Effect of time history in coincidence among inputs on spatiotemporal learning rule
Abstract
The spatiotemporal learning rule (STLR) updates the synaptic weights based on the coincidence among inputs to a neuron, enabling it to discriminate subtle spatiotemporal differences, in contrast to the Hebbian learning rule. In this study, we evaluated the learning performance of STLR by varying the learning coefficient and the time constant of the time history in coincidence. To quantitatively evaluate learning performance, we improved the multistage template-matching method. The results demonstrated that introducing an appropriate time constant enhances context retention and mitigates forgetting during spatiotemporal pattern learning. Furthermore, we used the Modified National Institute of Standards and Technology dataset as actual spatiotemporal patterns. In conclusion, the time history of coincidence is essential for effectively capturing and learning the contextual structures in spatiotemporal patterns.
Fields of Study & Subjects
Cognitive and developmental aspects of mathematical skills
Motor Control and Adaptation
Child and Animal Learning Development
Publication details
- Journal / source
- Nonlinear Theory and Its Applications IEICE
- Publisher
- Institute of Electronics, Information and Communications Engineers (IEICE)
- Volume
- 17
- Issue
- 3
- Pages
- 1213–1224
- Publication date
- 1 January 2026
- Language
- EN