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Axer, M.

Publications and source records attributed to Axer, M..

10 recordsLinked to original sources

Brain FACTs: A same-section workflow for Fiber Architecture, Cytoarchitecture and cell Types in large-scale brain sections

Understanding the human brain's multiscale organization requires linking cells, connections and architecture, yet conventional methods are incompatible within a single specimen, and inter-individual variability confounds cross-brain comparisons. Multiple-label immunohistochemistry for different cell types has been applied in interleaved sections but remains challenging within a single large human brain section and, has never been combined on the same tissue with 3D polarized light imaging (3D-PLI) for three-dimensional fiber architecture. Here we introduce a sequential multimodal workflow integrating 3D-PLI, multiplex chromogenic immunohistochemistry and Nissl staining on the same large human brain section, preserving each technique's quality and specificity. The method was validated on vervet monkey and Wistar rat sections. The resulting paired high-resolution images eliminate inter-subject variability and enable direct micron-scale mapping of fiber tracts relative to molecularly defined cell types, yielding previously inaccessible insights such as molecular identification of white-matter components, refined cortical layering and cytoarchitectural disambiguation.

neuroscience↗

Precise MRI-Histology Coregistration of Paraffin-Embedded Tissue with Blockface Imaging

Magnetic resonance imaging (MRI) provides 3D spatial information on tissue, yet it lacks at the molecular level. In contrast, histology provides cellular and molecular information, but it lacks the 3D spatial context and direct in vivo translation. Coregistering the two is key for the 3D-embedding of histological details, validating pathological MRI findings, and finding quantitative imaging biomarkers of neurodegenerative diseases. However, coregistration is challenging due to non-linear distortions of the tissue from histological processing and sectioning leading to microscopic and macroscopic nonlinear 3D deformations between specimen MRI and stained histology sections. To address this, we developed a novel pipeline, named Brewsters Blockface Quantification (BBQ), integrating robust optical approaches with innovative 2D and 3D registration algorithms to achieve precise volumetric alignment of specimen MRI data with histological images. On a variety of brain tissue specimens from distinct anatomical regions and across multiple species, our methodology generated blockface volumes with minimal distortion and artifacts. Using these blockface volumes as an intermediary, we achieve a precise alignment between MRI and histology slides, yielding registration results with an overlapping Dice score of [~]90% for whole tissue alignment between MRI and blockface volumes, and >95% for 2D MRI-histology registration. This correlative MRI-histology pipeline with robust 2D and 3D coregistration methods promises to enhance our understanding of neurodegenerative diseases and aid the development of MRI-based disease biomarkers.

bioengineering↗

Uncovering microstructural architecture from histology

Mapping the brains fiber network is crucial for understanding its function and malfunction, but resolving nerve trajectories over large fields of view is challenging. Here, we show that computational scattered light imaging (ComSLI) can map fiber networks in histology independent of sample preparation, also in formalin-fixed paraffin-embedded (FFPE) tissues including whole human brain sections. We showcase this method in new and archived, animal and human brain sections, for different sample preparations (in paraffin, deparaffinized, various stains, unstained fresh-frozen). We convert microscopic orientations to microstructure-informed fiber orientation distributions (FODs). Adapting tractography tools from diffusion magnetic resonance imaging (dMRI), we trace axonal trajectories revealing white and gray matter connectivity. These allow us to identify altered microstructure or deficient tracts in demyelinating or neurodegenerating pathology, and to show key advantages over dMRI, polarization microscopy, and structure tensor analysis. Finally, we map fibers in non-brain tissues, including muscle, bone, and blood vessels, unveiling the tissues function. Our cost-effective, versatile approach enables micron-resolution studies of intricate fiber networks across tissues, species, diseases, and sample preparations, offering new dimensions to neuroscientific and biomedical research.

pathology↗

HippoMaps: Multiscale cartography of the human hippocampal formation

The hippocampus has a unique microarchitecture, is situated at the nexus of multiple macroscale functional networks, contributes to numerous cognitive as well as affective processes, and is highly susceptible to brain pathology across common disorders. These features make the hippocampus a model to understand how brain structure covaries with function, in both health and disease. Here, we introduce HippoMaps, an open access toolbox and online data warehouse for the mapping and contextualization of subregional hippocampal data in the human brain (http://hippomaps.readthedocs.io). HippoMaps capitalizes on a unified hippocampal unfolding approach as well as shape intrinsic registration capabilities to allow for cross-subject and cross-modal data aggregation. We initialize this repository with an unprecedented combination of hippocampal data spanning 3D ex-vivo histology, ex-vivo 9.4 Tesla MRI, as well as in-vivo structural MRI and resting-state functional MRI (rsfMRI) obtained at 3 and 7 Tesla, together with intracranial encephalography (iEEG) recordings in epilepsy patients. HippoMaps also contains validated tools for spatial map association analysis in the hippocampus that correct for autocorrelation. All code and data are compliant with community standards, and comprehensive online tutorials facilitate broad adoption. Applications of this work span methodologies and modalities, spatial scales, as well as clinical and basic research contexts, and we encourage community feedback and contributions in the spirit of open and iterative scientific resource development.

