Navigation by Path Integration and the Fourier Transform: A Spiking-Neuron Model

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Advances in Artificial Intelligence (Canadian AI 2013)

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Abstract

In 2005, Hafting et al [1] reported that some neurons in the entorhinal cortex (EC) fire bursts when the animal occupies locations organized in a hexagonal grid pattern in their spatial environment. Previous to that, place cells had been observed, firing bursts only when the animal occupied a particular region of the environment. Both of these types of cells exhibit theta-cycle modulation, firing bursts in the 4-12Hz range. In addition, grid cells fire bursts of action potentials that precess with respect to the theta cycle, a phenomenon dubbed “theta precession”. Since then, various models have been proposed to explain the relationship between grid cells, place cells, and theta precession. However, most models have lacked a fundamental, overarching framework. As a reformulation of the pioneering work of Welday et al [2], we propose that the EC is implementing its spatial coding using the Fourier Transform. We show how the Fourier Shift Theorem relates to the phases of velocity-controlled oscillators (VCOs), and propose a model for how various other spatial maps might be implemented. Our model exhibits the standard EC behaviours: grid cells, place cells, and phase precession, as borne out by theoretical computations and spiking-neuron simulations. We hope that framing this constellation of phenomena in Fourier Theory will accelerate our understanding of how the EC – and perhaps the hippocampus – encodes spatial information.

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Orchard, J., Yang, H., Ji, X. (2013). Navigation by Path Integration and the Fourier Transform: A Spiking-Neuron Model. In: Zaïane, O.R., Zilles, S. (eds) Advances in Artificial Intelligence. Canadian AI 2013. Lecture Notes in Computer Science(), vol 7884. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38457-8_12

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  • DOI: https://doi.org/10.1007/978-3-642-38457-8_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-38456-1

  • Online ISBN: 978-3-642-38457-8

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