首页|基于神经成像技术的味觉解码研究进展

基于神经成像技术的味觉解码研究进展

扫码查看
味觉感知的神经基础作为认知神经科学与感官科学研究的交汇点,正日益受到学界的关注.本文综述应用神经成像技术于味觉解码领域的最新研究进展,深入探讨大脑如何依赖其精细的神经网络处理味觉信息,并实现从感官输入到复杂认知功能的转换.脑电图(EEG)以其高时间分辨率捕捉大脑对味觉刺激的即时电生理反应,而功能性磁共振成像(fMRI)则利用其高空间分辨率详细映射大脑对味觉刺激的血液动力学响应.此外,功能性近红外光谱成像(fNIRS)技术以其对运动伪影的低敏感性和良好的时间分辨率,为在自然行为条件下监测味觉处理提供了新的视角.本文综合评述这些技术揭示的味觉感知神经网络结构,并讨论它们在增进对味觉感知机制的理解以及在相关疾病的诊断和治疗中的应用潜力.
Advancements in Gustatory Decoding Based on Neuroimaging Techniques
The neural basis of gustatory perception,as a convergence point of cognitive neuroscience and sensory sci-ence,is increasingly gaining scholarly attention.This review summarized the latest research advances in the application of neuroimaging techniques to the field of gustatory decoding,delving into how the brain relied on its intricate neural net-works to process gustatory information and transition from sensory input to complex cognitive functions.Electroencephalog-raphy(EEG)captured the immediate electrophysiological responses of the brain to gustatory stimuli with its high temporal resolution,while functional magnetic resonance imaging(fMRI)mapped the hemodynamic responses of the brain to gus-tatory stimuli with its high spatial resolution.Additionally,functional near-infrared spectroscopy(fNIRS)technology,with its low sensitivity to motion artifacts and good temporal resolution,provided a new perspective for monitoring taste pro-cessing under natural behavioral conditions.This review synthesized the neural network structures of gustatory perception revealed by these techniques and discussed their potential applications in enhancing our understanding of the mechanisms of gustatory perception and in the diagnosis and treatment of related diseases.

gustatory perceptionelectroencephalography(EEG)functional magnetic resonance imaging(fMRI)function-al near-infrared spectroscopy(fNIRS)spatial distribution

刘源、朱忆雯、樊玉霞、仇晨曦

展开 >

宁夏大学食品科学与工程学院 银川 750021

上海交通大学农业与生物学院 上海 200240

味觉感知 脑电图 功能性磁共振成像 功能性近红外光谱成像 空间分布

2024

中国食品学报
中国食品科学技术学会

中国食品学报

CSTPCD北大核心EI
影响因子:1.079
ISSN:1009-7848
年,卷(期):2024.24(8)