本文重点介绍了使用同步fMRI-EEG对人脑功能进行体内成像,探论了基于fMRI和EEG同步成像的人脑功能的最新进展,概述了同步fMRI-EEG记录存在的挑战,以及从MRI扫描仪内记录的EEG数据中去除伪影的技术。最后,给出了设计实验以提高fMRI和EEG实用性的技术指南,以及整合fMRI和EEG数据以实现高时空分辨率的各种方法。 血氧水平依赖...
本文重点介绍了使用同步fMRI-EEG对人脑功能进行体内成像,探论了基于fMRI和EEG同步成像的人脑功能的最新进展,概述了同步fMRI-EEG记录存在的挑战,以及从MRI扫描仪内记录的EEG数据中去除伪影的技术。最后,给出了设计实验以提高fMRI和EEG实用性的技术指南,以及整合fMRI和EEG数据以实现高时空分辨率的各种方法。 血氧水平依赖...
A M/EEG-fMRI Fusion Primer: Resolving Human Brain Responses in Space and Time..Neuron. 作者|大发 排版|Uka 校对|喵君姐姐 昆昆 往期推荐 文献| PNAS:青年时期人脑网络结构-功能耦合的发展 文献| 相较于传统fNIRS,时域矩量fNIRS在多大程度上提高了对大脑活动的设计? 文献| Cell Reports:任栓成/高东/...
2.Dong, L., et al., 2014. Simultaneous EEG-fMRI:Trial level spatio-temporal fusion for hierarchically reliable informationdiscovery. Neuroimage. 99,28-41. 3.Dong, L., et al., 2015a. Local MultimodalSerial Analysis for Fusing EEG-fMRI: A New Method to Study Familial CorticalMyoclonic Trem...
#EEG-fMRI2个 导读 功能性磁共振成像(fMRI)和脑电图(EEG)是用于测量人脑神经活动的非侵入性技术。fMRI测量的是与神经活动血流动力学变化相关的磁共振信号,具有良好的空间分辨率(2-3mm各向同性)和较低的时间分辨率(1-3s)。而EEG用于以毫秒级的时间分辨率记录大脑中的电活动,但空间分辨率有限。通过fMRI和EEG的结合...
EEG-fMRI information fusion: biophysics and data analysis. In: Mulert, C., Lemieux, L. (Eds.), E.E.G.-FM.R.I.Springer, Berlin, pp. 511-526Daunizeau, J., Laufs, H., Friston, K., 2010. EEG-fMRI information fusion: Biophysics and data analysis. In: Mulert, C., Lemieux, L...
EEGandfMRIare complementary modalifieswith repect to spatiotemporal resolution.Through fusionofEEGand fMPd,hi曲spacial and temporal resolution informationabout underlyingneuro-activity canbe achieved,and thelimitationsin uni-modalanalysis ofEEGandfMRIareovercomed effectively. Inthis paper,several essentialaspec...
The combination of electroencephalography (EEG) with functional magnetic resonance imaging (fMRI) forms a powerful tool for the investigation of brain function, but concurrent implementation of EEG and fMRI poses many technical challenges. Here, the moti
, integration through prediction like in the discussed EEG–fMRI epilepsy studies) or ζfMRI ((ii): fMRI to EEG approaches, i.e., integration through constraints). In contradistinction, symmetrical EEG–fMRI fusion approaches rely on a joint EEG–fMRI generative model, which allows the estimation...
et al. Novel machine learning-driven comparative analysis of CSP, STFT, and CSP-STFT fusion for EEG data classification across multiple meditation and non-meditation sessions in BCI pipeline. Brain Inf. 12, 4 (2025). https://doi.org/10.1186/s40708-025-00251-4 Download citation Received28 ...