Different brain regions exhibit complex information processing even at rest. Therefore, assessing temporal correlations between regions permits task-free visualization of their ‘resting state connectivity’. Although functional MRI (fMRI) is widely used for mapping resting state connectivity in the human brain, it is not well suited for ‘microvascular scale’ imaging in rodents because of its limited spatial resolution. Moreover, co-registered cerebral blood flow (CBF) and total hemoglobin (HbT) data are often unavailable in conventional fMRI experiments. Therefore, we built a customized system that combines laser speckle contrast imaging (LSCI), intrinsic optical signal (IOS) imaging and fluorescence imaging (FI) to generate multi-contrast functional connectivity maps at a spatial resolution of 10 μm. This system comprised of three illumination sources: a 632 nm HeNe laser (for LSCI), a 570 nm ± 5 nm filtered white light source (for IOS), and a 473 nm blue laser (for FI), as well as a sensitive CCD camera operating at 10 frames per second for image acquisition. The acquired data enabled visualization of changes in resting state neurophysiology at microvascular spatial scales. Moreover, concurrent mapping of CBF and HbT-based temporal correlations enabled in vivo mapping of how resting brain regions were linked in terms of their hemodynamics. Additionally, we complemented this approach by exploiting the transit times of a fluorescent tracer (Dextran-FITC) to distinguish arterial from venous perfusion. Overall, we demonstrated the feasibility of wide area mapping of resting state connectivity at microvascular resolution and created a new toolbox for interrogating neurovascular function.
Janaka Senarathna, Darian Hadjiabadi, Stacy Gil, Nitish V. Thakor, Arvind P. Pathak, and Namrata Batra, "Wide-area mapping of resting state hemodynamic correlations at microvascular resolution with multi-contrast optical imaging (Conference Presentation)," Proc. SPIE 10051, Neural Imaging and Sensing, 100510Z (Presented at SPIE BiOS: January 31, 2017; Published: 19 April 2017); https://doi.org/10.1117/12.2255518.5371358608001.
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