Simulated Language Acquisition in a Biologically Realistic Model of the Brain

Abstract

Despite tremendous progress in neuroscience, we do not have a compelling narrative for the precise way whereby the spiking of neurons in our brain results in high-level cognitive phenomena such as planning and language. NO_SCPLOWEMOC_SCPLOW is a simple mathematical formulation of six basic and broadly accepted principles of neuroscience: excitatory neurons, brain areas, random synapses, Hebbian plasticity, local inhibition, and inter-area inhibition. We implement with NO_SCPLOWEMOC_SCPLOW a simulated neuromorphic system, which is capable of basic language acquisition: starting from a tabula rasa, the system learns, in any language, the semantics of words, their syntactic role (verb versus noun), the word order of the language, and the ability to generate novel sentences, all through the exposure to a number of grounded sentences in the same language that is similar to language acquisition by humans. We discuss several possible extensions and implications of this result.