Temporal adaptation enhances efficient contrast gain control on natural images
-
1
University Tuebingen, Neuroethology/ Computational Neuroscience and Vision, Germany
-
2
University Tuebingen, Computational Neuroscience and Vision, Germany
The redundancy reduction hypothesis postulates that neural representations adapt to sensory input statistics such that their responses become as statistically independent as possible. Based on this hypothesis, many properties of early visual neurons-like orientation selectivity or divisive normalization-have been linked to natural image statistics. Divisive normalization, in particular, models a widely observed neural response property: The divisive inhibition of a single neuron by a pool of others. This mechanism has been shown to reduce the redundancy among neural responses to typical contrast dependencies in natural images. Using recent advances in natural image modeling, we show that the previously studied static model of divisive normalization achieves substantially less redundancy reduction than a theoretically optimal redundancy reduction mechanism called radial factorization. This optimal mechanism, however, is inconsistent with the existing neurophysiological observations. We suggest a new physiologically plausible modification of the standard model which accounts for the dynamics of the visual input by adapting to local contrasts during fixations. In this way the dynamic version of the standard model achieves almost optimal redundancy reduction performance. Our results imply that the dynamics of natural viewing conditions are critical for testing the role of divisive normalization for redundancy reduction.
Acknowledgements
We thank P. Berens, L. Busse, S. Katzner and L. Theis for fruitful discussions and comments.
Keywords:
constrast gain control,
divisive normalization,
Early Vision,
natural image statistics,
redundancy reduction
Conference:
Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012.
Presentation Type:
Poster
Topic:
Sensory processing and perception
Citation:
Sinz
F and
Bethge
M
(2012). Temporal adaptation enhances efficient contrast gain control on natural images.
Front. Comput. Neurosci.
Conference Abstract:
Bernstein Conference 2012.
doi: 10.3389/conf.fncom.2012.55.00048
Copyright:
The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers.
They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.
The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.
Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.
For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.
Received:
25 May 2012;
Published Online:
12 Sep 2012.
*
Correspondence:
Mr. Fabian Sinz, University Tuebingen, Neuroethology/ Computational Neuroscience and Vision, Tuebingen, 72076, Germany, fabian.sinz@uni-tuebingen.de