In vivo imaging of inhibitory, GABAergic neurons by MRI

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Structure-function relationship of cerebral networks in experimental neuroscience: Contribution of magnetic resonance imaging

© 2012 Elsevier Inc. All rights reserved

Atlas-based imaging data analysis tool for quantitative mouse brain histology (AIDAhisto)

Cell counting in neuroscience is a routine method of utmost importance to support descriptive in vivo findings with quantitative data on the cellular level. Although known to be error- and bias-prone, manual cell counting of histological stained brain slices remains the gold standard in the field. While the manual approach is limited to small regions-of-interest in the brain, automated tools are needed to up-scale translational approaches and generate whole mouse brain counts in an atlas framework. Our goal was to develop an algorithm which requires no pre-training such as machine learning algorithms, only minimal user input, and adjustable variables to obtain reliable cell counting results for stitched mouse brain slices registered to a common atlas such as the Allen Mouse Brain atlas. We adapted filter banks to extract the maxima from round-shaped cell nuclei and various cell structures. In a qualitative as well as quantitative comparison to other tools and two expert raters, AIDAhisto provides accurate and fast results for cell nuclei as well as immunohistochemical stainings of various types of cells in the mouse brain

Atlas-based imaging data analysis tool for quantitative mouse brain histology (AIDAhisto)

Cell counting in neuroscience is a routine method of utmost importance to support descriptive in vivo findings with quantitative data on the cellular level. Although known to be error- and bias-prone, manual cell counting of histological stained brain slices remains the gold standard in the field. While the manual approach is limited to small regions-of-interest in the brain, automated tools are needed to up-scale translational approaches and generate whole mouse brain counts in an atlas framework. Our goal was to develop an algorithm which requires no pre-training such as machine learning algorithms, only minimal user input, and adjustable variables to obtain reliable cell counting results for stitched mouse brain slices registered to a common atlas such as the Allen Mouse Brain atlas. We adapted filter banks to extract the maxima from round-shaped cell nuclei and various cell structures. In a qualitative as well as quantitative comparison to other tools and two expert raters, AIDAhisto provides accurate and fast results for cell nuclei as well as immunohistochemical stainings of various types of cells in the mouse brain

Graph theoretical quantification of white matter reorganization after cortical stroke in mice

Stroke is a devastating disease leading to cell death and disconnection between neurons both locally and remote, often resulting in severe long-term disability. Spontaneous reorganization of areas and pathways not primarily affected by ischemia is, however, associated with albeit limited recovery of function. Quantitative mapping of whole-brain changes of structural connectivity concerning the ischemia-induced sensorimotor deficit and recovery thereof would help to target structural plasticity in order to improve rehabilitation. Currently, only in vivo diffusion MRI can extract the structural whole-brain connectome noninvasively. This approach is, however, used primarily in human studies. Here, we applied atlas-based MRI analysis and graph theory to DTI in wild-type mice with cortical stroke lesions. Using a DTI network approach and graph theory, we aimed at gaining insights into the dynamics of the spontaneous reorganization after stroke related to the recovery of function. We found evidence for altered structural integrity of connections of specific brain regions, including the breakdown of connections between brain regions directly affected by stroke as well as long-range rerouting of intra- and transhemispheric connections related to improved sensorimotor behavior

Terminal H-reflex Measurements in Mice

The Hoffmann reflex (H-reflex), as an electrical analog to the stretch reflex, allowselectrophysiological validation of the integrity of neural circuits after injuries such asspinal cord damage or stroke. An increase of the H-reflex response, together withsymptoms like non-voluntary muscle contractions, pathologically augmented stretchreflex, and hypertonia in the corresponding muscle, is an indicator of post-strokespasticity (PSS).In contrast to rather nerve-unspecific transcutaneous measurements, here, we presenta protocol to quantify the H-reflex directly at the ulnar and median nerves of theforepaw, which is applicable, with minor modifications, to the tibial and sciatic nerveof the hindpaw. Based on the direct stimulation and the adaptation to different nerves,the method represents a reliable and versatile tool to validate electrophysiologicalchanges in spasticity-related disease models