690 research outputs found

    Neurovascular Imaging

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    A deep learning approach to 3D segmentation of brain vasculature

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    The segmentation of blood-vessels is an important preprocessing step for the quantitative analysis of brain vasculature. We approach the segmentation task for two-photon brain angiograms using a fully convolutional 3D deep neural network.Published versio

    Cerebral tissue pO2 response to stimulation is preserved with age in awake mice

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    Published in final edited form as: Neurosci Lett. 2019 April 23; 699: 160–166. doi:10.1016/j.neulet.2019.02.007.Compromised oxygen supply to cerebral tissue could be an important mechanism contributing to age-related cognition decline. We recently showed in awake mice that resting cerebral tissue pO2 decreases with age, a phenomenon that manifests mainly after middle-age. To extend these findings, here we aimed to study how tissue pO2 response to neuronal stimulation is affected by aging. We used two-photon phosphorescence lifetime microscopy to directly measure the brain tissue pO2 response to whisker stimulation in healthy awake young, middle-aged and old mice. We show that despite a decrease in baseline tissue pO2, the amplitude of the tissue pO2 response to stimulation is well preserved with age. However, the response dynamics are altered towards a slower response with reduced post-stimulus undershoot in older ages, possibly due to stiffer vessel wall among other factors. An estimation of the net oxygen consumption rate using a modified Krogh model suggests that the O2 overshoot during stimulation may be necessary to secure a higher capillary O2 delivery to the tissue proportional to increased CMRO2 to maintain the capillary tissue pO2. It was observed that the coupling between the CMRO2 and capillary O2 delivery is preserved with age.Accepted manuscrip

    Contribution of speckle noise in near-infrared spectroscopy measurements

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    Near-infrared spectroscopy (NIRS) is widely used in biomedical optics with applications ranging from basic science, such as in functional neuroimaging, to clinical, as in pulse oximetry. Despite the relatively low absorption of tissue in the near-infrared, there is still a significant amount of optical attenuation produced by the highly scattering nature of tissue. Because of this, designers of NIRS systems have to balance source optical power and source–detector separation to maximize the signal-to-noise ratio (SNR). However, theoretical estimations of SNR neglect the effects of speckle. Speckle manifests as fluctuations of the optical power received at the detector. These fluctuations are caused by interference of the multiple random paths taken by photons in tissue. We present a model for the NIRS SNR that includes the effects of speckle. We performed experimental validations with a NIRS system to show that it agrees with our model. Additionally, we performed computer simulations based on the model to estimate the contribution of speckle noise for different collection areas and source–detector separations. We show that at short source–detector separation, speckle contributes most of the noise when using long coherence length sources. Considering this additional noise is especially important for hybrid applications that use NIRS and speckle contrast simultaneously, such as in diffuse correlation spectroscopy.R01 EB025145 - NIBIB NIH HHS; R24 NS104096 - NINDS NIH HHSPublished versio

    Colocalization of neurons in optical coherence microscopy and Nissl-stained histology in Brodmann’s area 32 and area 21

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    Published in final edited form as: Brain Struct Funct. 2019 January ; 224(1): 351–362. doi:10.1007/s00429-018-1777-z.Optical coherence tomography is an optical technique that uses backscattered light to highlight intrinsic structure, and when applied to brain tissue, it can resolve cortical layers and fiber bundles. Optical coherence microscopy (OCM) is higher resolution (i.e., 1.25 µm) and is capable of detecting neurons. In a previous report, we compared the correspondence of OCM acquired imaging of neurons with traditional Nissl stained histology in entorhinal cortex layer II. In the current method-oriented study, we aimed to determine the colocalization success rate between OCM and Nissl in other brain cortical areas with different laminar arrangements and cell packing density. We focused on two additional cortical areas: medial prefrontal, pre-genual Brodmann area (BA) 32 and lateral temporal BA 21. We present the data as colocalization matrices and as quantitative percentages. The overall average colocalization in OCM compared to Nissl was 67% for BA 32 (47% for Nissl colocalization) and 60% for BA 21 (52% for Nissl colocalization), but with a large variability across cases and layers. One source of variability and confounds could be ascribed to an obscuring effect from large and dense intracortical fiber bundles. Other technical challenges, including obstacles inherent to human brain tissue, are discussed. Despite limitations, OCM is a promising semi-high throughput tool for demonstrating detail at the neuronal level, and, with further development, has distinct potential for the automatic acquisition of large databases as are required for the human brain.Accepted manuscrip
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