A General Purpose Architecture for Building Spiking Neuron Models of Biological Cognition

Abstract

We have recently created the world's largest biologically realistic brain model that is capable of performing tasks (Eliasmith et al., 2012). This model uses 2.5 million spiking neurons, takes visual input from a 28x28 pixel visual field, and controls a physically modelled arm. By presenting different visual inputs, the model can perform eight different tasks, including memorizing and writing a list of numbers, single-digit addition via counting, and flexible pattern completion in the Raven's Matrices task. This tutorial is meant to introduce the software toolkit and theoretical background that would allow other researchers to build their own models using the same architecture, allowing them to explore other tasks and brain functions. This tool supports a novel cognitive architecture (SPA; the Semantic Pointer Architecture) that directly connects neuroscience with cognitive science.


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