Language acquisition and statistical learning

Abstract

Statistical learning is a basic mechanism of information processing in the human brain. The purpose lies in the extraction of probabilistic regularities from the multitude of sensory inputs. Principles of statistical learning contribute significantly to language acquisition and presumably also to language recovery following stroke. The empirical database presented in this manuscript demonstrates that the process of word segmentation, acquisition of a lexicon, and acquisition of simple grammatical rules can be entirely explained through statistical learning. Statistical learning is mediated by changes in synaptic weights in neuronal networks. The concept therefore stands at the transition to molecular biology and pharmacology of the neuronal synapse. It still remains to be shown if all aspects of language acquisition can be explained through statistical learning and which regions of the brain are involved in or capable of statistical learning. Principles of effective language training are obvious already. Most important is the massive, repeated interactive exposure. Conscious processing of the stimulus material may not be essential. The crucial principle is a high cooccurrence of language and corresponding sensory processes. This requires a more intense training frequency than traditional aphasia treatment programs provide.