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home contact program alumni application


Organizers: Wolfgang Einhäuser-Treyer   Roland Fleming   Alexander Schütz
Funded by the Center for Mind, Brain and Behavior at
Justus-Liebig University Gießen and Philipps-University Marburg.

Preliminary program

Sunday 5
Arrival and welcome
20:00 Introduction ETFS
Monday 6
9:00-12:00 Lecture Ulrike Grünert Retina
14:00-16:00 Poster session
16:00-19:00 Lecture Paul Martin Subcortical visual pathways
20:00 Discussion Karl Gegenfurtner How to get your work published
Tuesday 7
9:00-12:00 Lecture Karl Gegenfurtner Color
14:00-16:00 Exercise Matteo Toscani Color
16:00-19:00 Lecture Tony Movshon Cortex
20:00 Discussion Tony Movshon Effective visual presentations
Wednesday 8
9:00-12:00 Lecture Tony Movshon Motion
14:00-16:00 Exercise Roland Fleming Computer graphics
16:00-19:00 Lecture Zoe Kourtzi fMRI / Learning
20:00
Thursday 9
9:00-12:00 Lecture Anitha Pasupathy Ventral cortex
14:00-16:00 Exercise Wolfgang Einhäuser Natural scenes
16:00-19:00 Lecture Pieter Roelfsema Perceptual organization
20:00
Friday 10
9:00-12:00 Lecture Larry Maloney Perception and action
14:00-16:00 Exercise Larry Maloney Bayesian modeling
16:00-19:00 Lecture Pascal Mamassian Visual confidence
20:00
Saturday 11
9:00-12:00 Lecture Roland Fleming Material perception
14:00-17:00 Lecture Alexander Schütz Eye movements and perception
20:00 Banquet & Party
Sunday 12
Day off (optional trip to Marburg)
Monday 13
9:00-12:00 Lecture Wyeth Bair Models of the ventral cortex
14:00-16:00 Poster session
16:00-19:00 Lecture Ruth Rosenholtz Crowding
20:00 Discussion Stefan Treue Animal research
Tuesday 14
9:00-12:00 Lecture Stefan Treue Physiology of attention
14:00-16:00 Exercise Alexander Schütz Eye movement analysis
16:00-19:00 Lecture James Bisley Eye movements and attention
20:00 Discussion Andrew Welchman Career planing
Wednesday 15
9:00-12:00 Lecture Felix Wichmann Deep learning
14:00-16:00 Exercise Felix Wichmann Deep learning
16:00-19:00 Lecture Andrew Welchman Depth
20:00 Feverish work on student projects
Thursday 16
9:00-12:00 Lecture Wolfgang Einhäuser Multistability
14:00-17:00 Lecture Claire Sergent Visual awareness
20:00 Student presentations
Friday 17
Farewell, transfer to airport

Daily meals

8-9: Breakfast
12-2: Lunch
7-8: Dinner

Confirmed speakers

Wyeth Bair, University of Washington, aims to understand neural circuitry and neural coding in the cerebral cortex of the primate visual system. He approaches this problem by recording directly from neurons in the functioning brain in vivo and by creating and refining large scale spiking neural network models that run on parallel computers (see http://www.imodel.org).

  • Bair, W., & Movshon, J.A. (2004). Adaptive temporal integration of motion in direction-selective cells in macaque visual cortex. The Journal of Neuroscience, 24, 7305-7323. [pdf]
  • Baker, P. M., & Bair, W. (2012). Inter-neuronal correlation distinguishes mechanisms of direction selectivity in cortical circuit models. The Journal of Neuroscience, 32(26), 8800-8816. [pdf]
  • Cavanaugh, J. R., Bair, W., & Movshon, J. A. (2002). Nature and interaction of signals from the receptive field center and surround in macaque V1 neurons. Journal of neurophysiology, 88(5), 2530-2546. [pdf]

James Bisley, University of California, Los Angeles, studies the neuronal mechanisms underlying the allocation of visual attention and the guidance of eye movements.

  • Mirpour K, Bolandnazar Z, Bisley JW (2018) Suppression of frontal eye field neuronal responses with maintained fixation. Proc Natl Acad Sci U S A 115:804-809. [pdf]
  • Mirpour K, Arcizet F, Ong WS, Bisley JW (2009) Been there, seen that: a neural mechanism for performing efficient visual search. J Neurophysiol 102:3481-3491. [pdf]
  • Bisley JW, Goldberg ME (2003) Neuronal activity in the lateral intraparietal area and spatial attention. Science 299:81-86. [pdf]

Wolfgang Einhäuser-Treyer, TU Chemnitz, works on attention and eye movements during natural-scene processing and in real-world tasks, and uses rivalry to study commonalities between perception, action and decision-making.

