Other 17 2%
Unknown 607 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 186 27%
Researcher 129 19%
Student > Master 92 13%
Student > Bachelor 48 7%
Professor > Associate Professor 45 7%
Other 190 27%
Unknown 1 <1%
Readers by discipline Count As %
Psychology 171 25%
Neuroscience 109 16%
Computer Science 96 14%
Agricultural and Biological Sciences 69 10%
Unspecified 64 9%
Other 181 26%
Unknown 1 <1%

Attention Score in Context

This research output has an Altmetric Attention Score of 12. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 24 November 2017.
All research outputs
#1,115,375
of 12,184,158 outputs
Outputs from Biological Cybernetics
#16
of 504 outputs
Outputs of similar age
#14,587
of 141,478 outputs
Outputs of similar age from Biological Cybernetics
#1
of 7 outputs
Altmetric has tracked 12,184,158 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 504 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 141,478 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 89% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them