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通过卷积和最优线性加权将 BOLD fMRI 与神经振荡联系起来。

Relating BOLD fMRI and neural oscillations through convolution and optimal linear weighting.

机构信息

Sir Peter Mansfield Magnetic Resonance Centre, School of Physics and Astronomy, University of Nottingham, University Park, Nottingham, NG7 2RD, UK.

出版信息

Neuroimage. 2010 Jan 15;49(2):1479-89. doi: 10.1016/j.neuroimage.2009.09.020. Epub 2009 Sep 22.

Abstract

The exact relationship between neural activity and BOLD fMRI is unknown. However, several recent findings, recorded invasively in both humans and monkeys, show a positive correlation of BOLD to high-frequency (30-150 Hz) oscillatory power changes and a negative correlation to low-frequency (8-30 Hz) power changes arising from cortical areas. In this study, we computed the time series correlation between BOLD GE-EPI fMRI at 7 T and neural activity measures from noninvasive MEG, using a time-frequency beam former for source localisation. A sinusoidal drifting grating was presented visually for 4 s followed by a 20 s rest period in both recording modalities. The MEG time series were convolved with either a measured or canonical haemodynamic response function (HRF) for comparison with the measured BOLD data, and the BOLD data were deconvolved with either a measured or a canonical HRF for comparison with the measured MEG. In the visual cortex, the higher frequencies (mid-gamma=52-75 Hz and high-gamma=75-98 Hz) were positively correlated with BOLD whilst the lower frequencies (alpha=8-12 Hz and beta=12-25 Hz) were negatively correlated with BOLD. Furthermore, regression including all frequency bands predicted BOLD better than stimulus timing alone, although no individual frequency band predicted BOLD as well as stimulus timing. For this paradigm, there was, in general, no difference between using the SPM canonical HRF compared to the subject-specific measured HRF. In conclusion, MEG replicates findings from invasive recordings with regard to time series correlations with BOLD data. Conversely, deconvolution of BOLD data provides a neural estimate which correlates well with measured neural effects as a function of neural oscillation frequency.

摘要

神经活动与 BOLD fMRI 的确切关系尚不清楚。然而,最近的几项发现,在人类和猴子的侵入性记录中都显示出 BOLD 与高频(30-150 Hz)振荡功率变化呈正相关,与源自皮质区域的低频(8-30 Hz)功率变化呈负相关。在这项研究中,我们使用时频波束形成器进行源定位,计算了 7 T 下 BOLD GE-EPI fMRI 与非侵入性 MEG 神经活动测量之间的时间序列相关性。在两种记录模式下,视觉呈现正弦漂移光栅 4 秒,然后休息 20 秒。将 MEG 时间序列与测量或标准血液动力学响应函数(HRF)卷积,以与测量的 BOLD 数据进行比较,并将 BOLD 数据与测量或标准 HRF 去卷积,以与测量的 MEG 进行比较。在视觉皮层中,较高频率(中伽马=52-75 Hz 和高伽马=75-98 Hz)与 BOLD 呈正相关,而较低频率(阿尔法=8-12 Hz 和贝塔=12-25 Hz)与 BOLD 呈负相关。此外,包括所有频带的回归比刺激时间本身更好地预测了 BOLD,尽管没有单个频带像刺激时间那样好地预测了 BOLD。对于这种范式,使用 SPM 标准 HRF 与使用特定于受试者的测量 HRF 相比,通常没有区别。总之,MEG 复制了侵入性记录中关于与 BOLD 数据的时间序列相关性的发现。相反,BOLD 数据的反卷积提供了一个与测量的神经效应很好相关的神经估计,作为神经振荡频率的函数。

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