Project Leaders

Dr. Paolo Pretto 
Phone: +49 7071 601-644 
Fax: +49 7071 601-616 
paolo.pretto[at]tuebingen.mpg.de

Dr. Ksander de Winkel
Phone: +49 7071 601-643
Fax: +49 7071 601-616 
Opens window for sending emailksander.dewinkel[at]tuebingen.mpg.de

News

February 13, 2017
Two new papers published in PLoS ONE:
 
- Nesti A, de Winkel K, Bülthoff HH (2017) Accumulation of Inertial Sensory Information in the Perception of Whole Body Yaw Rotation.
(Opens external link in new windowPLoS ONE 12(1): e0170497)
 
- de Winkel KN, Katliar M, Bülthoff HH (2017) Causal Inference in Multisensory Heading Estimation.
(Opens external link in new windowPLoS ONE 12(1): e0169676)
 
January 30, 2017
Opens external link in new window27th Oculomotor Meeting - Program
The Program of the 27th Oculomotor meeting (3-4 Feb) is now available for download.
 
October 25, 2016
Opens internal link in current window27th Oculomotor Meeting
The website for the 27th Oculomotor meeting - held 3-4 February at our institute - is online! Follow the link above.
 
September 9, 2016
Opens external link in new windowDriving Simulation Conference 2016 VR
Joost Venrooij presented a paper and Paolo Pretto delivered a keynote presentation at the Driving Simulation Conference 2016 VR in Paris, France. The paper was titled: "Comparison between filter- and optimization-based motion cueing in the Daimler Driving Simulator". The keynote was titled: "Twenty years of DSC: a review of driver's motion perception research".

Opens internal link in current windowNews Archive

Five most recent Publications

Nooij SAE, Pretto P, Oberfeld D, Hecht H and Bülthoff HH (April-2017) Vection is the main contributor to motion sickness induced by visual yaw rotation: Implications for conflict and eye movement theories PLoS ONE 12(4) 1-19.
Nesti A, de Winkel K and Bülthoff HH (January-2017) Accumulation of Inertial Sensory Information in the Perception of Whole Body Yaw Rotation PLoS ONE 12(1) 1-14.
de Winkel KN, Katliar M and Bülthoff HH (January-2017) Causal Inference in Multisensory Heading Estimation PLoS ONE 12(1) 1-20.
Miermeister P, Lächele M, Boss R, Masone C, Schenk C, Tesch J, Kerger M, Teufel H, Pott A and Bülthoff HH (October-2016) The CableRobot Simulator: Large Scale Motion Platform Based on Cable Robot Technology, IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016), IEEE, Piscataway, NJ, USA, 3024-3029.
Venrooij J, Cleij D, Katliar M, Pretto P, Bülthoff HH, Steffen D, Hoffmeyer FW and Schöner H-P (September-8-2016) Comparison between filter- and optimization-based motion cueing in the Daimler Driving Simulator, DSC 2016 Europe: Driving Simulation Conference & Exhibition, 31-38.
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Multi-sensory self-motion perception


In order to gain an understanding of how our brain constructs perceptions of self-motion, we perform fundamental psychophysical experiments. In these experiments, we make use of our motion simulator facilities to present human participants with various kinds of visual and physical motion stimuli, and we inquire about how the participants perceive these stimuli. For example, we investigate how sensitive we are to motions by determining the smallest motion intensity that we can still perceive, and the smallest difference needed to distinguish between motions. In these experiments, we vary all possible characteristics of the motions, in order to determine how our perception is affected.
 

 

We aim at extending the current knowledge on self-motion perception by performing experiments in conditions that cover the richness and complexity of real-life situations. In our experiments, we obtain various measures of self-motion perceptions while we manipulate: (I) motion directions, frequencies and intensities; (II) the source(s) of sensory information (unisensory visual and inertial stimulation, or multisensory visual-inertial stimulation); (III) the degree to which visual and inertial information are in agreement. Experimental data are used to assess the tenability of psychophysical models designed to capture the nature of these perceptions.

Sensitivity measures such as differential thresholds (i.e. the smallest perceivable change in motion intensity) are estimated using various (adaptive) psychophysical methods. We use behavioral tasks to measure participants' perceptions both objectively (e.g., by using forced-choice decision tasks, direct estimation methods, and by assessing response times), and subjectively (e.g., by verbal reports). We also explore the use of neuroimaging methods to reveal neural correlates of self-motion perceptions.

Our previous findings have shown that human differential thresholds (the ability to tell motions apart on the basis of any particular quality) increase with stimulus intensity, following a trend that is consistent with Stevens' power laws of perception (Stevens, 1957). Similar trends are found for visual only, inertial only and congruent visual-inertial cues (see Figure below).

In recent work, we assessed how our brain deals with intersensory discrepancies: how is the perception of self-motion affected when the motion that we see and feel is not in agreement? The results of these studies are consistent with Causal Inference models of perception (Körding et al., 2007), showing that our brain fuses information from the visual and inertial sensory systems when the information provided by the different systems is in close agreement, but that it tends to segregate these sources of information when there is only little agreement.

Stevens, S.S. (1957). "On the psychophysical law". Psychological Review. 64 (3): 153-181
Körding KP, Beierholm U, Ma WJ, Quartz S, Tenenbaum JB, Shams L (2007) Causal Inference in Multisensory Perception. PLoS ONE 2(9): e943
Visualization of the posterior probability that any combination of a visual (θV)and an inertial (θI) heading stimulus will be attributed to a common cause (PT(CjxV, xI), as a function of the duration of the motion profiles in seconds (T) (taken with permission from: de Winkel, Katliar, & Bülthoff, 2017).

Relevant publications

7. Nesti A, de Winkel K and Bülthoff HH (January-2017) Accumulation of Inertial Sensory Information in the Perception of Whole Body Yaw Rotation PLoS ONE 12(1) 1-14.
6. de Winkel KN, Katliar M and Bülthoff HH (January-2017) Causal Inference in Multisensory Heading Estimation PLoS ONE 12(1) 1-20.
5. Nooij SAE, Nesti A, Bülthoff HH and Pretto P (August-2016) Perception of rotation, path, and heading in circular trajectories Experimental Brain Research 234(8) 2323–2337.
4. Nesti A, Nooij SAE, Losert M, Bülthoff HH and Pretto P (May-2016) Roll rate perceptual thresholds in active and passive curve driving simulation Simulation: Transactions of the Society for Modeling and Simulation International 92(5) 417-426.
3. Nesti A, Beykirch KA, Pretto P and Bülthoff HH (December-2015) Human discrimination of head-centred visual–inertial yaw rotations Experimental Brain Research 233(12) 3553-3564.
2. de Winkel KN, Katliar M and Bülthoff HH (May-2015) Forced Fusion in Multisensory Heading Estimation PLoS ONE 10(5) 1-20.
1. Nesti A, Beykirch KA, Pretto P and Bülthoff HH (March-2015) Self-motion sensitivity to visual yaw rotations in humans Experimental Brain Research 233(3) 861-869.

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Last updated: Friday, 24.03.2017