  • Einhäuser, W., Stout, J., Koch, C., & Carter, O. (2008). Pupil dilation reflects perceptual selection and predicts subsequent stability in perceptual rivalry. Proc Natl Acad Sci USA, 105(5) : 1704-1709. [pdf]
  • 't Hart, B.M., & Einhäuser, W. (2012). Mind the step: complementary effects of an implicit task on eye and head movements in real-life gaze allocation. Exp Brain Res, 223(2): 233-249. [pdf]

Roland Fleming, Universität Giessen, works on perception of shape, illumination and materials (psychophysics, computer graphics, modeling).

  • Fleming, R.W. (2014). Visual Perception of Materials and their Properties. Vision Research, 94, 62-75. [pdf]
  • Muryy, A., Welchman, A.E., Blake, A. and R.W. Fleming (2013). Specular reflections and the estimation of shape from binocular disparity. Proceedings of the National Academy of Sciences, 110(6): 2413-2418. [pdf]

Karl Gegenfurtner, Universität Giessen, works on color vision, natural images, and the relationship between perception and action (psychophysics).

  • Gegenfurtner, K.R., Bloj, M. & Toscani, M. (2015) The many colours of the dress. Current Biology, 25, R543-R544. [pdf]
  • Toscani, M., Valsecchi, M. & Gegenfurtner, K.R. (2013) Optimal sampling of visual information for lightness judgments. Proceedings of the National Academy of Sciences USA, 110(27), 11163-11168. [pdf]
  • Hansen, T., Olkkonen, M., Walter, S. & Gegenfurtner, K.R. (2006) Memory modulates color appearance. Nature Neuroscience,  9, 1367-1368. [pdf]
  • Gegenfurtner, K.R. & Kiper, D.C. (2003) Color vision. Annual Review of Neuroscience, 26, 181-206. [pdf]

Ulrike Grünert, University of Sydney, works on the functional neuroanatomy of the mammalian retina with special focus on human and non-human primates. Her work has defined parallel pathways through the primate retina and identified the connections of retinal ganglion cells with other retinal cells and ganglion cell targets in the brain.

Zoe Kourtzi, University of Cambridge, focuses on imaging the neural processes in the human brain that mediate complex, adaptive cognitive functions and behaviour.

  • Li, S., Mayhew, S. D., & Kourtzi, Z. (2009). Learning shapes the representation of behavioral choice in the human brain. Neuron 62, 441-452. [pdf]
  • Li, S., Ostwald, D., Giese, M., & Kourtzi, Z. (2007). Flexible coding for categorical decisions in the human brain. J Neurosci. 27(45):12321-12330. [pdf]

Larry Maloney, New York University, works on models of human performance based on mathematical statistics, physics and mathematics.

  • Ernst, M. O. & Bülthoff, H. H. (2004). Merging the senses into a robust percept. Trends in Cognitive Science, 8, 162-169. [pdf]
  • Trommershäuser, J., Maloney, L. T. & Landy M. S. (2008). Decision making, movement planning and statistical decision theory. Trends in Cognitive Science, 12, 291-297. [pdf]
  • Geisler, W.S. (1989). Sequential-ideal observer analysis of visual discriminations. Psychological Review, 96, 267-314. [pdf]
  • Landy, M. S., Maloney, L. T., Johnston, E. B., & Young, M. (1995). Measurement and modeling of depth cue combination: In defense of weak fusion. Vision Research, 35, 389-412. [pdf]

Pascal Mamassian, École Normale Supérieure, works on 3D, motion, and time perception, with an emphasis on sequential effects and confidence judgments.

  • Kiani, R., & Shadlen, M. N. (2009). Representation of confidence associated with a decision by neurons in the parietal cortex. Science, 324(5928), 759–764. [pdf]
  • Fleming, S. M., Weil, R. S., Nagy, Z., Dolan, R. J., & Rees, G. (2010). Relating introspective accuracy to individual differences in brain structure. Science, 329(5998), 1541–1543. [pdf]
  • Mamassian, P. (2016). Visual confidence. Annual Review of Vision Science, 2(1), 459–481. [pdf]

Paul Martin, University of Sydney, studies anatomy and physiology of subcortical pathways in non-human primates, with emphasis on the role of parallel pathways in sensory signal transmission.

