Neurophotonics was launched in 2014 coinciding with the launch of the BRAIN Initiative focused on development of technologies for advancement of neuroscience. For the last seven years, Neurophotonics’ agenda has been well aligned with this focus on neurotechnologies featuring new optical methods and tools applicable to brain studies. While the BRAIN Initiative 2.0 is pivoting towards applications of these novel tools in the quest to understand the brain, in this article we review an extensive and diverse toolkit of novel methods to explore brain function that have emerged from the BRAIN Initiative and related large-scale efforts for measurement and manipulation of brain structure and function. Here, we focus on neurophotonic tools mostly applicable to animal studies. A companion article, scheduled to appear later this year, will cover diffuse optical imaging methods applicable to noninvasive human studies. For each domain, we outline the current state-of-the-art of the respective technologies, identify the areas where innovation is needed and provide an outlook for the future directions.
Optical coherence tomography provides volumetric reconstruction of brain structure with micrometer resolution. Gray matter and white matter can be highlighted using conventional and polarization-based contrasts; however, vasculature in ex-vivo fixed brain has not been investigated at large scale due to lack of intrinsic contrast. We present contrast enhancement to visualize the vasculature by perfusing titanium dioxide particles transcardially into the mouse vascular system. The brain, after dissection and fixation, is imaged by a serial optical coherence scanner. Accumulation of particles in blood vessels generates distinguishable optical signals. Among these, the cross-polarization images reveal the vasculature organization remarkably well. The conventional and polarization-based contrasts are still available for probing the gray matter and white matter structures. The segmentation and reconstruction of the vasculature are presented by using a deep learning algorithm. Axonal fiber pathways in the mouse brain are delineated by utilizing the retardance and optic axis orientation contrasts. This is a low-cost method that can be further developed to study neurovascular diseases and brain injury in animal models.
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