Parsing Sequentially Presented Commands in a Large-Scale Biologically Realistic Brain Model

35th Annual Conference of the Cognitive Science Society, 2013

Terrence C. Stewart, Chris Eliasmith


We present a neural mechanism for interpreting and executing visually presented commands. These are simple verb-noun commands (such as WRITE THREE) and can also include conditionals ([if] SEE SEVEN, [then] WRITE THREE). We apply this to a simplified version of our large-scale functional brain model "Spaun", where input is a 28x28 pixel visual stimulus, with a different pattern for each word. Output controls a simulated arm, giving hand-written answers. Cortical areas for categorizing, storing, and interpreting information are controlled by the basal ganglia (action selection) and thalamus (routing). The final model has approximately 100,000 LIF spiking neurons. We show that the model is extremely robust to neural damage (40 percent of neurons can be destroyed before performance drops significantly). Performance also drops for visual display times less than 250ms. Importantly, the system also scales to large vocabularies (approximately 100,000 nouns and verbs) without requiring an exponentially large number of neurons.

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35th Annual Conference of the Cognitive Science Society
Cognitive Science Society


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