Department of Electrical Engineering, Stanford University, CA 94305, USA.
J Neurosci Methods. 2013 Sep 15;218(2):184-95. doi: 10.1016/j.jneumeth.2013.04.015. Epub 2013 Jun 4.
Optogenetic functional magnetic resonance imaging (of MRI) technology enables cell-type-specific, temporally precise neuronal control and the accurate, in vivo readout of the resulting activity across the entire brain. With the ability to precisely control excitation and inhibition parameters and accurately record the resulting activity, there is an increased need for a high-throughput method to bring the of MRI studies to their full potential. In this paper, an advanced system facilitating real-time fMRI with interactive control and analysis in a fraction of the MRI acquisition repetition time (TR) is proposed. With high-processing speed, sufficient time will be available for the integration of future developments that further enhance of MRI data or streamline the study. We designed and implemented a highly optimised, massively parallel system using graphics processing units (GPUs), which achieves the reconstruction, motion correction, and analysis of 3D volume data in approximately 12.80 ms. As a result, with a 750 ms TR and 4 interleaf fMRI acquisition, we can now conduct sliding window reconstruction, motion correction, analysis and display in approximately 1.7% of the TR. Therefore, a significant amount of time can now be allocated to integrating advanced but computationally intensive methods that improve image quality and enhance the analysis results within a TR. Utilising the proposed high-throughput imaging platform with sliding window reconstruction, we were also able to observe the much-debated initial dips in our of MRI data. Combined with methods to further improve SNR, the proposed system will enable efficient real-time, interactive, high-throughput of MRI studies.
光遗传学功能磁共振成像(ofMRI)技术能够实现细胞类型特异性、时间精确的神经元控制,并准确地在体内读出整个大脑中由此产生的活动。通过精确控制兴奋和抑制参数并准确记录由此产生的活动,人们对高通量方法的需求越来越大,以充分发挥 ofMRI 研究的潜力。本文提出了一种先进的系统,能够在磁共振成像采集重复时间(TR)的一小部分内实现实时 fMRI,并具有交互式控制和分析功能。由于具有高速处理能力,将有足够的时间来整合进一步增强 ofMRI 数据或简化研究的未来发展。我们设计并实现了一个使用图形处理单元(GPU)的高度优化、大规模并行系统,该系统可以在大约 12.80 毫秒内重建、运动校正和分析三维体积数据。因此,在 750 毫秒 TR 和 4 个交错 fMRI 采集的情况下,我们现在可以在大约 1.7%的 TR 内进行滑动窗口重建、运动校正、分析和显示。因此,现在可以分配大量时间来整合先进但计算密集型的方法,这些方法可以提高图像质量并在 TR 内增强分析结果。利用具有滑动窗口重建功能的高速成像平台,我们还能够观察到我们的 ofMRI 数据中备受争议的初始下降。结合进一步提高 SNR 的方法,该系统将能够实现高效的实时、交互式、高通量 ofMRI 研究。