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Parsing with fLIF Neurons

This paper presents a natural language parsing system based solely on fatiguing Leaky Integrate and Fire neurons, a relatively faithful model of biological neurons. The parser implements cell assemblies, sequences, finite state automaton and a stack. The stack enables the system to parse context free grammars. The system uses variable binding to apply the rules, and implement the stack. A novel form of variable binding based on short term potentiation is presented. The output of the system is a semantic frame of the sentence that was parsed. The symbolic interpretation is derived from the underlying neural firing by a simple count of neurons that fire in a particular cycle. The system parses over 99% of the tested sentences correctly.