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arXiv:2405.14600cs.AI

Discretization of continuous input spaces in the hippocampal autoencoder

Adrian F. Amil, Ismael T. Freire, Paul F. M. J. Verschure

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Abstract

The hippocampus has been associated with both spatial cognition and episodic memory formation, but integrating these functions into a unified framework remains challenging. Here, we demonstrate that forming discrete memories of visual events in sparse autoencoder neurons can produce spatial tuning similar to hippocampal place cells. We then show that the resulting very high-dimensional code enables neurons to discretize and tile the underlying image space with minimal overlap. Additionally, we extend our results to the auditory domain, showing that neurons similarly tile the frequency space in an experience-dependent manner. Lastly, we show that reinforcement learning agents can effectively perform various visuo-spatial cognitive tasks using these sparse, very high-dimensional representations.

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Journal reference
DOI
Subjects
cs.AIArtificial Intelligence cs.LGMachine Learning q-bio.NCNeurons and Cognition

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    • This paper may be interesting to some of you: Discretization of continuous input spaces in the hippocampal autoencoder https://arxiv.org/pdf/2405.14600

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