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Our research is directed at understanding information processing in the visual system during visual and motor judgements. Our laboratory in Gießen includes set-ups for studies on visual perception (color vision and perception of natural scenes) and sensori-motor coordination, including state-of-the-art equipment for eye-tracking (EyeLinkII, DPI Eyetracker), motion analysis (Optotrak-3020 System, Zebris Tracking System), and for the manipulation of visual-proprioceptive information (PHANToM- force feedback device).
We currently primarily use psychophysical methods, but future research questions are also directed at studying the neural correlates of sensori-motor control. Collaborations have recently been established within the joint graduate program Neuronal representation and action control with the Department of Neurophysics and Department of Experimental and Clinical Biopsychology at the nearby Philipps-Universität Marburg.
In addition, our lab participates in national and international co-operations directed at studying the behavioral and neural aspects of sensori-motor control (Research Training Network on Perception for Recognition and Action funded by the European Commission; Forschungsverbund MODKOG, funded by the BMBF).
Perception of material qualities
A crucial task of the human visual system is to determine the material that an object is made of. Correct identification of material qualities affects basic decisions such as whether food is edible, skin is healthy, or whether an object is pliable. Humans perceive these qualities in a split second. Yet, little is known about how the brain recognizes materials. Using a combination of psychophysics, image analysis, computational modeling, eye -/ hand tracking, and fMRI we investigate questions such as: What information does the brain use to estimate and categorize material qualities? How do expectations about materials affect how we perceive them, look at them or interact with them? Does freely interacting with a material change how it feels or appears?
Schmid, A.C., Barla, P. & Doerschner, K. (2020). Material category determined by specular reflection structure mediates the processing of image features for perceived gloss. bioRxiv. DOI
- Schmid, A.C., Boyaci, H. & Doerschner, K. (2020). Dynamic dot displays reveal material motion network in the human brain. bioRxiv. DOI
- Schmid, A.C. & Doerschner, K. (2019). Representing stuff in the human brain. Current Opinion in Behavioral Sciences, 30, pp.178-185. DOI
- Toscani, M., Yucel, E. & Doerschner, K. (2019). Gloss and speed judgements yield different fine tuning of saccadic sampling in dynamic scenes. i-Perception, 10(6): 2041669519889070. DOI
- Cavdan, M., Doerschner, K. & Drewing, K. (2019). The many dimensions underlying perceived softness: How exploratory procedures are influences by material and the perceptual task. IEEE World Haptic Conference. DOI
Perception & Action (PerAct) Lab
The PerAct Lab studies how humans use sensory information to guide their actions, focusing on two themes: spatial coding for action and sensorimotor predictions.
Spatial coding for action. To successfully interact with the environment, the human brain needs to build up a representation of where the action goal is located in space. We are interested in how humans spatially represent targets for actions and how they use this spatial information to plan and control eye and hand movements, e.g., directing gaze to a reach goal or grasping an object. Experiments in virtual reality allow us to expand our research on spatial coding for action from small-scale, static to large-scale, dynamic environments.
Sensorimotor predictions. As processing of sensory information takes time, predictive mechanisms can help us to overcome these delays and to prepare our motor system to react at the right place to the right time, e.g. predicting the upcoming position of our moving arm when catching a ball helps us to quickly adjust our arm movement if the ball's trajectory suddenly changes. We investigate how well humans can establish and use sensorimotor predictions, and how these predictions influence the processing of sensory feedback. We believe that feedback signals are up- and down-weighted depending on the accuracy of sensorimotor predictions.
For our research, we use a variety of state-of-the-art methods in real and virtual environments, ranging from eye, hand and whole-body movement tracking to psychophysics and functional neuroimaging (fMRI).
Fiehler, K., Brenner, E., & Spering, M. (2019). Prediction in goal-directed action. Journal of Vision, 19(9), 10, 1-21. DOI
Gertz, H. & Fiehler, K. (2015). Human posterior parietal cortex encodes the movement goal in a pro-/anti-reach task. Journal of Neurophysiology, 114, 170-183. DOI
Karimpur, H., Morgenstern, Y., & Fiehler, K. (2019) Facilitation of allocentric coding by virtue of object-semantics. Scientific Reports, 9, 6263. DOI
Klinghammer, M., Blohm, G., & Fiehler, K. (2015). Contextual factors determine the use of allocentric information for reaching in a naturalistic scene. Journal of Vision, 15(13), 24. DOI
Voudouris D., & Fiehler K. (2017). Enhancement and suppression of tactile signals during reaching. Journal of Experimental Psychology: Human Perception and Performance, 43(6), 1238-1248. DOI
Individual differences in perception
Visual perception feels like an objective window to the world. When we claim to have seen something ‘with our own eyes’, we mean to imply the objective certainty of what we saw, rather than the subjective nature of our impressions. Nevertheless, our perception of the world isn’t always the same. We can look at the same image, but move our eyes to different parts of it; look at the same face and disagree about its trustworthiness; and sometimes even look at the same object and disagree about its colour.
