High-throughput optogenetic functional magnetic resonance imaging with parallel computations.
High-throughput optogenetic functional magnetic resonance imaging with parallel computations.
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DOI：
10.1016/j.jneumeth.2013.04.015
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发表时间：
2013-09-15
影响因子：
3
通讯作者：
Lee, Jin Hyung
中科院分区：
文献类型：
--
作者：
Fang, Zhongnan;Lee, Jin Hyung
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的活动结果。由于能够精确控制兴奋和抑制参数，并准确记录由此产生的活动，越来越需要一种高通量方法来充分发挥 ofMRI 研究的潜力。本文提出了一种先进的系统，可以在 MRI 采集重复时间 (TR) 的一小部分内实现实时功能磁共振成像的交互式控制和分析。凭借如此高的处理速度，将有足够的时间来集成未来的发展，从而进一步提高 MRI 数据质量或更好地简化研究。我们使用图形处理单元 (GPU) 设计并实现了高度优化的大规模并行系统，该系统在大约 12.80 毫秒内实现了 3D 体数据的重建、运动校正和分析。因此，通过 750 ms TR 和 4 个插叶 fMRI 采集，我们现在可以在大约 1.7% 的 TR 中进行滑动窗口重建、运动校正、分析和显示。因此，现在可以分配大量时间来集成先进但计算密集型的方法，这些方法可以在 TR 内实现更高的图像质量和更好的分析结果。利用所提出的具有滑动窗口重建的高通量成像平台，我们还能够观察到我们的 ofMRI 数据中备受争议的初始下降。结合进一步提高信噪比的方法，所提出的系统将实现高效、实时、交互式、高通量的 MRI 研究。
Optogenetic functional magnetic resonance imaging (ofMRI) technology enables cell-type specific, temporally precise neuronal control and accurate, in vivo readout of resulting activity across the whole brain. With the ability to precisely control excitation and inhibition parameters, and to accurately record the resulting activity, there is an increased need for a high-throughput method to bring the ofMRI studies to their full potential. In this paper, an advanced system that can allow real-time fMRI with interactive control and analysis in a fraction of the MRI acquisition repetition time (TR) is proposed. With such high processing speed, sufficient time will be available for integration of future developments that can further enhance ofMRI data quality or better streamline the study. We designed and implemented a highly optimized, massively parallel system using graphics processing unit (GPU)s which achieves 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 can enable higher image quality and better analysis results all within a TR. Utilizing the proposed high-throughput imaging platform with sliding window reconstruction, we were also able to observe the much-debated initial dips in our ofMRI data. Combined with methods to further improve SNR, the proposed system will enable efficient real-time, interactive, high-throughput ofMRI studies.
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