Live Demonstration: Bio-inspired implementation of a sparse-learning spike-based hippocampus memory model

The hippocampus acts as a short-term memory capable of recalling a previously-learned complete memory from a fragment of it. Inspired by the hippocampus and taking into account its input from the visual stream, a neuromorphic system capable of learning images and remembering them from a fragment of...

Full description

Saved in:
Bibliographic Details
Published in2023 IEEE International Symposium on Circuits and Systems (ISCAS) p. 1
Main Authors Casanueva-Morato, Daniel, Ayuso-Martinez, Alvaro, Dominguez-Morales, Juan P., Jimenez-Fernandez, Angel, Jimenez-Moreno, Gabriel
Format Conference Proceeding
LanguageEnglish
Published IEEE 21.05.2023
Subjects
Biological system modeling
Circuits and systems
Integrated circuit modeling
Neuromorphics
Real-time systems
Streaming media
Visualization
Online AccessGet full text

Cover

More Information
Summary:The hippocampus acts as a short-term memory capable of recalling a previously-learned complete memory from a fragment of it. Inspired by the hippocampus and taking into account its input from the visual stream, a neuromorphic system capable of learning images and remembering them from a fragment of it in real time was developed. The system contains a bio-inspired hippocampal spiking memory that acts as an autoassociative network that, for each input image, associates the spatial activation patterns of the pixels of the image. A monitor has been designed to visualize the internal spiking activity of the network during the simulation.
ISSN:2158-1525
DOI:10.1109/ISCAS46773.2023.10181583