Division of Psychology and Language Sciences, University College London, London, United Kingdom.
Department of Philology, University of Huelva, Huelva, Spain.
Neurosci Biobehav Rev. 2017 Dec;83:742-764. doi: 10.1016/j.neubiorev.2016.07.029. Epub 2016 Jul 27.
Schizophrenia (SZ) and autism spectrum disorders (ASD) are characterised by marked language deficits, but it is not clear how these arise from gene mutations associated with the disorders. Our goal is to narrow the gap between SZ and ASD and, ultimately, give support to the view that they represent abnormal (but related) ontogenetic itineraries for the human faculty of language. We will focus on the distinctive oscillatory profiles of the SZ and ASD brains, in turn using these insights to refine our understanding of how the brain implements linguistic computations by exploring a novel model of linguistic feature-set composition. We will argue that brain rhythms constitute the best route to interpreting language deficits in both conditions and mapping them to neural dysfunction and risk alleles of the genes. Importantly, candidate genes for SZ and ASD are overrepresented among the gene sets believed to be important for language evolution. This translational effort may help develop an understanding of the aetiology of SZ and ASD and their high prevalence among modern populations.
精神分裂症 (SZ) 和自闭症谱系障碍 (ASD) 的特点是明显的语言缺陷，但目前尚不清楚这些缺陷是如何由与这些疾病相关的基因突变引起的。我们的目标是缩小 SZ 和 ASD 之间的差距，并最终支持这样一种观点，即它们代表了人类语言能力异常（但相关）的个体发生轨迹。我们将重点研究 SZ 和 ASD 大脑的独特振荡模式，反过来，通过探索语言特征集组成的新模型，利用这些见解来深化我们对大脑如何通过探索语言特征集组成的新模型来实现语言计算的理解。我们将认为，脑节律是解释这两种情况下语言缺陷并将其映射到神经功能障碍和基因风险等位基因的最佳途径。重要的是，SZ 和 ASD 的候选基因在被认为对语言进化重要的基因集中过度表达。这种转化努力可能有助于我们了解 SZ 和 ASD 的病因及其在现代人群中的高患病率。