Our research aims to understand more about three related questions:
1) How does perception vary from one person to the next?
2) What are the mechanisms behind these differences?
3) How do they shape who we are and how we interact with others?
To investigate these questions, we use eyetracking, psychophysics and neuroimging in healthy and clinical populations. More information can be found here.
de Haas, B., Iakovidis, A. L., Schwarzkopf, D. S., & Gegenfurtner, K. R. (2019). Individual differences in visual salience vary along semantic dimensions. Proceedings of the National Academy of Sciences, 116(24), 11687-11692. DOI
Moutsiana, C., de Haas, B., Papageorgiou, A., Van Dijk, J. A., Balraj, A., Greenwood, J. A., & Schwarzkopf, D. S. (2016). Cortical idiosyncrasies predict the perception of object size. Nature communications, 7(1), 1-12. DOI
de Haas, B., Kanai, R., Jalkanen, L., & Rees, G. (2012). Grey matter volume in early human visual cortex predicts proneness to the sound-induced flash illusion. Proceedings of the Royal Society B: Biological Sciences, 279(1749), 4955-4961. DOI
The perception of color is a central component of primate vision. Colour facilitates object perception and recognition, and has an important role in scene segmentation and visual memory. Despite the long history of colour vision studies, much there is still much to be learned about the physiological basis of colour perception. Recent studies are beginning to indicate that colour is processed not in isolation, but together with information about luminance and visual form to achieve a unitary and robust representation of the visual world.
- Hansen, T., & Gegenfurtner, K. R. (2006). Higher level chromatic mechanisms for image segmentation. Journal of Vision, 6(3), 239\u2013259. [PDF]
- Hansen, T., Olkkonen, M., Walter, S. & Gegenfurtner, K. R. (2006). Memory modulates color appearance. Nature Neuroscience, 9(11), 1367–1368.
- Gegenfurtner, K.R. (2003) Cortical mechanisms of colour vision. Nature Reviews Neuroscience, 4, 563–572. [PDF]
- Gegenfurtner, K.R. & Kiper, D.C. (2003) Color vision. Annual Review of Neuroscience, 26, 181–206.[PDF]
Haptic and Multisensory Perception
Perception is an active process during that we purposively gather sensory information. Haptic perception is the prime example for this principle. For example, when we aim to haptically judge an object's softness, we first will have to appropriately explore the object in order to obtain the relevant sensory information. Often a single indentation of the object is not sufficient, but we repeatedly indent the object before we deliver a judgment.
In the HapLab we study how humans control natural explorations in active touch, and how information of different type is integrated into a percept of the stimulus. We found, for example, that humans perceive objects to be softer, when they already believe that these objects are relatively soft (Metzger & Drewing, 2019). We also modeled the integration of serially gathered texture information over the course of the exploration, using an ideal observer model (Lezkan, Metzger & Drewing, 2018). Other results suggest that people fine-tune their exploratory movements in order to optimize perception (Zoeller, Lezkan, Paulun, Fleming, & Drewing, 2019). Further research foci in the HapLab are on different dimensions of softness (Cavdan, Doerschner, & Drewing, 2019), haptic saliency and haptic search, multisensory integration (i.e. size-weights illusion), signals to haptic perception of environmental properties (time, space, softness, texture, shape) and on emotional effects of haptic stimulation (Drewing, Weyel, Celebi, & Kaya, 2018).
Typical visuo-haptic VR setup, 3D-printed and custom-made stimuli
The main competences of the lab are on behavioral and perceptual aspects of haptic and multisensory signal processing and of associated movement control. Presently we use in the first place a visuo-haptic VR/AR-setup including a force-feedback device, force sensors and a stereo display, a high-resolution 3D printer (Stratasys Objet Pro), vibrotactile actuators and various custom-made stimuli.
