Ellis, Andrew W.; Mast, Fred W. (24 January 2014). A Hierarchical Bayesian Model for Measuring Motion Adaptation (Unpublished). In: Swiss Society for Neuroscience Annual Meeting 2014. Bern, Switzerland. 24.-25.01.2014.
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poster_ssn_201401.pdf - Accepted Version Available under License BORIS Standard License. Download (1MB) | Preview |
Previous research has shown that motion imagery draws on the same neural circuits that are involved in perception of motion, thus leading to a motion aftereffect (Winawer et al., 2010). Imagined stimuli can induce a similar shift in participants’ psychometric functions as neural adaptation due to a perceived stimulus. However, these studies have been criticized on the grounds that they fail to exclude the possibility that the subjects might have guessed the experimental hypothesis, and behaved accordingly (Morgan
et al., 2012). In particular, the authors claim that participants can adopt arbitrary response criteria, which results in similar changes of the central tendency μ of psychometric curves as those shown by Winawer et al. (2010).
Item Type: |
Conference or Workshop Item (Poster) |
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Division/Institute: |
07 Faculty of Human Sciences > Institute of Psychology > Cognitive Psychology, Perception and Methodology |
UniBE Contributor: |
Ellis, Andrew, Mast, Fred |
Subjects: |
100 Philosophy > 150 Psychology |
Funders: |
[4] Swiss National Science Foundation |
Projects: |
[1207] Mental Imagery and Perceptual Learning |
Language: |
English |
Submitter: |
Andrew William Ellis |
Date Deposited: |
19 Jun 2014 10:58 |
Last Modified: |
05 Dec 2022 14:32 |
BORIS DOI: |
10.7892/boris.49470 |
URI: |
https://boris.unibe.ch/id/eprint/49470 |
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