Abstract
To behave in a robust and adaptive way, animals must extract task-relevant sensory information efficiently. One way to understand how they achieve this is to explore regularities within the information animals perceive during natural behavior. In this chapter, we describe how we have used artificial neural networks (ANNs) to explore efficiencies in vision and memory that might underpin visually guided route navigation in complex worlds. Specifically, we use three types of neural network to learn the regularities within a series of views encountered during a single route traversal (the training route), in such a way that the networks output the familiarity of novel views presented to them. The problem of navigation is then reframed in terms of a search for familiar views, that is, views similar to those associated with the route. This approach has two major benefits. First, the ANN provides a compact holistic representation of the data and is thus an efficient way to encode a large set of views. Second, as we do not store the training views, we are not limited in the number of training views we use and the agent does not need to decide which views to learn.
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Notes
- 1.
Here Lettvin and colleagues found that parts of the frog’s visual system are tuned to detect small moving objects. Thus the eye is providing information to the frog about where to direct the tongue in the hope of catching a fly. McCulloch and Pitts, authors of this paper, are commonly held up as pioneers of neural network research. J. Y. Lettvin, H. R. Maturana, W. S. McCulloch, and W. H. Pitts, “What the Frog’s Eye Tells the Frog’s Brain,” Proc. IRE 47 (1959) 1940–1951.
- 2.
Lettvin again came up with the concept of a sparse code in the brain where small numbers of individual neurons may be highly selective to concepts such as one’s grandmother. See Quian-Quiroga, R., Fried, I., and Koch, C. (2013) Brain Cells for Grandmother. Scientific American, Feb.
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Philippides, A., Graham, P., Baddeley, B., Husbands, P. (2015). Using Neural Networks to Understand the Information That Guides Behavior: A Case Study in Visual Navigation. In: Cartwright, H. (eds) Artificial Neural Networks. Methods in Molecular Biology, vol 1260. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2239-0_14
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DOI: https://doi.org/10.1007/978-1-4939-2239-0_14
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