neuroscience↗

Evaluation of surface-based hippocampal registration using ground-truth subfield definitions

The hippocampus is an archicortical structure, consisting of subfields with unique circuits. Understanding its microstructure, as proxied by these subfields, can improve our mechanistic understanding of learning and memory and has clinical potential for several neurological disorders. One prominent issue is how to parcellate, register, or retrieve homologous points between two hippocampi with grossly different morphologies. Here, we present a surface-based registration method that solves this issue in a contrast-agnostic, topology-preserving manner. Specifically, the entire hippocampus is first analytically unfolded, and then samples are registered in 2D unfolded space based on thickness, curvature, and gyrification. We demonstrate this method in seven 3D histology samples and show superior alignment with respect to subfields using this method over more conventional registration approaches. HighlightsO_LIHippocampal subfields contain microcircuits that are critical for memory and vulnerable to neurological disease. C_LIO_LIHippocampi have variable folding patterns between individuals, making them hard to register or parcellate. C_LIO_LIWe present a surface-based hippocampal registration method that is analogous to neocortical inflation to a sphere and registration. C_LIO_LITesting in seven detailed 3D histology samples revealed successful registration with respect to hippocampal subfields, and outperformed more conventional methods. C_LIO_LIThis method provides groundwork for detailed multimodal hippocampal mapping across subjects and datasets in the future. C_LI Data availabilityThe methodological advancements described here are made easily accessible in the latest version of open source software HippUnfold1. Code used in the development and testing of these methods, as well as preprocessed images, manual segmentations, and results, are openly available2.

neuroscience↗

A direct fiber approach to model sclera collagen architecture and biomechanics

Sclera collagen fiber microstructure and mechanical behavior are central to eye physiology and pathology. They are also complex, and are therefore often studied using modeling. Most models of sclera, however, have been built within a conventional continuum framework. In this framework, collagen fibers are incorporated as statistical distributions of fiber characteristics such as the orientation of a family of fibers. The conventional continuum approach, while proven successful for describing the macroscale behavior of the sclera, does not account for the sclera fibers are long, interwoven and interact with one another. Hence, by not considering these potentially crucial characteristics, the conventional approach has only a limited ability to capture and describe sclera structure and mechanics at smaller, fiber-level, scales. Recent advances in the tools for characterizing sclera microarchitecture and mechanics bring to the forefront the need to develop more advanced modeling techniques that can incorporate and take advantage of the newly available highly detailed information. Our goal was to create a new computational modeling approach that can represent the sclera fibrous microstructure more accurately than with the conventional continuum approach, while still capturing its macroscale behavior. In this manuscript we introduce the new modeling approach, that we call direct fiber modeling, in which the collagen architecture is built explicitly by long, continuous, interwoven fibers. The fibers are embedded in a continuum matrix representing the non-fibrous tissue components. We demonstrate the approach by doing direct fiber modeling of a rectangular patch of posterior sclera. The model integrated fiber orientations obtained by polarized light microscopy from coronal and sagittal cryosections of pig and sheep. The fibers were modeled using a Mooney- Rivlin model, and the matrix using a Neo-Hookean model. The fiber parameters were determined by inversely matching experimental equi-biaxial tensile data from the literature. After reconstruction, the direct fiber model orientations agreed well with the microscopy data both in the coronal plane (adjusted R2=0.8234) and in the sagittal plane (adjusted R2=0.8495) of the sclera. With the estimated fiber properties (C10=5746.9 MPa; C01=-5002.6MPa, matrix shear modulus 200kPa), the models stress-strain curves simultaneously fit the experimental data in radial and circumferential directions (adjusted R2s 0.9971 and 0.9508, respectively). The estimated fiber elastic modulus at 2.16% strain was 5.45GPa, in reasonable agreement with the literature. During stretch, the model exhibited stresses and strains at sub-fiber level, with interactions among individual fibers which are not accounted for by the conventional continuum methods. Our results demonstrate that direct fiber models can simultaneously describe the macroscale mechanics and microarchitecture of the sclera, and therefore that the approach can provide unique insight into tissue behavior questions inaccessible with continuum approaches. HighlightsCollagen fibers are the main load-bearing component of eye tissues. Conventional sclera modeling ignores that fibers are long, interwoven and interact. We demonstrate a direct fiber model with long, interwoven and interacting fibers. Collagen fiber mechanical properties were estimated using inverse fitting. The model captures simultaneously sclera fiber structure and macroscale mechanics.

