Literature DB >> 23747482

High-throughput optogenetic functional magnetic resonance imaging with parallel computations.

Zhongnan Fang1, Jin Hyung Lee.   

Abstract

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.
Copyright © 2013 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  GPU; Initial dip; Motion correction; Optogenetics; Parallel; ofMRI

Mesh:

Year:  2013        PMID: 23747482      PMCID: PMC4221590          DOI: 10.1016/j.jneumeth.2013.04.015

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


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  17 in total

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