Distribution and orientation of nerve fibers and myelin assembly in a brain section retrieved by small-angle neutron scattering

The structural connectivity of the brain has been addressed by various imaging techniques such as diffusion weighted magnetic resonance imaging (DWMRI) or specific microscopic approaches based on histological staining or label-free using polarized light (e.g., three-dimensional Polarized Light Imaging (3D-PLI), Optical Coherence Tomography (OCT)). These methods are sensitive to different properties of the fiber enwrapping myelin sheaths i.e. the distribution of myelin basic protein (histology), the apparent diffusion coefficient of water molecules restricted in their movements by the myelin sheath (DWMRI), and the birefringence of the oriented myelin lipid bilayers (3D-PLI, OCT). We show that the orientation and distribution of nerve fibers as well as myelin in thin brain sections can be determined using scanning small angle neutron scattering (sSANS). Neutrons are scattered from the fiber assembly causing anisotropic diffuse small-angle scattering and Bragg peaks related to the highly ordered periodic myelin multilayer structure. The scattering anisotropy, intensity, and angular position of the Bragg peaks can be mapped across the entire brain section. This enables mapping of the fiber and myelin distribution and their orientation in a thin brain section, which was validated by 3D-PLI. The experiments became possible by optimizing the neutron beam collimation to highest flux and enhancing the myelin contrast by deuteration. This method is very sensitive to small microstructures of biological tissue and can directly extract information on the average fiber orientation and even myelin membrane thickness. The present results pave the way toward bio-imaging for detecting structural aberrations causing neurological diseases in future.

Chapter 54: Biology, Genetics and Evolution

In this Chapter we first look at the core view of the biology of language associated with Minimalism, including the Biolinguistics Program (section 2). Next, we consider research on the brain (section 3) and genetics (section 4), associated with this framework. Finally, we introduce some subsequent views of language evolution which break away from the saltationist, discontinuous nature of the mainstream approach (section 5), and draw some conclusions regarding future prospects (section 6).

Light microscopy based approach for mapping connectivity with molecular specificity

Mapping neuroanatomy is a foundational goal towards understanding brain function. Electron microscopy (EM) has been the gold standard for connectivity analysis because nanoscale resolution is necessary to unambiguously resolve synapses. However, molecular information that specifies cell types is often lost in EM reconstructions. To address this, we devise a light microscopy approach for connectivity analysis of defined cell types called spectral connectomics. We combine multicolor labeling (Brainbow) of neurons with multi-round immunostaining Expansion Microscopy (miriEx) to simultaneously interrogate morphology, molecular markers, and connectivity in the same brain section. We apply this strategy to directly link inhibitory neuron cell types with their morphologies. Furthermore, we show that correlative Brainbow and endogenous synaptic machinery immunostaining can define putative synaptic connections between neurons, as well as map putative inhibitory and excitatory inputs. We envision that spectral connectomics can be applied routinely in neurobiology labs to gain insights into normal and pathophysiological neuroanatomy.

Light microscopy based approach for mapping connectivity with molecular specificity

Mapping neuroanatomy is a foundational goal towards understanding brain function. Electron microscopy (EM) has been the gold standard for connectivity analysis because nanoscale resolution is necessary to unambiguously resolve chemical and electrical synapses. However, molecular information that specifies cell types is often lost in EM reconstructions. To address this, we devised a light microscopy approach for connectivity analysis of defined cell types called spectral connectomics. We combined multicolor genetic labeling (Brainbow) of neurons with a multi-round immunostaining Expansion Microscopy (miriEx) strategy to simultaneously interrogate morphology, molecular markers, and connectivity in the same brain section. We applied our multimodal profiling strategy to directly link inhibitory neuron cell types with their network morphologies. Furthermore, we showed that correlative Brainbow and endogenous synaptic machinery immunostaining can be used to define putative synaptic connections between spectrally unique neurons, as well as map putative inhibitory and excitatory inputs. We envision that spectral connectomics can be applied routinely in neurobiology labs to gain insights into normal and pathophysiological neuroanatomy across multiple animals and time points.

Automatic navigation system for the mouse brain

Identification and delineation of brain regions in histologic mouse brain sections is especially pivotal for many neurogenomics, transcriptomics, proteomics and connectomics studies, yet this process is prone to observer error and bias. Here we present a novel brain navigation system, named NeuroInfo, whose general principle is similar to that of a global positioning system (GPS) in a car. NeuroInfo automatically navigates an investigator through the complex microscopic anatomy of histologic sections of mouse brains (thereafter: “experimental mouse brain sections”). This is achieved by automatically registering a digital image of an experimental mouse brain section with a three-dimensional (3D) digital mouse brain atlas that is essentially based on the third version of the Allen Mouse Brain Common Coordinate Framework (CCF v3), retrieving graphical region delineations and annotations from the 3D digital mouse brain atlas, and superimposing this information onto the digital image of the experimental mouse brain section on a computer screen. By doing so, NeuroInfo helps in solving the long-standing problem faced by researchers investigating experimental mouse brain sections under a light microscope—that of correctly identifying the distinct brain regions contained within the experimental mouse brain sections. Specifically, NeuroInfo provides an intuitive, readily-available computer microscopy tool to enhance researchers’ ability to correctly identify specific brain regions in experimental mouse brain sections. Extensive validation studies of NeuroInfo demonstrated that this novel technology performs remarkably well in accurately delineating regions that are large and/or located in the dorsal parts of mouse brains, independent on whether the sections were imaged with fluorescence or brightfield microscopy. This novel navigation system provides a highly efficient way for registering a digital image of an experimental mouse brain section with the 3D digital mouse brain atlas in a minute and accurate delineation of the image in real-time.

Nucleus Ruber of Actinopterygians

Nucleus ruber is known as an important supraspinal center that controls forelimb movements in tetrapods, and the rubral homologue may serve similar functions in fishes (motor control of pectoral fin). However, two apparently different structures have been identified as ‘nucleus ruber' in actinopterygians. One is nucleus ruber of Goldstein (1905) (NRg), and the other nucleus ruber of Nieuwenhuys and Pouwels (1983) (NRnp). It remains unclear whether one of these nuclei (or perhaps both) is homologous to tetrapod nucleus ruber. To resolve this issue from a phylogenetic point of view, we have investigated the distribution of tegmental neurons retrogradely labeled from the spinal cord in eight actinopterygian species. We also investigated the presence/absence of the two nuclei with Nissl- or Bodian-stained brain section series of an additional 28 actinopterygian species by comparing the morphological features of candidate rubral neurons with those of neurons revealed by the tracer studies. Based on these analyses, the NRg was identified in all actinopterygians investigated in the present study, while the NRnp appears to be absent in basal actinopterygians. The phylogenetic distribution pattern indicates that the NRg is the more likely homologue of nucleus ruber, and the NRnp may be a derived nucleus that emerged during the course of actinopterygian evolution.