Biology subjects

Reisert, M.

Publications and source records attributed to Reisert, M..

4 recordsLinked to original sources

bioRxiv2022

The Brain/MINDS Marmoset Connectivity Atlas: Exploring bidirectional tracing and tractography in the same stereotaxic space

We report on the implementation and features of the Brain/MINDS Marmoset Connectivity Atlas, BMCA, a new resource that provides access to anterograde neuronal tracer data in the prefrontal cortex of a marmoset brain. Neuronal tracers combined with fluorescence microscopy are a key technology for the systematic mapping of structural brain connectivity. We selected the prefrontal cortex for mapping due to its important role in higher brain functions. This work introduces the BMCA standard image preprocessing pipeline and tools for exploring and reviewing the data. We developed the BMCA-Explorer, which is an online image viewer designed for data exploration. Unlike other existing image explorers, it visualizes the data of different individuals in a common reference space at an unprecedented high resolution, facilitating comparative studies. To foster the integration with other marmoset brain image databases and cross-species comparisons, we added fiber tractography data from diffusion MRI, retrograde neural tracer data from the Marmoset Brain Connectivity Atlas project, and tools to map image data between marmoset and the human brain image space. This version of BMCA allows direct comparison between the results of 52 anterograde and 164 retrograde tracer injections in the cortex of the marmoset.

neuroscience↗

bioRxiv2020

DTI reveals whole-brain microstructural changes in the P301L mouse model of tauopathy

IntroductionIncreased expression of hyperphosphorylated tau and the formation of neurofibrillary tangles are associated with neuronal loss and white matter damage. Using high resolution ex vivo diffusion tensor imaging (DTI), we investigated microstructural changes in the white and grey matter in the P301L mouse model of human tauopathy at 8.5 months-of-age. For unbiased computational analysis, we implemented a pipeline for voxel-based analysis (VBA) and atlas-based analysis (ABA) of DTI mouse brain data. MethodsHemizygous and homozygous transgenic P301L mice and non-transgenic littermates were used. DTI data were acquired for generation of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD) maps. VBA on the entire brain were performed using SPM8 and SPM Mouse toolbox. Initially, all DTI maps were co-registered with Allen mouse brain atlas to bring them to one common coordinate space. In VBA, co-registered DTI maps were normalized and smoothed in order to perform two-sample t-tests to compare hemizygotes with non-transgenic littermates, homozygotes with non-transgenic littermates, hemizygotes with homozygotes on each DTI parameter map. In ABA, the average values for selected regions-of-interests were computed with co-registered DTI maps and labels in Allen mouse brain atlas. After, the same two-sample t-tests were executed on the estimated average values. ResultsWe made reconstructed DTI data and VBA and ABA pipeline publicly available. With VBA, we found microstructural changes in the white matter in hemizygous P301L mice compared to non-transgenic littermates. In contrast, more pronounced and brain-wide spread changes were observed in VBA when comparing homozygous P301L mice with non-transgenic littermates. Statistical comparison of DTI metrics in selected brain regions by ABA corroborated findings from VBA. FA was found to be decreased in most brain regions, while MD, RD and AD were increased compared to hemizygotes and non-transgenic littermates. Discussion/ConclusionHigh resolution ex vivo DTI demonstrated brain-wide microstructural changes in the P301L mouse model of human tauopathy. The comparison between hemizygous and homozygous P301L mice revealed a gene-dose dependent effect on DTI metrics. The publicly available computational data analysis pipeline can provide a platform for future mechanistic and longitudinal studies.

neuroscience↗

bioRxiv2019

Mapping the living mouse brain neural architecture: strain specific patterns of brain structural and functional connectivity

Mapping the structural and functional brain connectivity fingerprints became an essential approach in neurology and experimental neuroscience because network properties can underlie behavioral phenotypes. In mouse models, revealing strain related patterns of brain wiring have a tremendous importance, since these animals are used to answer questions related to neurological or neuropsychiatric disorders. C57BL/6 and BALB/cJ inbred strains are primary \"genetic backgrounds\" for brain disease modelling and for testing therapeutic approaches. Nevertheless, extensive literature describes basal differences in the behavioral, neuroanatomical and neurochemical profiles of the two strains, which raises the question whether the observed effects are pathology specific or depend on the genetic background. Here we performed a systematic comparative exploration of brain structure and function of C57BL/6 and BALB/cJ mice via Magnetic Resonance Imaging (MRI). We combined voxel-based morphometry (VBM), diffusion MRI and high resolution fiber mapping (hrFM) and resting state functional MRI (rs-fMRI) and depicted brain-wide dissimilarities in the morphology and \"connectome\" features in the two strains. Particularly C57BL/6 animals show bigger and denser frontal cortical areas, cortico-striatal tracts and thalamic and midbrain pathways, and higher density of fibers in the genu and splenium of the corpus callosum. These features are fairly reflected in the functional connectograms that emphasize differences in \"hubness\", frontal cortical and basal forbrain connectivity. We demonstrate strongly divergent reward-aversion circuitry patterns and some variations of the default mode network features. Inter-hemispherical functional connectivity showed flexibility and adjustment regarding the structural patterns in a strain specific manner. We further provide high-resolution tractograms illustrating also inter-individual variability across inter-hemispherical callosal pathways in the BALB/cJ strain.

neuroscience↗

bioRxiv2018

Lead-DBS v2: Toward a comprehensive pipeline for deep brain stimulation imaging

Deep brain stimulation (DBS) is a highly efficacious treatment option for movement disorders and a growing number of other indications are investigated in clinical trials. To ensure optimal treatment outcome, exact electrode placement is required. Moreover, to analyze the relationship between electrode location and clinical results, a precise reconstruction of electrode placement is required, posing specific challenges to the field of neuroimaging. Since 2014 the open source toolbox Lead-DBS is available, which aims at facilitating this process. The tool has since become a popular platform for DBS imaging. With support of a broad community of researchers worldwide, methods have been continuously updated and complemented by new tools for tasks such as multispectral nonlinear registration, structural / functional connectivity analyses, brain shift correction, reconstruction of microelectrode recordings and orientation detection of segmented DBS leads. The rapid development and emergence of these methods in DBS data analysis require us to revisit and revise the pipelines introduced in the original methods publication. Here we demonstrate the updated DBS and connectome pipelines of Lead-DBS using a single patient example with state-of-the-art high-field imaging as well as a retrospective cohort of patients scanned in a typical clinical setting at 1.5T. Imaging data of the 3T example patient is co-registered using five algorithms and nonlinearly warped into template space using ten approaches for comparative purposes. After reconstruction of DBS electrodes (which is possible using three methods and a specific refinement tool), the volume of tissue activated is calculated for two DBS settings using four distinct models and various parameters. Finally, four whole-brain tractography algorithms are applied to the patients preoperative diffusion MRI data and structural as well as functional connectivity between the stimulation volume and other brain areas are estimated using a total of eight approaches and datasets. In addition, we demonstrate impact of selected preprocessing strategies on the retrospective sample of 51 PD patients. We compare the amount of variance in clinical improvement that can be explained by the computer model depending on the method of choice.\n\nThis work represents a multi-institutional collaborative effort to develop a comprehensive, open source pipeline for DBS imaging and connectomics, which has already empowered several studies, and may facilitate a variety of future studies in the field.

neuroscience↗