Cavdan, M., Doerschner, K., & Drewing, K. (2019). The Many Dimensions Underlying Perceived Softness: How Exploratory Procedures are Influenced by Material and the Perceptual Task. IEEE World Haptics Conference, WHC 2019 (pp. 437-442), IEEE. DOI
Drewing, K., Weyel, C., Celebi, H., & Kaya, D. (2018). Systematic Relations between Affective and Sensory Material Dimensions in Touch. IEEE Transactions on Haptics 11(4), 611-622. DOI
Lezkan, A., & Drewing, K. (2018). Processing of haptic texture information over sequential exploration movements. Attention, Perception, & Psychophysics, 80(1), 177-192. DOI
Metzger, A., & Drewing, K. (2019). Memory influences haptic perception of softness. Scientific Reports, 9(1), 1-10. DOI
Zoeller, A. C., Lezkan, A., Paulun, V. C., Fleming, R. W., & Drewing, K. (2019). Integration of prior knowledge during haptic exploration depends on information type. Journal of Vision, 19(4), 1-15. DOI
Perception and eye movements in natural scenes
We study the principles underlying the selection of fixation targets under natural viewing conditions. We study fixation patterns and saccadic latencies of human subjects viewing under natural images and videos of natural scenes and ask how stimulus features like contrast, color and spatial frequency content interact with top-down mediated expectations.
- Thorpe, S., Gegenfurtner, K.R., Fabre-Thorpe, M. & Bülthoff, H.H. (2001) Detection of animals in natural images using far peripheral vision. European Journal of Neuroscience, 14, 869-876. <Get PDF file>
- Gegenfurtner, K.R. & Rieger, J. (2000) Sensory and cognitive contributions of color to the perception of natural scenes.Current Biology, 10, 805-808. <Get PDF file>
Eye movements and Visual Perception
Dr. Jutta Billino, Dr. Doris Braun, Prof. Karl Gegenfurtner, Ph.D.
Humans frequently move their eyes, either to fixate a new location in the visual field (saccadic eye movements), or to keep fixation on a moving object (smooth pursuit eye movements). These eye movements pose two problems. First, an appropriate target location and execution time has to be selected for the eye movements. Hence we study, which visual signals are used to guide these eye movements, i.e. how visual perception influences the control of eye movements. Second, the execution of eye movements changes the visual image on the retina. To maintain a clear and stable perception of the world, the visual system has to cope with the retinal image motion. In this context we study how visual perception is affected by the execution of concurrent eye movements.
Our experimental approach comprises psychophysics measurements under simultaneous tracking of eye movements to investigate the bidirectional relationship between perception and eye movements.
- Schütz, A.C., Braun, D.I., Kerzel, D. & Gegenfurtner, K.R. (2008) Improved visual sensitivity during smooth pursuit eye movements. Nature Neuroscience, 11, 1211-1216. DOI
- Spering, M. & Gegenfurtner, K.R. (2008). Contextual effects on motion perception and smooth pursuit eye movements. Brain Research, 1225, 76-85. DOI
- White, B.J., Stritzke, M. & Gegenfurtner, K.R. (2008) Saccadic facilitation in natural backgrounds. Current Biology, 18, 124-128. DOI
Visually guided motor behavior
We investigate the complex mechanisms involved in interactions of humans with the environment. The versatility of the human visuo-motor system can be seen in the ease with which we perform everyday tasks such as reaching and grasping for objects under varying visual input. For example, we can easily grasp fragile objects like eggs (we might even learn to juggle them), or we might learn to adapt quickly to the distortions introduced by wearing left-right reversing prisms, etc. On the other hand, it is still very difficult to devise technical systems which are capable of only a subset of the capabilities of the human motor system.
One of the questions we have been studying intensively during recent years is whether the visual guidance of motor behavior is achieved by different processes (and neuronal substrates) as our conscious (visual) perception. Studies on neurological patients suggest such a division of labor in the human brain and it was suggested that this dissociation between vision-for-action and vision-for-perception can also be found in healthy humans. Support for this view came from studies which found that grasping is less affected by visual illusions than perception. Our results, to the contrary, suggest that the motor system uses very similar processes and neuronal signals as visual perception. This suggests that the brain is more coherent than currently proposed by a number of theories in visual neuroscience.
- V. H. Franz. Planning versus online control: Dynamic illusion effects in grasping? Spatial Vision, 16(3-4):211 - 223, 2003. [PDF]
- V. H. Franz. Action does not resist visual illusions. Trends in Cognitive Sciences, 5(11):457 - 459, 2001. [PDF]
- V. H. Franz, K. R. Gegenfurtner, H. H. Bülthoff, and M. Fahle. Grasping visual illusions: No evidence for a dissociation between perception and action. Psychological Science, 11(1):20 - 25, 2000. [PDF]