人工智能的智能:利用机器学习对大脑解码的研究和大脑功能的分析

Q4 Medicine
I. Kobayashi
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引用次数: 0

摘要

在本文中,我们提出了一种基于人类大脑活动的深度学习模型生成自然语言描述的大脑解码方法。此外,为了阐明大脑的功能,我们重点研究了预测编码,它被假设为大脑皮层的功能之一。我们调查了深度学习模型的预测与实际大脑活动数据之间的一致性,以验证预测编码假设。此外,我们提出了一种使用相同的验证模型从人脑活动数据生成图像的方法。(2020年11月9日收稿,2020年12月7日收稿)
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligence of Artificial Intelligence : A Study on Brain Decoding using Machine Learning and the Analysis of Brain Functions
In this paper, we propose a brain decoding method for the generation of natural language descriptions based on human brain activity by a deep learning model. In addition, to elucidate brain functions, we focused on predictive coding, which is hypothesized to be one of the functions of the cerebral cortex. We investigated the agreement between the predictions of deep learning model and the actual brain activity data to test the predictive coding hypothesis. Furthermore, we propose a method for generating images from human brain activity data by using the same validation model. (Received November 9, 2020;accepted December 7, 2020)
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