Bio-inspired computational memory model of the Hippocampus: an approach to a neuromorphic spike-based Content-Addressable Memory

TL;DR

This paper introduces the first hardware implementation of a bio-inspired, spike-based hippocampal content-addressable memory model that can learn, forget, and recall memories from fragments, advancing neuromorphic system development.

Contribution

It presents a novel hardware model of hippocampal memory based on CA3, capable of learning and recalling memories, implemented on SpiNNaker hardware.

Findings

Successfully implemented on SpiNNaker hardware

Demonstrated ability to learn and recall both orthogonal and non-orthogonal memories

Validated through functional, stress, and applicability tests

Abstract

The brain has computational capabilities that surpass those of modern systems, being able to solve complex problems efficiently in a simple way. Neuromorphic engineering aims to mimic biology in order to develop new systems capable of incorporating such capabilities. Bio-inspired learning systems continue to be a challenge that must be solved, and much work needs to be done in this regard. Among all brain regions, the hippocampus stands out as an autoassociative short-term memory with the capacity to learn and recall memories from any fragment of them. These characteristics make the hippocampus an ideal candidate for developing bio-inspired learning systems that, in addition, resemble content-addressable memories. Therefore, in this work we propose a bio-inspired spiking content-addressable memory model based on the CA3 region of the hippocampus with the ability to learn, forget and recall memories, both orthogonal and non-orthogonal, from any fragment of them. The model was implemented on the SpiNNaker hardware platform using Spiking Neural Networks. A set of experiments based on functional, stress and applicability tests were performed to demonstrate its correct functioning. This work presents the first hardware implementation of a fully-functional bio-inspired spiking hippocampal content-addressable memory model, paving the way for the development of future more complex neuromorphic systems.