We introduce the GRIN-axicon, a new low-cost optical component that is easy to manufacture and could replace the axicon in various setups such as a two-photon microscope. In neuroscience, the imaging of in vivo samples requires high temporal resolution in order to capture the interactions between neurons located at different depths in the tissue. To achieve this, the use of an axicon lens increases the depth of field of the microscope and reduces the number of scans to be performed. However, the axicon is difficult to manufacture and generally has defects on the tip of the cone, thus degrading the quality of the resultant Bessel-Gauss beam.
Brain functional connectivity based on the measure of blood oxygen level-dependent (BOLD) functional magnetic resonance imaging (fMRI) signals has become one of the most widely used measurements in human neuroimaging. However, the nature of the functional networks revealed by BOLD fMRI can be ambiguous, as highlighted by a recent series of experiments that have suggested that typical resting-state networks can be replicated from purely vascular or physiologically driven BOLD signals. After going through a brief review of the key concepts of brain network analysis, we explore how the vascular and neuronal systems interact to give rise to the brain functional networks measured with BOLD fMRI. This leads us to emphasize a view of the vascular network not only as a confounding element in fMRI but also as a functionally relevant system that is entangled with the neuronal network. To study the vascular and neuronal underpinnings of BOLD functional connectivity, we consider a combination of methodological avenues based on multiscale and multimodal optical imaging in mice, used in combination with computational models that allow the integration of vascular information to explain functional connectivity.
KEYWORDS: Functional magnetic resonance imaging, Contamination, Blood, Two photon excitation microscopy, Angiography, Monte Carlo methods, Magnetism, Tissues, Brain, Capillaries
The vascular space occupancy (VASO) fMRI method probes changes in cerebral blood volume (CBV) under various physiological states, including neuronal activation in humans. However, it requires a careful choice of sequence parameters because the blood oxygen-level dependent (BOLD) effect offsets the VASO signal. Assessing this BOLD contamination as a function of pulse sequence parameters would improve the quantification of CBV changes with VASO. However, this task requires knowledge of the cerebral vascular geometry of the MRI voxel. Towards this end, optical microscopy can provide high-resolution 3D images of vasculature. Here, we use detailed angiograms of rodent brain acquired with two-photon microscopy to model fMRI signals (VASO and BOLD) from first principles using Monte Carlo diffusion of water protons. We present quantitative plots of VASO together with intra- and extravascular BOLD fractional signal changes as a function of echo time (TE), for spin echo (SE) and gradient echo (GRE) pulse sequences, at low to ultra-high magnetic fields. Our results indicate that at 3T, the BOLD contamination of the VASO response is under 12% for GRE and 2% for SE up to TE=6 ms, but this contamination is significantly higher at 7T and above. We also found GRE BOLD intravascular contributions of 85% at 1.5T, 55% at 3T and 4% at 7T and SE intravascular contributions of 70% at 1.5T, 40% at 3T and 10% at 7T. These results may provide important information to optimize the pulse sequence timing in human VASO and BOLD fMRI, leading the way to a wider application of these fMRI techniques in healthy and diseased brain.
We characterized cortical microvascular PO2 and blood flow changes in response to whisker stimulation in awake mice. The measurements were performed by combining two-photon microscopy imaging of the cortical oxygenation and optical coherence tomography imaging of the cerebral blood flow. In order to perform fast spatio-temporally resolved measurements of PO2, we used a newly-developed oxygen-sensitive probe PtG-2P, which has significantly higher brightness than the established two-photon-enhanced oxygen sensor PtP-C343. We characterized the performance of the new probe in vivo and mapped the amplitudes and shapes (e.g. initial dip, overshoot, and post stimulus undershoot) of the PO2 changes as a function of the vessel type (e.g., arterioles, capillaries, and venules) and a distance from the activation center. The measurements in the awake mice are not affected by the confounding factors of anesthesia on the animal physiology, including the level of cerebral metabolism and the amplitude and speed of neuronal and vascular responses. Our results will help to understand changes in oxygenation and blood flow on the cortical microvascular scale, will lead to improved understanding of the cerebral physiology, pathophysiology and will improve quantitative interpretation of fMRI signals.
Diffuse, optical near infrared imaging is increasingly being used in various neurocognitive contexts where changes in optical signals are interpreted through activation maps. Statistical population comparison of different age or clinical groups rely on the relative homogeneous distribution of measurements across subjects in order to infer changes in brain function. In the context of an increasing use of diffuse optical imaging with older adult populations, changes in tissue properties and anatomy with age adds additional confounds. Few studies investigated these changes with age. Duncan et al. measured the so-called diffusion path length factor (DPF) in a large population but did not explore beyond the age of 51 after which physiological and anatomical changes are expected to occur [Pediatr. Res. 39(5), 889-894 (1996)]. With increasing interest in studying the geriatric population with optical imaging, we studied changes in tissue properties in young and old subjects using both magnetic resonance imaging (MRI)-guided Monte-Carlo simulations and time-domain diffuse optical imaging. Our results, measured in the frontal cortex, show changes in DPF that are smaller than previously measured by Duncan et al. in a younger population. The origin of these changes are studied using simulations and experimental measures.
Biophysical models of hemodynamics provide a tool for quantitative multimodal brain imaging by allowing a deeper
understanding of the interplay between neural activity and blood oxygenation, volume and flow responses to stimuli.
Multicompartment dynamical models that describe the dynamics and interactions of the vascular and metabolic
components of evoked hemodynamic responses have been developed in the literature. In this work, multimodal data
using near-infrared spectroscopy (NIRS) and diffuse correlation flowmetry (DCF) is used to estimate total baseline
hemoglobin concentration (HBT0) in 7 adult subjects. A validation of the model estimate and investigation of the partial
volume effect is done by comparing with time-resolved spectroscopy (TRS) measures of absolute HBT0. Simultaneous
NIRS and DCF measurements during hypercapnia are then performed, but are found to be hardly reproducible. The
results raise questions about the feasibility of an all-optical model-based estimation of individual vascular properties.
In this work, we explore diffuse correlation spectroscopy (DCS) in a two-layered geometry. We compare the
effiency of an homogeneous and a two-layered model to recover flow changes. By simulating a realistic human
head with MRI anatomical data, we show that the two-layered model allows distinction between superficial layers
and brain hemodynamic changes. The results show that the two-layered model provides a better estimate for
the flow change than the homogeneous one. Experimental measurements with a two-layered dynamical phantom
confirm the ability of the two-layered analytical model to distinguish flow increase in each layer.
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