Schall Ulrich
Priority Centre for Translational Neuroscience & Mental Health Research, The University of Newcastle, Callaghan, Australia, Hunter Medical Research Institute, Newcastle, Australia, Schizophrenia Research Institute, Sydney, Australia.
Biol Psychol. 2016 Apr;116:41-6. doi: 10.1016/j.biopsycho.2015.09.001. Epub 2015 Sep 2.
Since its inception in the 1970s, the mismatch negativity (MMN) event-related potential has improved our understanding of pre-attentive detection of rule violations, which is a fundamental cognitive process considered by some a form of "primitive intelligence". The body of research to date ranges from animal studies (i.e. when investigating the neural mechanisms and pharmacological properties of MMN generation) to researching the psychophysiological nature of human consciousness. MMN therefore offers the possibility to detect abnormal functioning in the neural system involved in MMN generation, such as it occurs in some neurodevelopmental disorders or patients in vegetative state. While the clinical research data holds considerable promise for translation into clinical practice, standardization and normative data of an optimized (i.e. disorder-specific) MMN recording algorithm is needed in order for MMN to become a valuable clinical investigation tool.
自20世纪70年代出现以来,失匹配负波(MMN)这一事件相关电位增进了我们对违反规则的前注意检测的理解,这是一种被一些人视为“原始智能”形式的基本认知过程。迄今为止的研究范围从动物研究(即研究MMN产生的神经机制和药理学特性时)到研究人类意识的心理生理学本质。因此,MMN为检测参与MMN产生的神经系统的异常功能提供了可能性,比如在一些神经发育障碍或植物人状态患者中出现的情况。虽然临床研究数据在转化为临床实践方面有很大前景,但为了使MMN成为一种有价值的临床研究工具,需要优化(即针对特定疾病)的MMN记录算法的标准化和规范数据。