  • Cleland, B. G., Levick, W. R., Morstyn, R., & Wagner, H. G. (1976). Lateral geniculate relay of slowly-conducting retinal afferents to cat visual cortex. Journal of Physiology, 255, 299-320. [pdf]
  • Derrington, A. M., & Lennie, P. (1984). Spatial and temporal contrast sensitivities of neurones in lateral geniculate nucleus of macaque. Journal of Physiology, 357, 219-40. [pdf]
  • Martin, P. R., White, A. J. R., Goodchild, A. K., Wilder, H. D., & Sefton, A. E. (1997). Evidence that blue-on cells are part of the third geniculocortical pathway in primates. European Journal of Neuroscience, 9(7), 1536-41. [pdf]
  • McAlonan, K., Cavanaugh, J., & Wurtz, R. H. (2008). Guarding the gateway to cortex with attention in visual thalamus. Nature, 456(7220), 391-94. [pdf]
  • Wiesel, T. N., & Hubel, D. (1966). Spatial and chromatic interactions in the lateral geniculate body of the rhesus monkey. Journal of Neurophysiology, 29, 1115-56. [pdf]
  • Wurtz, R. H., McAlonan, K., Cavanaugh, J., & Berman, R. A. (2011). Thalamic pathways for active vision. Trends in Cognitive Sciences., 15(4), 177-84. [pdf]
  • Zeater, N., Cheong, S. K., Solomon, S. G., Dreher, B., & Martin, P. R. (2015). Binocular visual responses in primate lateral geniculate nucleus. Current Biology, 25(24), 3190-95. [pdf]

Tony Movshon, Center for Neural Science, New York, studies the function and development of the primate visual system, particularly the neurophysiological basis of motion perception (electrophysiology, psychophysics).

Elements of vision:

  • Marr DC (1982). Vision: A Computational Investigation into the Human Representation and Processing of Visual Information, chapter 1. MIT press. [pdf]
  • Enroth-Cugell C, Robson JG (1984). Functional Characteristics and Diversity of Cat Retinal Ganglion Cells. Investigative Ophthalmology and Visual Science 25: 250-267. [pdf]
  • Adelson EH, Bergen J (1991). The plenoptic function and the elements of early vision. In Computational Models of Visual Processing, Landy MS, Movshon JA, eds. MIT Press. [pdf]
  • Mante V, Frazor RA, Bonin V, Geisler WS, Carandini M (2005). Independence of luminance and contrast in natural scenes and in the early visual system. Nat Neurosci 8: 1690-1697. [pdf]
  • Lennie P, Movshon JA (2005). Coding of color and form in the geniculostriate visual pathway. J Opt Soc Am A 22: 2013-2033. [pdf]
Cortex:
  • Jazayeri, M, & Afraz, A (2017). Navigating the neural space in search of the neural code. Neuron, 93(5), 1003-1014. [pdf]
  • Krakauer, JW, Ghazanfar, AA, Gomez-Marin, A, MacIver, MA, & Poeppel, D (2017). Neuroscience needs behavior: correcting a reductionist bias. Neuron, 93(3), 480-490. [pdf]
  • Movshon JA, Simoncelli EP (2015). Representation of naturalistic image structure in the primate visual cortex. Cold Spring Harbor Symposia on Quantitative Biology 79: 115–122. [pdf]
  • Rust NC, Mante V, Simoncelli EP & Movshon JA (2006). How MT cells analyze the motion of visual patterns. Nature Neuroscience, 9(11), 1421-1431. [pdf]

Anitha Pasupathy, University of Washington ,works on the neural basis of visual shape perception and recognition, the ability to identify and recognize objects from all angles, distances, and in almost any lighting condition. She uses single cell neurophysiological studies in awake monkeys, behavioral manipulations, computational modeling and reversible inactivation techniques to investigate how the information reaching our eyes is represented in the neural activity patterns in the brain, how these representations are transformed in successive stages and finally how these representations inform behavior.

  • Pasupathy, A., & Brincat, S. L. (2012). Population Coding of Object Contour Shape in V4 and Posterior Inferotemporal Cortex. In: Visual Population Codes: Toward a Common Multivariate Framework for Cell Recording and Functional Imaging, 189. [pdf]
  • Bushnell, B. N., Harding, P. J., Kosai, Y., & Pasupathy, A. (2011). Partial occlusion modulates contour-based shape encoding in primate area V4. The Journal of Neuroscience, 31(11), 4012-4024. [pdf]
  • Bushnell, B. N., & Pasupathy, A. (2012). Shape encoding consistency across colors in primate V4. Journal of Neurophysiology, 108(5), 1299-1308. [pdf]
  • Pasupathy, A., & Connor, C. E. (2002). Population coding of shape in area V4. Nature neuroscience, 5(12), 1332-1338. [pdf]

Pieter Roelfsema, Netherlands Institute for Neurosciences, Amsterdam, is interested in how attentional processes coordinate neuronal activity in different brain areas (electrophysiology).

