English
 
User Manual Privacy Policy Disclaimer Contact us
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Bayesian Integration in Force Estimation

Kording, K., Ku, S.-P., & Wolpert, D. (2004). Bayesian Integration in Force Estimation. Journal of Neurophysiology, 92(5), 3161. doi:10.​1152/​jn.​00275.​2004.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D757-A Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0013-D758-8
Genre: Journal Article

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Kording, KP, Author
Ku, S-P1, Author              
Wolpert, DM, Author
Affiliations:
1Department Physiology of Cognitive Processes, Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497798              

Content

show
hide
Free keywords: -
 Abstract: When we interact with objects in the world, the forces we exert are finely tuned to the dynamics of the situation. As our sensors do not provide perfect knowledge about the environment, a key problem is how to estimate the appropriate forces. Two sources of information can be used to generate such an estimate: sensory inputs about the object and knowledge about previously experienced objects, termed prior information. Bayesian integration defines the way in which these two sources of information should be combined to produce an optimal estimate. To investigate whether subjects use such a strategy in force estimation, we designed a novel sensorimotor estimation task. We controlled the distribution of forces experienced over the course of an experiment thereby defining the prior. We show that subjects integrate sensory information with their prior experience to generate an estimate. Moreover, subjects could learn different prior distributions. These results suggest that the CNS uses Bayesian models when estimating force requirements.

Details

show
hide
Language(s):
 Dates: 2004-11
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: Journal of Neurophysiology
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 92 (5) Sequence Number: - Start / End Page: 3161 Identifier: -