基于模型的区分方法在皮质电图中定位情绪影响

A. Kaplan, Qi Cheng, P. Karande, Elizabeth Tran, M. Bijanzadeh, Heather E. Dawes, E. Chang
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引用次数: 0

摘要

使用皮质电图(ECoG)传感器获得的大脑活动的详细记录为探索人类大脑的活动提供了机会。我们研究了ECoG阵列数据在受试者情绪影响方面的信息内容。对数正态谱模型是根据接受难治性癫痫监测的患者的数据估计的。针对这一问题,提出了一种基于模型的判别位置映射方法。ECoG阵列的不同空间敏感性允许对局部脑活动进行回顾性分析。我们的判别措施评估信息内容在每个传感器位置相对于积极和消极的情绪影响的表现。这个测度可以用估计模型之间的对称Kullback-Leibler散度来近似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Localization of Emotional Affect in Electrocorticography Using a Model Based Discrimination Measure
Detailed recordings of brain activity acquired using Electrocorticography (ECoG) sensors offer an opportunity to explore the activity of the human brain. We study the information content of ECoG array data with respect to the emotional affect of the subject. Lognormal spectral models are estimated on data from patients undergoing monitoring for intractable epilepsy. A model based approach for mapping discriminative locations is developed for this problem. Differing spatial sensitivity in the ECoG array allows for retrospective analysis of localized brain activity. Our discriminability measure evaluates the information content at each sensor location relative to Positive and Negative displays of emotional affect. This measure can be approximated by a symmetrized Kullback-Leibler divergence between the estimated models.
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