  • Lorteije, J.A.M., Zylberberg, A., Ouellette, B.G., De Zeeuw, C.I., Sigman, M. & Roelfsema, P.R. (2015) The formation of hierarchical decisions in the visual cortex. Neuron, 87, 1344­1356. [pdf]
  • Roelfsema, P. R., & de Lange, F. P. (2016). Early visual cortex as a multiscale cognitive blackboard. Annual Review of Vision Science, 2, 131-151. [pdf]
  • Roelfsema, P. R., & Holtmaat, A. (2018). Control of synaptic plasticity in deep cortical networks. Nature Reviews Neuroscience, 19(3), 166. [pdf]
  • van Vugt, B., Dagnino, B., Vartak, D., Safaai, H., Panzeri, S., Dehaene, S., & Roelfsema, P. R. (2018). The threshold for conscious report: Signal loss and response bias in visual and frontal cortex. Science, 360(6388), 537-542. [pdf]

Ruth Rosenholtz, MIT, is interested in behavioral and computational aspects of human vision. Topics include peripheral vision, texture perception, perceptual organization, visual search, and scene perception. She also works on applied vision, most recently design of user interfaces and information visualizations, and vision for driving.

Alexander Schütz, University of Marburg, works on the relationship of eye movements and perception.

  • Schütz, A. C., Braun, D. I., & Gegenfurtner, K. R. (2011). Eye movements and perception: a selective review. Journal of Vision, 11(5):9, 1-30. [pdf]
  • Schütz, A. C., Braun, D. I., Kerzel, D., & Gegenfurtner, K. R. (2008). Improved visual sensitivity during smooth pursuit eye movements. Nature Neuroscience, 11(10), 1211-1216. [pdf]
  • Wolf, C., & Schütz, A. C. (2015). Trans-saccadic integration of peripheral and foveal feature information is close to optimal. Journal of Vision, 16(16):1, 1-18. [pdf]

Claire Sergent, Université Paris Descartes.

Stefan Treue, German Primate Center Göttingen, works on the neural correlates of attention in primate visual cortex (electrophysiology, psychophysics, modeling).

  • Maunsell, J. H. R., & Treue, S. (2006). Feature-based attention in visual cortex. Trends in Neurosciences, 29(6) , 317-322. [pdf]
  • Treue, S. (2001). Neural correlates of attention in primate visual cortex. Trends in Neurosciences, 24 , 295-300. [pdf]

Andrew Welchman, University of Cambridge, is interested in psychophysics and modelling of 3D vision, brain imaging and movement synchronisation.

  • Ban H & Welchman AE (2015) fMRI analysis-by-synthesis reveals a dorsal hierarchy that extracts surface slant. Journal of Neuroscience, 35, 9823-35. [pdf]
  • Goncalves NR, Ban H, Sánchez-Panchuelo RM, Francis ST, Schluppeck D & Welchman AE (2015) 7 tesla FMRI reveals systematic functional organization for binocular disparity in dorsal visual cortex. Journal of Neuroscience, 35, 3056-72. [pdf]
  • Chang DHF, Mevorach C, Kourtzi Z & Welchman AE (2014) Training transfers the limits on perception from parietal to ventral cortex. Current Biology 24, 2445–2450. [pdf]
  • Ban H, Preston TJ, Meeson A & Welchman AE (2012) The integration of motion and disparity cues to depth in dorsal visual cortex. Nature Neuroscience, 15, 636-43. [pdf]

Felix Wichmann, Eberhard Karls Universität Tübingen, works on spatial vision, lightness- and brightness as well as object recognition, combining psychophysical experiments, computational modeling and machine learning..

  • Jäkel, F., Schölkopf, B. and Wichmann, F. A. (2009). Does cognitive science need kernels? Trends in Cognitive Sciences, 13(9), 381-388. [pdf]
  • Kienzle, W., Franz, M. O., Schölkopf, B. and Wichmann, F. A. (2009). Center-surround patterns emerge as optimal predictors for human saccade targets. Journal of Vision, 9(5:7), 1-15. [pdf]
  • Geirhos, R., Temme, C. R. M., Rauber, J., Schütt, H. H., Bethge, M. and Wichmann, F. A. (2018). Generalisation in humans and deep neural networks. In Bengio, S., Wallach, H., Larochelle, H., Grauman, K., Cesa-Bianchi, N., and Garnett, R., editors, Advances in Neural Information Processing Systems (NeurIPS) 31, pages 7549–7561. [pdf]
  • Geirhos, R., Rubisch, P., Michaelis, C., Bethge, M., Wichmann, F. A. and Brendel, W. (2019). ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness. International Conference on Learning Representations (ICLR), 2019 [pdf]
  • Schütt, H. H. and Wichmann, F. A. (2017). An image-computable psychophysical spatial vision model. Journal of Vision, 17(12):12, 1–35. [pdf]