August 2009
Volume 9, Issue 8
Vision Sciences Society Annual Meeting Abstract  |   August 2009
Perceptual learning for speed discrimination in optical flow
Author Affiliations
  • Stefan Ringbauer
    Institute of Neural Information Processing, University of Ulm
  • Florian Raudies
    Institute of Neural Information Processing, University of Ulm
  • Heiko Neumann
    Institute of Neural Information Processing, University of Ulm
Journal of Vision August 2009, Vol.9, 869. doi:
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      Stefan Ringbauer, Florian Raudies, Heiko Neumann; Perceptual learning for speed discrimination in optical flow. Journal of Vision 2009;9(8):869. doi:

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      © ARVO (1962-2015); The Authors (2016-present)

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Problem. Perceptual learning can improve observer performance in visual decision making tasks (Dosher et al., Psychological Review, 112, 2005). Here we investigate perceptual learning for motion speed discrimination of a coherent motion pattern subsequently displayed at different speeds in one quadrant (random motion at all other quadrants). The goal is to evaluate whether performance is still improved when the coherent motion is presented in a different quadrant.

Methods. We propose a neural model of motion perception consisting of a hierarchy of areas to represent the main processing stages along the dorsal pathway in visual cortex, namely V1, MT, and MSTd (Bayerl & Neumann, Neural Computation, 16, 2004; Ringbauer et al., LNCS 4669, 2007). Optical flow is detected in area V1 and integrated in area MT by speed and direction sensitive neurons. Global motion patterns are spatially integrated subsequently in model area MSTd cells which are sensitive to rotational, radial, and laminar motion patterns (Graziano et al., J. of Neuroscience, 14, 1994). Model MSTd cells project to dorso-lateral area LIP where cells temporally accumulate responses to judge and discriminate different motion configurations (Hanks et al., Nature Neuroscience, 9, 2006). Here, perceptual learning is incorporated through synaptic reweighting in LIP controlling the input stimulus and the strength of mutual inhibition between recurrent competitive field neurons (Grossberg & Pilly, Vision Research, 48, 2008).

Results and Conclusion. The model shows decreased reaction time after several trials in a training setup. Additionally small speed differences can be discriminated more accurately even if the target pattern is presented in a quadrant that has previously not been probed during training. Thus the model predicts that improved speed discrimination performance after perceptual learning using a selected quadrant can be transferred to other locations as well.

Ringbauer, S. Raudies, F. Neumann, H. (2009). Perceptual learning for speed discrimination in optical flow [Abstract]. Journal of Vision, 9(8):869, 869a,, doi:10.1167/9.8.869. [CrossRef]
 Supported by German Federal Ministry of Education and Research, project 01GW0763, Brain plasticity and Perceptual Learning Graduate School of Mathematical Analysis of Evolution, Information and Complexity at the University of Ulm.

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