Abstract
Area V4 lies in the middle of the ventral visual pathway in primate brains. It is an intermediate stage in the visual processing for object discrimination. V4 neurons exhibit selectivity to complex boundary conformation. In this paper, we propose a novel model of V4 neurons based on sparse coding. The model is a multi-layer neural network of which the output layer consists of laterally connected V4 units. We provide an informal proof for sparse coding with intra-layer inhibitory connections and show experimentally that this model successfully reproduces shape selectivity observed in V4 neurons. The model provides clues to the high level representation of visual stimuli in the brain.
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Wei, H., Dong, Z., Li, Q. (2014). A Model of V4 Neurons Based on Sparse Coding. In: Loo, C.K., Yap, K.S., Wong, K.W., Teoh, A., Huang, K. (eds) Neural Information Processing. ICONIP 2014. Lecture Notes in Computer Science, vol 8834. Springer, Cham. https://doi.org/10.1007/978-3-319-12637-1_30
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DOI: https://doi.org/10.1007/978-3-319-12637-1_30
Publisher Name: Springer, Cham
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