Brain Language Laboratory, Department of Philosophy and Humanities, WE4 Freie Universität Berlin, Habelschwerdter Allee 45, 14195, Berlin, Germany.
Berlin School of Mind and Brain, Humboldt Universität zu Berlin, Luisenstraße 56, 10117, Berlin, Germany.
Sci Rep. 2019 Mar 5;9(1):3579. doi: 10.1038/s41598-019-39864-1.
In blind people, the visual cortex takes on higher cognitive functions, including language. Why this functional reorganisation mechanistically emerges at the neuronal circuit level is still unclear. Here, we use a biologically constrained network model implementing features of anatomical structure, neurophysiological function and connectivity of fronto-temporal-occipital areas to simulate word-meaning acquisition in visually deprived and undeprived brains. We observed that, only under visual deprivation, distributed word-related neural circuits 'grew into' the deprived visual areas, which therefore adopted a linguistic-semantic role. Three factors are crucial for explaining this deprivation-related growth: changes in the network's activity balance brought about by the absence of uncorrelated sensory input, the connectivity structure of the network, and Hebbian correlation learning. In addition, the blind model revealed long-lasting spiking neural activity compared to the sighted model during word recognition, which is a neural correlate of enhanced verbal working memory. The present neurocomputational model offers a neurobiological account for neural changes following sensory deprivation, thus closing the gap between cellular-level mechanisms, system-level linguistic and semantic function.
在盲人中，视觉皮层承担了更高的认知功能，包括语言。为什么这种功能重组在神经元回路水平上会机械地出现，目前还不清楚。在这里，我们使用一个受生物约束的网络模型来模拟视觉剥夺和未剥夺大脑中的词义习得，该模型实现了额颞枕区域的解剖结构、神经生理功能和连接性的特征。我们观察到，只有在视觉剥夺的情况下，与单词相关的分布式神经回路才会“进入”被剥夺的视觉区域，从而承担语言-语义作用。有三个因素对于解释这种与剥夺相关的生长至关重要：由于缺乏不相关的感觉输入而导致的网络活动平衡的变化、网络的连接结构以及赫布氏相关学习。此外，与有视力的模型相比，盲模型在识别单词时显示出持续的尖峰神经活动，这是增强言语工作记忆的神经相关物。本神经计算模型为感觉剥夺后的神经变化提供了神经生物学解释，从而弥合了细胞水平机制、系统水平语言和语义功能之间的差距。
