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Data and example code from Rokers, Fulvio, Pillow & Cooper. "Systematic Misperceptions of 3-D Motion Explained by Bayesian Inference" Journal of Vision 2018, Vol.18, 23. doi:10.1167/18.3.23

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Systematic Misperceptions of 3D Motion Explained by Bayesian Inference.
B. Rokers, J.M. Fulvio, J. Pillow and E.A Cooper
Journal of Vision, 2018
Vol.18, 23. doi:10.1167/18.3.23


(1) Data

Files for each study in folder contain trial data in columns:

1.  subject number
2.  viewing distance in cm
3.  target contrast (Michelson)
4.  stimulus eccentricity in degrees (left is negative)
5.  stimulus direction (deg) - 0 == rightward, CCW to 360
6.  response direction (deg) - 0 == rightward, CCW to 360
7.  stimulus speed in x (cm/s leftward is negative)
8.  stimulus speed in z (cm/s towards is negative)

(2) Scripts

do_motion_uncertainty: calculation of uncertainty in motion estimation for different locations in visual space

do_model_fit: example model fitting to one participant’s data

do_analyze_exp[1/2/3]: load and plot lateral bias and direction confusions from each experiment

Requires Philipp Berens’ CircStat toolbox in path:
https://github.com/circstat/circstat-matlab

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Data and example code from Rokers, Fulvio, Pillow & Cooper. "Systematic Misperceptions of 3-D Motion Explained by Bayesian Inference" Journal of Vision 2018, Vol.18, 23. doi:10.1167/18.3.23

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