Abstract
Introduction. The Efficient coding hypothesis [1, 2] proposes that biological sensory processing has evolved to maximize the information transmitted to the brain from the environment, and should therefore be tuned to the statistics of the world. Metabolic and wiring considerations impose additional sparsity on these representations, such that the activity of individual neurons are as decorrelated as possible [3]. Efficient coding has provided a framework for understanding early sensory processing in both vision and audition, for example in explaining the receptive field properties of simple and complex cells in primary visual cortex (V1) and the tuning properties of auditory nerve fibres [4].
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Barlow, H.B.: Possible principles underlying the transformation of sensory messages. Sensory Communication, 217–234 (1961)
Atick, J.J.: Could information theory provide an ecological theory of sensory processing? Network: Computation in Neural Systems 3(2), 213–251 (1992)
Simoncelli, E.P.: Vision and the statistics of the visual environment. Current Opinion in Neurobiology 13(2), 144–149 (2003)
Olshausen, B.A., Field, D.J., et al.: Sparse coding of sensory inputs. Current Opinion in Neurobiology 14(4), 481–487 (2004)
Diamond, M., von Heimendahl, M., Knutsen, P., Kleinfeld, D., Ahissar, E.: ’Where’ and ’What’ in the whisker sensorimotor system. Nat. Rev. Neurosci. 9(8) (2008)
Prescott, T., Pearson, M., Mitchinson, B., Sullivan, J., Pipe, A.: Whisking with robots from rat vibrissae to biomimetic technology for active touch. IEEE Robotics and Automation Magazine 16(3), 42–50 (2009)
O’Connor, D.H., Huber, D., Svoboda, K.: Reverse engineering the mouse brain. Nature 461(7266), 923–929 (2009)
Evans, M.H., Fox, C.W., Lepora, N., Pearson, M.J., Sullivan, J.C., Prescott, T.J.: The effect of whisker movement on radial distance estimation: a case study in comparative robotics. Frontiers in Neurorobotics 6(12) (2012)
Fox, C.W., Evans, M.H., Pearson, M.J., Prescott, T.J.: Towards hierarchical blackboard mapping on a whiskered robot. Robotics and Autonomous Systems 60(11), 1356–1366 (2012)
Evans, M.H., Pearson, M.J., Lepora, N.F., Prescott, T.J., Fox, C.W.: Whiskered texture classification with uncertain contact pose geometry. In: 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 7–13 (2012)
Evans, M.H., Fox, C.W., Pearson, M.J., Prescott, T.J.: Spectral template based classification of robotic whisker sensor signals in a floor texture discrimination task. In: Proceedings of Towards Autonomous Robotic Systems (TAROS), pp. 19–24 (2009)
Evans, M.H., Fox, C.W., Pearson, M.J., Lepora, N.F., Prescott, T.J.: Whisker-object contact speed affects radial distance estimation. In: 2010 IEEE International Conference on Robotics and Biomimetics (ROBIO), pp. 720–725 (2010)
Fox, C.W., Evans, M.H., Lepora, N.F., Pearson, M., Ham, A., Prescott, T.J.: CrunchBot: A mobile whiskered robot platform. In: Groß, R., Alboul, L., Melhuish, C., Witkowski, M., Prescott, T.J., Penders, J. (eds.) TAROS 2011. LNCS (LNAI), vol. 6856, pp. 102–113. Springer, Heidelberg (2011)
Sullivan, J.C., Mitchinson, B., Pearson, M.J., Evans, M.H., Lepora, N.F., Fox, C.W., Melhuish, C., Prescott, T.J.: Tactile discrimination using active whisker sensors. IEEE Sensors Journal 12(2), 350–362 (2012)
Szwed, M., Bagdasarian, K., Ahissar, E.: Encoding of vibrissal active touch. Neuron 40(3), 621–630 (2003)
Lottem, E., Azouz, R.: A unifying framework underlying mechanotransduction in the somatosensory system. The Journal of Neuroscience 31(23), 8520–8532 (2011)
Lee, H., Battle, A., Raina, R., Ng, A.Y.: Efficient sparse coding algorithms. In: Advances in Neural Information Processing Systems, vol. 19, p. 801 (2007)
Petersen, R., Brambilla, M., Bale, M., Alenda, A., Panzeri, S., Montemurro, M., Maravall, M.: Diverse and temporally precise kinetic feature selectivity in the VPm thalamic nucleus. Neuron 60(5), 890–903 (2008)
Mitchinson, B., Gurney, K.N., Redgrave, P., Melhuish, C., Pipe, A.G., Pearson, M., Gilhespy, I., Prescott, T.J.: Empirically inspired simulated electro-mechanical model of the rat mystacial follicle-sinus complex. Proc. Biol. Sci. 271(1556), 2509–2516 (2004)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2013 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Evans, M.H. (2013). Efficient Coding in the Whisker System: Biomimetic Pre-processing for Robots?. In: Lepora, N.F., Mura, A., Krapp, H.G., Verschure, P.F.M.J., Prescott, T.J. (eds) Biomimetic and Biohybrid Systems. Living Machines 2013. Lecture Notes in Computer Science(), vol 8064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39802-5_36
Download citation
DOI: https://doi.org/10.1007/978-3-642-39802-5_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-39801-8
Online ISBN: 978-3-642-39802-5
eBook Packages: Computer ScienceComputer Science (R0)