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皮质-纹状体语言通路对句法复杂性进行动态调整:一项计算研究。

Cortico-striatal language pathways dynamically adjust for syntactic complexity: A computational study.

作者信息

Szalisznyó Krisztina, Silverstein David, Teichmann Marc, Duffau Hugues, Smits Anja

机构信息

Department of Neuroscience, Psychiatry, University Hospital, Uppsala University, 751 85 Uppsala, Sweden; Computational Neuroscience Group, Wigner Research Institute, Hungarian Academy of Sciences, P.O. Box 49, Budapest, Hungary.

Department of Computational Science and Technology, KTH Royal Institute of Technology; Stockholm Brain Institute, Karolinska Institutet, Stockholm, Sweden.

出版信息

Brain Lang. 2017 Jan;164:53-62. doi: 10.1016/j.bandl.2016.08.005. Epub 2016 Oct 25.

Abstract

A growing body of literature supports a key role of fronto-striatal circuits in language perception. It is now known that the striatum plays a role in engaging attentional resources and linguistic rule computation while also serving phonological short-term memory capabilities. The ventral semantic and the dorsal phonological stream dichotomy assumed for spoken language processing also seems to play a role in cortico-striatal perception. Based on recent studies that correlate deep Broca-striatal pathways with complex syntax performance, we used a previously developed computational model of frontal-striatal syntax circuits and hypothesized that different parallel language pathways may contribute to canonical and non-canonical sentence comprehension separately. We modified and further analyzed a thematic role assignment task and corresponding reservoir computing model of language circuits, as previously developed by Dominey and coworkers. We examined the models performance under various parameter regimes, by influencing how fast the presented language input decays and altering the temporal dynamics of activated word representations. This enabled us to quantify canonical and non-canonical sentence comprehension abilities. The modeling results suggest that separate cortico-cortical and cortico-striatal circuits may be recruited differently for processing syntactically more difficult and less complicated sentences. Alternatively, a single circuit would need to dynamically and adaptively adjust to syntactic complexity.

摘要

越来越多的文献支持额-纹状体回路在语言感知中起关键作用。现在已知纹状体在调动注意力资源和语言规则计算中发挥作用,同时还具备语音短期记忆能力。口语处理中假设的腹侧语义流和背侧语音流二分法似乎在皮质-纹状体感知中也起作用。基于最近将深部布洛卡-纹状体通路与复杂句法表现相关联的研究,我们使用了先前开发的额-纹状体句法回路计算模型,并假设不同的并行语言通路可能分别有助于规范和非规范句子的理解。我们修改并进一步分析了如多米尼及其同事先前开发的主题角色分配任务和相应的语言回路储层计算模型。我们通过影响呈现的语言输入衰减的速度以及改变激活的单词表征的时间动态,在各种参数条件下检查了模型的性能。这使我们能够量化规范和非规范句子的理解能力。建模结果表明,对于句法上更难和不太复杂的句子,可能会以不同方式调用单独的皮质-皮质和皮质-纹状体回路。或者,单个回路需要动态且自适应地调整以适应句法复杂性。

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