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Visual Decoding of Phrases from Occipital Neuromagnetic Signals

机译:从枕骨神经磁信号的短语视觉解码

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Orthographic visual perception (reading) is encoded via a widespread dynamic interaction between different language centers of the brain and visual cortex. In this study, we investigated orthographic visual perception decoding with Magnetoencephalography (MEG), where phrases were visually presented to participants. We compared the decoding performance obtained with sensors within the occipital lobe that obtained with sensors covering the whole head. Two naive machine learning classifiers namely support vector machines (SVM) and linear discriminant analysis (LDA) were used. Experimental results indicated that the decoding performance using only occipital sensors is similar to the performance obtained with all sensors within the task period, which were all above chance level. In addition, temporal analysis by taking short-time windows showed that the occipital sensors were more discriminative near onset compared to later time periods, while using the whole head sensor setup at later time periods performed slightly better than occipital sensors. This finding may indicate a sequential order (from visual cortex to other areas beyond occipital lobe) during visual speech perception.
机译:正射视觉感知(阅读)通过大脑和视觉皮质的不同语言中心之间的广泛动态相互作用进行编码。在这项研究中,我们调查了用磁性脑图(MEG)进行正交视觉感知解码,其中短语在视觉上呈现给参与者。我们将使用传感器内的传感器和覆盖整个头部的传感器获得的传感器获得的解码性能进行了比较。使用两个天真的机器学习分类器即支持向量机(SVM)和线性判别分析(LDA)。实验结果表明,仅使用枕部传感器的解码性能类似于任务期内的所有传感器获得的性能,这是所有上述机会水平。此外,通过采用短时窗口的时间分析表明,与稍后的时间段相比,枕骨传感器更加差异,同时在稍后的时间段使用整个头部传感器设置稍微比枕骨传感器略好地执行。在视觉语音感知期间,该发现可以指示顺序顺序(从Visual Cortex到枕骨之外的其他区域)。

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