Literature DB >> 21670095

Statistically optimal integration of biased sensory estimates.

Peter Scarfe1, Paul B Hibbard.   

Abstract

Experimental investigations of cue combination typically assume that individual cues provide noisy but unbiased sensory information about world properties. However, in numerous instances, including real-world settings, observers systematically misestimate properties of the world from sensory information. Two such instances are the estimation of shape from stereo and motion cues. Bias in single-cue estimates, therefore poses a problem for cue combination if the visual system is to maintain accuracy with respect to the world, particularly because knowledge about the magnitude of bias in individual cues is typically unknown. Here, we show that observers fail to take account of the magnitude of bias in each cue during combination and instead combine cues in proportion to their reliability so as to increase the precision of the combined-cue estimate. This suggests that observers were unaware of the bias in their sensory estimates. Our analysis of cue combination shows that there is a definable range of circumstances in which combining information from biased cues, rather than vetoing one or other cue, can still be beneficial, by reducing error in the final estimate.

Mesh:

Year:  2011        PMID: 21670095     DOI: 10.1167/11.7.12

Source DB:  PubMed          Journal:  J Vis        ISSN: 1534-7362            Impact factor:   2.240


  9 in total

1.  Multisensory calibration is independent of cue reliability.

Authors:  Adam Zaidel; Amanda H Turner; Dora E Angelaki
Journal:  J Neurosci       Date:  2011-09-28       Impact factor: 6.167

2.  Humans use predictive kinematic models to calibrate visual cues to three-dimensional surface slant.

Authors:  Peter Scarfe; Andrew Glennerster
Journal:  J Neurosci       Date:  2014-07-30       Impact factor: 6.167

3.  Effective integration of serially presented stochastic cues.

Authors:  Mordechai Z Juni; Todd M Gureckis; Laurence T Maloney
Journal:  J Vis       Date:  2012-08-21       Impact factor: 2.240

4.  Computational characterization of visually induced auditory spatial adaptation.

Authors:  David R Wozny; Ladan Shams
Journal:  Front Integr Neurosci       Date:  2011-11-04

Review 5.  A review of human sensory dynamics for application to models of driver steering and speed control.

Authors:  Christopher J Nash; David J Cole; Robert S Bigler
Journal:  Biol Cybern       Date:  2016-04-16       Impact factor: 2.086

6.  Experimentally disambiguating models of sensory cue integration.

Authors:  Peter Scarfe
Journal:  J Vis       Date:  2022-01-04       Impact factor: 2.240

7.  Intra-Auditory Integration Improves Motor Performance and Synergy in an Accurate Multi-Finger Pressing Task.

Authors:  Kyung Koh; Hyun Joon Kwon; Yang Sun Park; Tim Kiemel; Ross H Miller; Yoon Hyuk Kim; Joon-Ho Shin; Jae Kun Shim
Journal:  Front Hum Neurosci       Date:  2016-06-08       Impact factor: 3.169

8.  Intra-auditory integration between pitch and loudness in humans: Evidence of super-optimal integration at moderate uncertainty in auditory signals.

Authors:  Kyung Koh; Hyun Joon Kwon; Tim Kiemel; Ross H Miller; Yang Sun Park; Min Joo Kim; Young Ha Kwon; Yoon Hyuk Kim; Jae Kun Shim
Journal:  Sci Rep       Date:  2018-09-12       Impact factor: 4.379

9.  Central tendency biases must be accounted for to consistently capture Bayesian cue combination in continuous response data.

Authors:  Stacey Aston; James Negen; Marko Nardini; Ulrik Beierholm
Journal:  Behav Res Methods       Date:  2021-07-13
  9 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.