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首页> 外文会议>International Conference on Affective Computing and Intelligent Interaction >Functional Connectivity from EEG Signals during Perceiving Pleasant and Unpleasant Odors
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Functional Connectivity from EEG Signals during Perceiving Pleasant and Unpleasant Odors

机译：从EEG信号感知在感知令人愉悦和令人不快的气味期间的功能连接

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摘要

The olfactory sense is strongly related to memory and emotional processes. Studies on the effects of odor perception from brain activity have been conducted by using different neuro-imaging techniques. In this paper, we analyse electroencephalog-raphy (EEG) of 23 subjects during perceiving pleasant and unpleasant odor stimuli. We describe the construction of brain functional connectivity networks measured by most commonly used models. We discuss the network-based features of functional connectivity, and design classifiers by applying different functional connectivity network features. Finally, we show that pleasant and unpleasant emotions from olfactory perceptions can be better classified if we see the brain as a nonlinear small-world network. By extracting appropriate features from functional connectivity networks, we manage to classify pleasant and unpleasant olfactory perceptions with an average Kappa value of 0.11 ± 0.17, which is significantly non-random.
机译：嗅觉感与记忆和情绪过程密切相关。通过使用不同的神经成像技术，通过了不同的神经成像技术进行了对脑活动的影响。在本文中，我们在感知令人愉悦和令人难以愉快的气味刺激期间分析23个受试者的脑电图（EEG）。我们描述了由最常用的模型测量的脑功能连接网络的构建。我们通过应用不同的功能连接网络功能讨论功能连接的基于网络的特征和设计分类器。最后，如果我们将大脑视为非线性小世界网络，我们表明来自嗅觉感知的愉快和令人不快的情绪可以更好地分类。通过从功能连接网络中提取适当的特征，我们设法分类令人愉快和令人不快的嗅觉感知，平均kappa值为0.11±0.17，这显着非随机。

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