Language Evolution and Computation Bibliography

This research takes grammatical constructions (sentence form-to-meaning mappings) as an alternative to abstract generative grammars in the context of understanding the emergence of language. A model of sentence processing based on this construction grammar approach is presented, and then a series of neuropsychological and neurophysiological studies are reviewed that attempt to validate the model and to establish its neurophysiological underpinnings. The resulting model is demonstrated to provide insight into a developmental and evolutionary passage from unitary idiom-like holophrases to progressively more abstract grammatical constructions. The model is then functionally validated by its insertion into a perceptually grounded system that allows spoken language interaction with a human interlocutor. The potential utility of this emergence approach in understanding language is discussed.

The objective of this research is to develop a system for language learning based on a ``minimum'' of pre-wired language-specific functionality, that is compatible with observations of perceptual and language capabilities in the human developmental trajectory. In the proposed system, meaning (in terms of descriptions of events and spatial relations) is extracted from video images based on detection of position, motion, physical contact and their parameters. Meaning extraction requires attentional mechanisms that are implemented from low-level perceptual primitives. Mapping of sentence form to meaning is performed by learning grammatical constructions, i.e., sentence to meaning mappings as defined by Goldberg [Goldberg, A. (1995). Constructions. Chicago and London: Univ. of Chicago Press]. These are stored and retrieved from a ``construction inventory'' based on the constellation of grammatical function words uniquely identifying the target sentence structure. The resulting system displays robust acquisition behavior that reproduces certain observations from developmental studies, with very modest ``innate'' language specificity.

The current research describes a functional trajectory from sensorimotor sequence learning to the learning of grammatical constructions in language. A brief review of the functional neurophysiology of the cortex and basal ganglia will be provided as background for a neural network model of this system in sensorimotor sequence learning. Sequential behavior is then defined in terms of serial, temporal and abstract structure. The resulting neuro-computational framework is demonstrated to account for observed sequence learning behavior. More interestingly, this framework naturally extends to grammatical constructions as form-to-meaning mappings. Predictions from the neuro-computational model concerning parallels in language and cognitive sequence processing are tested against behavioral and neurophysiological observations in humans, resulting in a refinement of the allocation of model functions to subdivisions of Broca's area. From a functional perspective this analysis will provide insight into the relation between the coding structure in human languages, and constraints derived from the underlying neurophysiological computational mechanisms.

Abstract: In order to understand the evolutionary pathway to the capability for language, we must first clearly understand the functional capabilities that the child brings to the task of language acquisition. Behavioral studies provide insight into infants' ability to extract ...