Abstract
Hierarchical neural networks require the parallel extraction of multiple features. This raises the question how a subpopulation of cells can become specific to one feature and invariant to another, while a different subpopulation becomes invariant to the first but specific to the second feature. Using a colour image sequence recorded by a camera mounted to a cat’s head, we train a population of neurons to achieve optimally stable responses. We find that colour sensitive cells emerge. Adding the additional objective of decorrelating the neurons’ outputs leads a subpopulation to develop achromatic receptive fields. The colour sensitive cells tend to be non-oriented, while the achromatic cells are orientation-tuned, in accordance with physiological findings. The proposed objective thus successfully separates cells which are specific for orientation and invariant to colour from orientation invariant colour cells.
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References
Olshausen, B.A., Field, D.J.: Emergence of simple-cell receptive field properties by learning a sparse code for natural images. Nature 381 (1996) 607–609
Hyvärinen, A., Hoyer, P.O.: Emergence of phase and shift invaraint features by decomposition of natural images into independent feature subspaces. Neural Comput. 12 (2000) 1705–1720
Földiak, P.: Learning Invariance from Transformation Sequences. Neural Computation 3 (1991) 194–200
Hurri, J., Hyvärinen A. Simple-Cell-Like Receptive Fields Maximize Temporal Coherence in Natural Video. submitted (2002)
Kayser, C., Einhäuser, W., Dümmer O., König P., Körding K.P.: Extracting slow subspaces from natural videos leads to complex cells. In G. Dorffner, H. Bischoff, K. Hornik (eds.) Artificial Neural Networks-(ICANN) LNCS 2130, Springer-Verlag, Berlin Heidelberg New York (2001) 1075–1080
Gouras, P.: Opponent-colour cells in different layers of foveal striate cortex. J. Physiol 199 (1974) 533–547
Lennie, P., Krauskopf, J., Sclar, G.: Chromatic Mechanisms in Striate Cortex of Macaque. J. Neurosci. 10 (1990) 649–669
Jähne, B.: Digital Image Processing-Concepts, Algortihms and Scientific Applications, 4th compl. rev. edn. Springer-Verlag, Berlin Heidelberg New York (1997)
Hoyer, P.O., Hyvärinen, A.: Independent Component Analysis Applied to Feature Extraction From Colour and Stereo Images. Network 11 (2000) 191–210
Einhäuser, W., Kayser, C, König, P., Körding, K.P.: Learning of complex cells properties from their responses to natural stimuli. Eur. J. Neurosci. 15 (2002) in press.
Lee, T.W., Wachtler, T., Sejnowski, T.: Color Opponency Constitutes A Sparse Representation For the Chromatic Structure of Natural Scenes. NIPS. 13 (2001) 866–872.
Wachtler, T., Lee, T.W., Sejnowski, T.: Chromatic Structure of natural scenes. J. Opt. Sco. Am. A 18 (2001) 65–77
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Einhäuser, W., Kayser, C., Körding, K.P., König, P. (2002). Learning Multiple Feature Representations from Natural Image Sequences. In: Dorronsoro, J.R. (eds) Artificial Neural Networks — ICANN 2002. ICANN 2002. Lecture Notes in Computer Science, vol 2415. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46084-5_4
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DOI: https://doi.org/10.1007/3-540-46084-5_4
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