English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Modeling the dynamics of visuo-motor adaptation behavior with a Kalman Filter

Burge, J., Ernst, M., & Banks, M. (2006). Modeling the dynamics of visuo-motor adaptation behavior with a Kalman Filter. In 7th International Multisensory Research Forum (IMRF 2006).

Item is

Files

show Files

Locators

show

Creators

show
hide
 Creators:
Burge, J, Author
Ernst, MO1, 2, Author           
Banks, MS, Author           
Affiliations:
1Max Planck Institute for Biological Cybernetics, Max Planck Society, ou_1497794              
2Department Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Max Planck Society, Spemannstrasse 38, 72076 Tübingen, DE, ou_1497797              

Content

show
hide
Free keywords: -
 Abstract: When the introduction of a prism makes visually guided reaching biased and inaccurate, adaptation occurs to restore accuracy. Bias in everyday life usually accumulates from a series of small changes, a process well simulated with a random walk. If bias were the only source of error, recalibration would be simple: correct the last error. But reaching behavior is also subject to random error. How does the visuo-motor system balance the need to filter random error with the need to adapt to time-varying bias? We investigated whether the Kalman filter, the optimal algorithm for this problem, models the dynamics of visuo-motor adaptation. The filter predicts that adaptation rate will be determined by the relative variances of current measurements and changing bias: rate should decrease with feedback variance and increase with variance in bias. Subjects pointed rapidly with an unseen hand to a brief visual target. Visual feedback indicated the endpoint of the motor movement. Feedback variance was increased with blur. The relationship between visual feedback location and the movement endpoint was altered with a random walk. Trial-by-trial pointing was measured. Subjects performed with a high level of efficiency and responded to changes in relative variances as predicted by the Kalman filter.

Details

show
hide
Language(s):
 Dates: 2006-06
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: BibTex Citekey: BurgeEB2006
 Degree: -

Event

show
hide
Title: 7th International Multisensory Research Forum (IMRF 2006)
Place of Event: Dublin, Ireland
Start-/End Date: 2006-06-18 - 2006-06-21

Legal Case

show

Project information

show

Source 1

show
hide
Title: 7th International Multisensory Research Forum (IMRF 2006)
Source Genre: Proceedings
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: 184 Start / End Page: - Identifier: -