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

Restoration of functional connectivity is a major contributor to functional recovery after stroke. We investigated the role of reactive astrocytes in functional connectivity and recovery after photothrombotic stroke in mice with attenuated reactive gliosis (GFAP(-/-)Vim(-/-)). Infarct volume and longitudinal functional connectivity changes were determined by in vivo T2-weighted magnetic resonance imaging (MRI) and resting-state functional MRI. Sensorimotor function was assessed with behavioral tests, and glial and neural plasticity responses were quantified in the peri-infarct region. Four weeks after stroke, GFAP(-/-)Vim(-/-) mice showed impaired recovery of sensorimotor function and aberrant restoration of global neuronal connectivity. These mice also exhibited maladaptive plasticity responses, shown by higher number of lost and newly formed functional connections between primary and secondary targets of cortical stroke regions and increased peri-infarct expression of the axonal plasticity marker Gap43. We conclude that reactive astrocytes modulate recovery-promoting plasticity responses after ischemic stroke.

Although spasticity is one of the most common causes of motor disability worldwide, its precise definition and pathophysiology remain elusive, which to date renders its experimental targeting tricky. At least in part, this difficulty is caused by heterogeneous phenotypes of spasticity-causing neurological disorders, all causing spasticity by involving upper motor neurons. The most common clinical symptoms are a series of rapid muscle contractions (clonus), an increased muscle tone (hypertonia), and augmented tendon reflex activity (hyperreflexia). This muscle overactivity is due to disturbed inhibition of spinal reflexes following upper motor neuron dysfunction. Despite a range of physical and pharmacological therapies ameliorating the symptoms, their targeted application remains difficult. Therefore, to date, spasticity impacts rehabilitative therapy, and no therapy exists that reverses the pathology completely. In contrast to the incidence and importance of spasticity, only very little pre-clinical work in animal models exists, and this research is focused on the cat or the rat spastic tail model to decipher altered reflexes and excitability of the motor neurons in the spinal cord. Meanwhile, the characterization of spasticity in clinically more relevant mouse models of neurological disorders, such as stroke, remains understudied. Here, we provide a brief introduction into the clinical knowledge and therapy of spasticity and an in-depth review of pre-clinical studies of spasticity in mice including the current experimental challenges for clinical translation.

Magnetic resonance imaging (MRI) is a key technology in multimodal animal studies of brain connectivity and disease pathology. In vivo MRI provides non-invasive, whole brain macroscopic images containing structural and functional information, thereby complementing invasive in vivo high-resolution microscopy and ex vivo molecular techniques. Brain mapping, the correlation of corresponding regions between multiple brains in a standard brain atlas system, is widely used in human MRI. For small animal MRI, however, there is no scientific consensus on pre-processing strategies and atlas-based neuroinformatics. Thus, it remains difficult to compare and validate results from different pre-clinical studies which were processed using custom-made code or individual adjustments of clinical MRI software and without a standard brain reference atlas. Here, we describe AIDAmri, a novel Atlas-based Imaging Data Analysis pipeline to process structural and functional mouse brain data including anatomical MRI, fiber tracking using diffusion tensor imaging (DTI) and functional connectivity analysis using resting-state functional MRI (rs-fMRI). The AIDAmri pipeline includes automated pre-processing steps, such as raw data conversion, skull-stripping and bias-field correction as well as image registration with the Allen Mouse Brain Reference Atlas (ARA). Following a modular structure developed in Python scripting language, the pipeline integrates established and newly developed algorithms. Each processing step was optimized for efficient data processing requiring minimal user-input and user programming skills. The raw data is analyzed and results transferred to the ARA coordinate system in order to allow an efficient and highly-accurate region-based analysis. AIDAmri is intended to fill the gap of a missing open-access and cross-platform toolbox for the most relevant mouse brain MRI sequences thereby facilitating data processing in large cohorts and multi-center studies.

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.

Pre-clinical research builds on a large variety of in vivo and ex vivo tools such as non-invasive imaging, microscopy, and analysis of gene expression. To work efficiently with multimodal data and correlate results across scales, it is of particular importance to have easy access to all data points from different specimen, e.g. the magnetic resonance imaging (MRI) data from different time points, and the post-mortem histology. That requires an efficient data management, which is customizable and designed to relate all applied methods, raw data and analyses to one specific animal. Despite increasing demands to handle such complex data, most pre-clinical labs have not yet established such an electronic database. Here, we present a novel cloud-based relational database for multimodal animal data, which operates on commercial software. We have implemented data fields for various pre-clinical features such as MRI, histology and behaviour. Automated procedures replace manual and recurrent calculations. Pre-set plotting and printing features provide efficient analysis and documentation. The database template is useful for all labs working with laboratory animals and the adaption to specific research projects requires no prior scripting expertise. The database works operating-system independent through the web browser and allows multiple users to work simultaneously. The data entry is monitored and restricted for particular tests according to the user management in order to keep for example users during the experiment blinded for the experimental group. The database improves data accessibility, standardization of data recording and data handling efficiency in pre-clinical research.

Brain lesions caused by cerebral ischemia or hemorrhage lead to a local breakdown of energy homeostasis followed by irreversible cell death and long-term impairment. Importantly, local brain lesions also generate remote functional and structural disturbances, which contribute to the behavioral deficit but also impact the recovery of function. While spontaneous recovery has been associated with endogenous repair mechanisms at the vascular, neural, and immune cell levels, the impact of structural plasticity on sensory-motor dysfunction and recovery thereof remains to be elucidated by longitudinal imaging in a mouse model. Here, we applied behavioral assessments, in vivo fiber tracking, and histological validation in a photothrombotic stroke mouse model. Atlas-based whole-brain structural connectivity analysis and ex vivo histology revealed secondary neurodegeneration in the ipsilesional brain areas, mostly in the dorsal sensorimotor area of the thalamus. Furthermore, we describe for the first time a lesion size-dependent increase in structural connectivity between the contralesional primary motor cortex and thalamus with the ipsilesional cortex. The involvement of the contralesional hemisphere was associated with improved functional recovery relative to lesion size. This study highlights the importance of in vivo fiber tracking and the role of the contralesional hemisphere during spontaneous functional improvement as a potential novel stroke biomarker and therapeutic targets.

Brain lesions caused by cerebral ischemia or hemorrhage lead to a local breakdown of energy homeostasis followed by irreversible cell death and long-term impairment. Importantly, local brain lesions also generate remote functional and structural disturbances, which contribute to the behavioral deficit but also impact the recovery of function. While spontaneous recovery has been associated with endogenous repair mechanisms at the vascular, neural, and immune cell levels, the impact of structural plasticity on sensory-motor dysfunction and recovery thereof remains to be elucidated by longitudinal imaging in a mouse model. Here, we applied behavioral assessments, in vivo fiber tracking, and histological validation in a photothrombotic stroke mouse model. Atlas-based whole-brain structural connectivity analysis and ex vivo histology revealed secondary neurodegeneration in the ipsilesional brain areas, mostly in the dorsal sensorimotor area of the thalamus. Furthermore, we describe for the first time a lesion size-dependent increase in structural connectivity between the contralesional primary motor cortex and thalamus with the ipsilesional cortex. The involvement of the contralesional hemisphere was associated with improved functional recovery relative to lesion size. This study highlights the importance of in vivo fiber tracking and the role of the contralesional hemisphere during spontaneous functional improvement as a potential novel stroke biomarker and therapeutic targets.