# Improving with Practice: A Neural Model of Mathematical Development

- Sean Aubin,
*University of Waterloo, Waterloo, Ontario, Canada*
- Aaron Voelker,
*University of Waterloo, Waterloo, Ontario, Canada*
- Chris Eliasmith,
*University of Waterloo, Waterloo, Ontario, Canada*

## Abstract

The ability to improve in speed and accuracy as a result of
repeating some task is an important hallmark of intelligent biological systems.
We model the progression from a counting-based strategy for addition to a
recall-based strategy. The model consists of two networks working in parallel: a
slower basal ganglia loop, and a faster cortical network. The slow network
methodically computes the count from one digit given another, corresponding to
the addition of two digits, while the fast network gradually "memorizes" the
output from the slow network. The faster network eventually learns how to add the
same digits that initially drove the behaviour of the slower network. Performance
of this model is demonstrated by simulating a fully spiking neural network that
includes basal ganglia, thalamus and various cortical areas.

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