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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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eacooper/Bayesian3DMotion
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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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