Centre for Cognitive and Brain Sciences, University of Macau, Macau S.A.R., China.
Faculty of Health Sciences, University of Macau, Macau S.A.R.., China.
Neural Plast. 2020 Oct 6;2020:8882207. doi: 10.1155/2020/8882207. eCollection 2020.
The current study is aimed at establishing links between brain network examination and neural plasticity studies measured by optical neuroimaging. Sixteen healthy subjects were recruited from the University of Macau to test the Granger Prediction Estimation (GPE) method to investigate brain network connectivity during figurative language comprehension. The method is aimed at mapping significant causal relationships across language brain networks, captured by functional near-infrared spectroscopy measurements (fNIRS): (i) definition of regions of interest (ROIs) based on significant channels extracted from spatial activation maps; (ii) inspection of significant causal relationships in temporal resolution, exploring the experimental task agreement; and (iii) early identification of stronger causal relationships that guide neuromodulation intervention, targeting impaired connectivity pathways. Our results propose top-down mechanisms responsible for perceptive-attention engagement in the left anterior frontal cortex and bottom-up mechanism in the right hemispheres during the semantic integration of figurative language. Moreover, the interhemispheric directional flow suggests a right hemisphere engagement in decoding unfamiliar literal sentences and fine-grained integration guided by the left hemisphere to reduce ambiguity in meaningless words. Finally, bottom-up mechanisms seem activated by logographic-semantic processing in literal meanings and memory storage centres in meaningless comprehension. To sum up, our main findings reveal that the Granger Prediction Estimation (GPE) integrated strategy proposes an effective link between assessment and intervention, capable of enhancing the efficiency of the treatment in language disorders and reducing the neuromodulation side effects.
本研究旨在建立脑网络检查与通过光神经影像学测量的神经可塑性研究之间的联系。从澳门大学招募了 16 名健康受试者来测试格兰杰预测估计（GPE）方法，以研究隐喻语言理解过程中的大脑网络连通性。该方法旨在通过功能近红外光谱测量（fNIRS）映射语言大脑网络中的显著因果关系：（i）基于从空间激活图中提取的显著通道定义感兴趣区域（ROI）；（ii）检查时间分辨率中的显著因果关系，探索实验任务的一致性；（iii）早期识别更强的因果关系，指导神经调节干预，针对受损的连通性途径。我们的结果提出了自上而下的机制，负责在隐喻语言的语义整合过程中左前额皮质的感知注意力参与，以及右半球的自下而上的机制。此外，半球间的定向流表明右半球参与解码不熟悉的字面句子，并由左半球引导进行细粒度的整合，以减少无意义单词的歧义。最后，似乎自下而上的机制通过文字意义中的象形语义处理和无意义理解中的记忆存储中心被激活。总之，我们的主要发现表明，格兰杰预测估计（GPE）集成策略在评估和干预之间提出了有效的联系，能够提高语言障碍治疗的效率，并减少神经调节的副作用。
