Conservation of the direct and indirect pathways dichotomy in mouse caudal striatum with uneven distribution of dopamine receptor D1- and D2-expressing neurons

The striatum is one of the key nuclei for adequate control of voluntary behaviors and reinforcement learning. Two striatal projection neuron types, expressing either dopamine receptor D1 (D1R) or dopamine receptor D2 (D2R) constitute two independent output routes: the direct or indirect pathways, respectively. These pathways co-work in balance to achieve coordinated behavior. Two projection neuron types are equivalently intermingled in most striatal space. However, recent studies revealed two atypical zones in the caudal striatum: the zone in which D1R-neurons are the minor population (D1R-poor zone) and that in which D2R-neurons are the minority (D2R-poor zone). It remains obscure as to whether these imbalanced zones have similar properties on axonal projections and electrophysiology to other striatal regions. Based on morphological experiments in mice using immunofluorescence, in situ hybridization, and neural tracing, here, we revealed the poor zones densely projected to the globus pallidus and substantia nigra pars lateralis, with a few collaterals in substantia nigra pars reticulata and compacta. As other striatal regions, D1R-neurons were the direct pathway neurons, while projection neurons in the poor zones possessed similar electrophysiological membrane properties to those in the conventional striatum using in vitro electrophysiological recording. In addition, the poor zones existed irrespective of the age of mice. We also identified the poor zones in the common marmoset as well as other rodents. These results suggest that the poor zones in the caudal striatum follow the conventional projection patterns irrespective of imbalanced distribution of projection neurons. The poor zones could be an innate structure and common in mammals and relate to specific functions via highly restricted projections.

Correlated Sensory and Sympathetic Innervation Between the Acupoint BL23 and Kidney in the Rat

Objective: To investigate the sensory and sympathetic innervations associated with both acupoint “Shenshu” (BL23) and kidney in the rat for insight into the neuronal correlation between the Back-Shu Point and its corresponding visceral organ.Methods: The BL23 and kidney were selected as the representative acupoint and visceral organ in this study, in which their local nerve fibers were examined by using double fluorescent immunohistochemistry with calcitonin gene-related peptide (CGRP) and tyrosine hydroxylase (TH). Meanwhile, their neuronal correlation in the dorsal root ganglia (DRGs), spinal cord, and sympathetic (paravertebral) chain were investigated using a double fluorescent neural tracing technique with Alexa Fluor 488 and 594 conjugates with cholera toxin subunit B (AF488/594-CTB).Results: The local tissue of acupoint BL23 and the fibrous capsule of kidney distributed abundantly with CGRP- and TH-positive nerve fibers, corresponding to their sensory and sympathetic innervation. On the other hand, the sensory neurons associated with acupoint BL23 and kidney were labeled with AF488/594-CTB and distributed from thoracic (T) 11 to lumbar (L) 3 DRGs and from T10 to L2 DRGs, respectively, in which some of them in T12-T13 DRGs were simultaneously labeled with both AF488/594-CTB. Also, postganglionic neurons associated with both acupoint BL23 and kidney were found in the sympathetic chain at the same spinal segments but separately labeled with AF488-CTB and AF594-CTB.Conclusion: Our study demonstrates the neural characteristics of the acupoint BL23 and kidney in the rat from the perspective of neurochemistry and neural pathways, providing an example for understanding the neuronal correlation between the Back-Shu Points and their corresponding visceral organs. These results suggest that the stimulation of the Back-Shu Points may regulate the activities of the target-organs via the periphery sensory and sympathetic pathways.

Unsupervised Neural Tracing in Densely Labeled Multispectral Brainbow Images

Reconstructing neuron morphology is central to uncovering the complexity of the nervous system. That is because the morphology of a neuron essentially provides the physical constraints to its intrinsic electrophysiological properties and its connectivity. Recent advances in imaging technologies generated large quantities of high-resolution 3D images of neurons in the brain. Furthermore, the multispectral labeling technology, Brainbow permits unambiguous differentiation of neighboring neurons in a densely labeled brain, therefore enables for the first time the possibility of studying the connectivity between many neurons from a light microscopy image. However, lack of reliable automated neuron morphology reconstruction makes data analysis the bottleneck of extracting rich informatics in neuroscience. Supervoxel-based neuron segmentation methods have been proposed to solve this problem, however, the use of previous approaches has been impeded by the large numbers of errors which arise in the final segmentation. In this paper, we present a novel unsupervised approach to trace neurons from multispectral Brainbow images, which prevents segmentation errors and tracing continuity errors using two innovations. First, we formulate a Gaussian mixture model-based clustering strategy to improve the separation of segmented color channels that provides accurate skeletonization results for the following steps. Next, a skeleton graph approach is proposed to allow the identification and correction of discontinuities in the neuron tree topology. We find that these innovations allow our approach to outperform current state-of-the-art approaches, which results in more accurate neuron tracing as a tree representation close to human expert annotation.

Distinct relations of microtubules and actin filaments with dendritic architecture

SummaryMicrotubules and F-actin have long been recognized as key regulators of dendritic morphology. Nevertheless, precisely ascertaining their distinct influences on dendritic trees have been hampered until now by the lack of direct, arbor-wide cytoskeletal quantification. We pair live confocal imaging of fluorescently labeled dendritic arborization (da) neurons in Drosophila larvae with complete multi-signal neural tracing to separately measure microtubules and F-actin. We demonstrate that dendritic arbor length is highly interrelated with local microtubule quantity, whereas local F-actin enrichment is associated with dendritic branching. Computational simulation of arbor structure solely constrained by experimentally observed subcellular distributions of these cytoskeletal components generated synthetic morphological and molecular patterns statistically equivalent to those of real da neurons, corroborating the efficacy of local microtubule and F-actin in describing dendritic architecture. The analysis and modeling outcomes hold true for the simplest (Class I), most complex (Class IV), and genetically altered (Formin3 overexpression) da neuron types.SUPPORT: NIH R01 NS39600 and NS086082 and BICCN U01 MH114829.