@inproceedings{f14247196da34837b3af4cfa9ecd2309,
title = "A spiking neural architecture that learns tasks",
abstract = "Cognitive architectures based on neural networks typically use the Basal Ganglia to model sequential behavior. A challenge for such models is to explain how the Basal Ganglia can learn to do new tasks relatively quickly. Here we present a model in which task-specific procedural knowledge is stored in a separate memory, and is executed by general procedures in the Basal Ganglia. In other words, learning happens elsewhere. The implementation discussed here is implemented in the Nengo cognitive architecture, but based on the principles of the PRIMs architecture. As a demonstration we model data from a mind-wandering experiment.",
keywords = "Basal Ganglia, Mind Wandering, Nengo, PRIMS, Skill Acquisition, Spiking neural networks",
author = "Niels Taatgen",
note = "Publisher Copyright: {\textcopyright} ICCM 2019.All rights reserved.; 17th International Conference on Cognitive Modeling (2020) ; Conference date: 17-08-2020 Through 18-08-2020",
year = "2020",
language = "English",
isbn = "9780998508238",
series = "Proceedings of ICCM 2019 - 17th International Conference on Cognitive Modeling",
publisher = "Applied Cognitive Science Lab, Penn State",
pages = "253--258",
editor = "Stewart, {Terrence C.}",
booktitle = "Proceedings of ICCM 2019 - 17th International Conference on Cognitive Modeling",
}