Moving objects generate motion information at different scales, which are processed in the visual system with a bank of spatiotemporal frequency channels. It is not known how the brain pools this information to reconstruct object speed and whether this pooling is generic or adaptive; that is, dependent on the behavioral task. We used rich textured motion stimuli of varying bandwidths to decipher how the human visual motion system computes object speed in different behavioral contexts. We found that, although a simple visuomotor behavior such as short-latency ocular following responses takes advantage of the full distribution of motion signals, perceptual speed discrimination is impaired for stimuli with large bandwidths. Such opposite dependencies can be explained by an adaptive gain control mechanism in which the divisive normalization pool is adjusted to meet the different constraints of perception and action.
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We thank J. Colombet, F. Barthélemy and X. DeGiovanni for their excellent technical support and A. Meso for improving the readability of the manuscript. We are grateful to Y. Frégnac, P. Cavanagh, K. Gegenfurtner, A. Movshon and T. Freeman for helpful comments and discussions in the preparation of the manuscript. This work was supported by the EU grant CODDE (VIIth Framework, Marie Curie Program, PITN-2008-214728), by the Centre National de la Recherche Scientifique and by the EU projects FACETS (VIth Framework, IST-FET-2005-15879) and BrainScales (VIth Framework, IST-FET-2011-269921).
The authors declare no competing financial interests.
Example of a dynamic random phase texture, named motion cloud, with mean spatial frequency of 0.3 cpd and small spatial frequency bandwidth (Bsf=0.025) (see Fig.1a). (MPG 1894 kb)
Example of a dynamic random phase texture, named motion cloud, with mean spatial frequency of 0.3 cpd and large spatial frequency bandwidth (Bsf=0.4) (see Fig.1a). (MPG 586 kb)
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Simoncini, C., Perrinet, L., Montagnini, A. et al. More is not always better: adaptive gain control explains dissociation between perception and action. Nat Neurosci 15, 1596–1603 (2012). https://doi.org/10.1038/nn.3229
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