Breitenstein C, Knecht S
Klinik und Poliklinik für Neurologie, Universität Münster.
Nervenarzt. 2003 Feb;74(2):133-43. doi: 10.1007/s00115-002-1466-1.
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.
统计学习是人类大脑信息处理的一种基本机制。其目的在于从大量的感官输入中提取概率规律。统计学习原理对语言习得有显著贡献,并且推测对中风后的语言恢复也有作用。本手稿中呈现的实证数据库表明,单词分割、词汇习得以及简单语法规则的习得过程都可以完全通过统计学习来解释。统计学习由神经网络中突触权重的变化介导。因此,这一概念处于向神经元突触的分子生物学和药理学过渡的阶段。语言习得的所有方面是否都能通过统计学习来解释,以及大脑的哪些区域参与或能够进行统计学习,仍有待证明。有效的语言训练原则已经很明显了。最重要的是大量、重复的互动接触。对刺激材料进行有意识的处理可能并非必不可少。关键原则是语言与相应感官过程的高度共现。这需要比传统失语症治疗方案更高的训练频率。