Frans Nordén, Behzad Iravani, Martin Schaefer, Anja L Winter, Mikael Lundqvist, Artin Arshamian, Johan N Lundström
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By doing so, we could determine when subjective valence information was communicated, what kind of information was transferred, and how the information was transferred (i.e., in which frequency band). Support vector machine (SVM) learning was used on the coherence spectrum and frequency-resolved Granger causality to identify valence-dependent differences in functional and effective connectivity between the OB and PC. We found that the OB communicates subjective odor valence to the PC in the gamma band shortly after odor onset, while the PC subsequently feeds broader valence-related information back to the OB in the beta band. Decoding accuracy was better for negative than positive valence, suggesting a focus on negative valence. Critically, we replicated these findings in an independent data set using additional odors across a larger perceived valence range. 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引用次数: 0
摘要
嗅觉系统的一个核心功能是确定气味的价值。在人类中,对气味价值感知的中枢处理已在嗅球(OB)中形成,但这一重要信息与嗅觉皮层(梨状皮层,PC)之间的神经机制尚不清楚。为了评估这两个节点之间的交流,我们同时测量了人类参与者嗅球和PC中依赖于气味的神经活动,同时获得了逐次试验的价值评级。通过这种方法,我们可以确定主观情绪信息何时被传递、传递了何种信息以及信息是如何传递的(即在哪个频段)。我们使用支持向量机(SVM)学习相干频谱和频率分辨格兰杰因果关系,以识别主观情感与主观情感之间的功能和有效连通性的差异。我们发现,在气味开始后不久,嗅觉器官就会在伽马波段将主观气味价值传递给个人计算机,而个人计算机随后会在β波段将与价值相关的信息反馈给嗅觉器官。对负面情绪的解码准确性要好于对正面情绪的解码准确性,这表明负面情绪是解码的重点。重要的是,我们在一个独立的数据集中使用了更多的气味,在更大的感知价位范围内重复了这些发现。综合上述结果,我们发现在特定的时间点,主观气味愉快度的水平会在多个频率上与 OB 和 PC 进行交流,这种交流模式与气味加工的两阶段模型相一致。
The human olfactory bulb communicates perceived odor valence to the piriform cortex in the gamma band and receives a refined representation back in the beta band.
A core function of the olfactory system is to determine the valence of odors. In humans, central processing of odor valence perception has been shown to take form already within the olfactory bulb (OB), but the neural mechanisms by which this important information is communicated to, and from, the olfactory cortex (piriform cortex, PC) are not known. To assess communication between the 2 nodes, we simultaneously measured odor-dependent neural activity in the OB and PC from human participants while obtaining trial-by-trial valence ratings. By doing so, we could determine when subjective valence information was communicated, what kind of information was transferred, and how the information was transferred (i.e., in which frequency band). Support vector machine (SVM) learning was used on the coherence spectrum and frequency-resolved Granger causality to identify valence-dependent differences in functional and effective connectivity between the OB and PC. We found that the OB communicates subjective odor valence to the PC in the gamma band shortly after odor onset, while the PC subsequently feeds broader valence-related information back to the OB in the beta band. Decoding accuracy was better for negative than positive valence, suggesting a focus on negative valence. Critically, we replicated these findings in an independent data set using additional odors across a larger perceived valence range. Combined, these results demonstrate that the OB and PC communicate levels of subjective odor pleasantness across multiple frequencies, at specific time points, in a direction-dependent pattern in accordance with a two-stage model of odor processing.
期刊介绍:
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