Constitutive cell proliferation and neurogenesis in the organum vasculosum lamina terminalis and subfornical organ of adult rats.

Neurogenesis continues throughout adulthood in the subventricular zone, hippocampal subgranular zone, and the hypothalamic median eminence (ME) and the adjacent medio-basal hypothalamus. The ME is one of the circumventricular organs (CVO), which are specialized brain areas characterized by an incomplete blood-brain barrier and, thus, are involved in mediating communication between the central nervous system and the periphery. Additional CVOs include the organum vasculosum laminae terminalis (OVLT) and the subfornical organs (SFO). Previous studies have demonstrated that the ME contains neural stem cells (NSCs) capable of generating new neurons and glia in the adult brain. However, it remains unclear whether the OVLT and SFO also contain proliferating cells, the identity of these cells, and their ability to differentiate into mature neurons. Here we show that glial and mural subtypes exhibit NSC characteristics, expressing the endogenous mitotic maker Ki67, and incorporating the exogenous mitotic marker BrdU in the OVLT and SFO of adult rats. Glial cells constitutively proliferating in the SFO comprise NG2 glia, while in the OVLT, both NG2 glia and tanycytes appear to constitute the NSC pool. Furthermore, pericytes, which are mural cells associated with capillaries, also contribute to the pool of cells constitutively proliferating in the OVLT and SFO of adult rats. In addition to these glial and mural cells, a fraction of NSCs containing proliferation markers Ki67 and BrdU also expresses the early postmitotic neuronal marker doublecortin, suggesting that these CVOs comprise newborn neurons. Notably, these neurons can differentiate and express the mature neuronal marker NeuN. These findings establish the sensory CVOs OVLT and SFO as additional neurogenic niches, where the generation of new neurons and glia persists in the adult brain.

Superresolution Imaging of Cytoskeletal Networks in Fixed Brain Tissue.

Emerging evidence suggests that neurodegeneration is directly linked to dysfunction of cytoskeleton; however, visualizing the organization of cytoskeletal structures in brain tissues remains challenging due to the limitation of resolution of light microscopy. Superresolution imaging overcomes this limitation and resolves subcellular structures below the diffraction barrier of light (20-200 nm), while retaining the advantages of fluorescent microscopy such as simultaneous visualization of multiple proteins and increased signal sensitivity and contrast. However, superresolution imaging approaches have been largely limited to very thin samples such as cultured cells growing as a single monolayer. Analysis of thicker tissue sections represents a technical challenge due to high background fluorescence and quality of the tissue preservation methods. Among superresolution microscopy approaches, structured illumination microscopy is one of the most compatible methods for analyzing thicker native tissue samples. We have developed a methodology that allows maximal preservation and quantitative analyses of cytoskeletal networks in tissue sections from a rodent brain. This methodology includes a specialized fixation protocol, tissue preparation, and image acquisition procedures optimized for the characterization of subcellular cytoskeletal structures using superresolution with structured illumination microscopy.

Anatomical Organization of the Rat Subfornical Organ.

The subfornical organ (SFO) is a sensory circumventricular organ located along the anterodorsal wall of the third ventricle. SFO lacks a complete blood-brain barrier (BBB), and thus peripherally-circulating factors can penetrate the SFO parenchyma. These signals are detected by local neurons providing the brain with information from the periphery to mediate central responses to humoral signals and physiological stressors. Circumventricular organs are characterized by the presence of unique populations of non-neuronal cells, such as tanycytes and fenestrated endothelium. However, how these populations are organized within the SFO is not well understood. In this study, we used histological techniques to analyze the anatomical organization of the rat SFO and examined the distribution of neurons, fenestrated and non-fenestrated vasculature, tanycytes, ependymocytes, glia cells, and pericytes within its confines. Our data show that the shell of SFO contains non-fenestrated vasculature, while fenestrated capillaries are restricted to the medial-posterior core region of the SFO and associated with a higher BBB permeability. In contrast to non-fenestrated vessels, fenestrated capillaries are encased in a scaffold created by pericytes and embedded in a network of tanycytic processes. Analysis of c-Fos expression following systemic injections of angiotensin II or hypertonic NaCl reveals distinct neuronal populations responding to these stimuli. Hypertonic NaCl activates ∼13% of SFO neurons located in the shell. Angiotensin II-sensitive neurons represent ∼35% of SFO neurons and their location varies between sexes. Our study provides a comprehensive description of the organization of diverse cellular elements within the SFO, facilitating future investigations in this important brain area.

A deconvolution-based approach to identifying large-scale effective connectivity.

Rapid, robust computation of effective connectivity between neural regions is an important next step in characterizing the brain's organization, particularly in the resting state. However, recent work has called into question the value of causal inference computed directly from BOLD, demonstrating that valid inferences require transformation of the BOLD signal into its underlying neural events as necessary for accurate causal inference. In this work we develop an approach for effective connectivity estimation directly from deconvolution-based features and estimates of inter-regional communication lag. We then test, in both simulation as well as whole-brain fMRI BOLD signal, the viability of this approach. Our results show that deconvolution precision and network size play outsized roles in effective connectivity estimation performance. Idealized simulation conditions allow for statistically significant effective connectivity estimation of networks of up to four hundred regions-of-interest (ROIs). Under simulation of realistic recording conditions and deconvolution performance, however, our result indicates that effective connectivity is viable in networks containing up to approximately sixty ROIs. We then validated the ability for the proposed method to reliably detect effective connectivity in whole-brain fMRI signal parcellated into networks of viable size.