Validation of the Role of Attention Mechanism in Predicting Brain Activity
Validation of the Role of Attention Mechanism in Predicting Brain Activity
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DOI：
10.1109/scisisis55246.2022.10001915
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发表时间：
2022-11
期刊：
影响因子：
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通讯作者：
Haruka Taguchi;S. Nishida;Shinji Nishimoto;Ichiro Kobayashi
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文献类型：
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作者：
Haruka Taguchi;S. Nishida;Shinji Nishimoto;Ichiro Kobayashi
在这项研究中，我们通过从图像识别深度学习模型中提取的图像特征回归大脑活动状态，从视觉刺激中估计人脑的状态。我们将注意力分支网络引入到图像识别深度学习模型中，在提取图像特征时增强了对注意力识别目标特征的捕捉，并从注意力加权或未加权的图像特征中估计大脑活动状态。通过实验验证注意机制在视觉刺激估计脑活动状态中的作用。结果，我们确认了注意力的引入对估计精度没有显著影响，但是在估计精度较高的区域中观察到差异。
In this study, we estimate the state of the human brain from visual stimuli by regressing the brain activity state from image features extracted from an image identification deep learning model. We introduce Attention Branch Network, which enhances to capture the features of the identified target by attention when extracting image features, into the image identification deep learning model and estimate the brain activity state from the image features weighted or unweighted by attention. Through experiments, we aim to verify the role of attention mechanism in estimating brain activity state from visual stimuli. As a result, we confirmed that the introduction of Attention did not have a significant effect on the estimation accuracy, but that differences were observed in the areas where the estimation accuracy was higher.