bioengineering↗

Fiber enhancement and 3D orientation analysis inlabel-free two-photon fluorescence microscopy

3D fluorescence microscopy can be profitably used in combination with tissue clearing and myelin labeling techniques for investigating the human brain myeloarchitectonics with sub-micrometric resolution, and for providing detailed histological reference data for the validation of diffusion magnetic resonance imaging (dMRI) tractography. Differently from state-of-the-art polarimetry-based neuroimaging modalities such as 3D polarized light imaging and 3D polarized-sensitive optical coherence tomography, the quantitative histological analysis of cortical and white matter fiber architectures from fluorescence microscopy images requires the estimation of fiber orientations via image processing techniques, as Fourier or structure tensor analysis. However, these can be error-prone as they are not able to detect myelinated fibers in surrounding brain tissue. Here we present a novel image processing pipeline built around a 3D Frangi filter able to enhance fiber structures of varying diameters in tiled brain section reconstructions of arbitrary size, and to produce accurate 3D fiber orientation maps in both grey and white matter regions, while preserving the native resolution of the employed microscopy system. The developed software tool also features the estimation of fiber orientation distribution functions which, in view of their widespread use in the neuroimaging community, may favor a multimodal comparison with brain connectivity data obtained from the aforementioned label-free optical modalities, and the validation of modern dMRI-based tractography. The proposed image processing pipeline was applied to brain samples treated according to a novel label-free preparation technique capable of enhancing the autofluorescence of myelinated fiber axons, thus demonstrating the feasibility of single fiber orientation analyses in fluorescence microscopy without the need for exogenous staining.

bioengineering↗

Imaging crossing fibers in mouse, pig, monkey, and human brain using small-angle X-ray scattering

Myelinated axons (nerve fibers) efficiently transmit signals throughout the brain via action potentials. Multiple methods that are sensitive to axon orientations, from microscopy to magnetic resonance imaging, aim to reconstruct the brains structural connectome. As billions of nerve fibers traverse the brain with various possible geometries at each point, resolving fiber crossings is necessary to generate accurate structural connectivity maps. However, doing so with specificity is a challenging task because signals originating from oriented fibers can be influenced by brain (micro)structures unrelated to myelinated axons. X-ray scattering can specifically probe myelinated axons due to the periodicity of the myelin sheath, which yields distinct peaks in the scattering pattern. Here, we show that small-angle X-ray scattering (SAXS) can be used to detect myelinated, axon-specific fiber crossings. We first demonstrate the capability using strips of human corpus callosum to create artificial double- and triple-crossing fiber geometries, and we then apply the method in mouse, pig, vervet monkey, and human brains. Given its specificity, capability of 3-dimensional sampling and high resolution, SAXS can serve as a ground truth for validating MRI as well as microscopy-based methods. Statement of SignificanceTo study how the nerve fibers in our brain are interconnected, scientists need to visualize their trajectories, which often cross one another. Here, we show the unique capacity of small-angle X-ray scattering (SAXS) to study these fiber crossings without use of labelling, taking advantage of SAXSs specificity to myelin - the insulating sheath that is wrapped around nerve fibers. We use SAXS to detect double and triple crossing fibers and unveil intricate crossings in mouse, pig, vervet monkey, and human brains. This non-destructive method can uncover complex fiber trajectories and validate other less specific imaging methods (e.g., MRI or microscopy), towards accurate mapping of neuronal connectivity in the animal and human brain. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=88 SRC="FIGDIR/small/510198v2_ufig1.gif" ALT="Figure 1"> View larger version (62K): org.highwire.dtl.DTLVardef@479368org.highwire.dtl.DTLVardef@11eb0c9org.highwire.dtl.DTLVardef@1e883adorg.highwire.dtl.DTLVardef@1ce024_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

Post mortem mapping of connectional anatomy for the validation of diffusion MRI

Despite the impressive advances in diffusion MRI (dMRI) acquisition and analysis that have taken place during the Human Connectome era, dMRI tractography is still an imperfect source of information on the circuitry of the brain. In this review, we discuss methods for post mortem validation of dMRI tractography, fiber orientations, and other microstructural properties of axon bundles that are typically extracted from dMRI data. These methods include anatomic tracer studies, Klinglers dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.

neuroscience↗

MAGIC: A label-free fluorescence method for 3D high-resolution reconstruction of myelinated fibers in large volumes

Analyzing the structure of neuronal fibers with single axon resolution, in large volumes, remains an unresolved challenge in connectomics. Here, we propose MAGIC (Myelin Autofluorescence imaging by Glycerol Induced Contrast enhancement), a simple tissue preparation method to perform label-free fluorescence imaging of myelinated fibers. We demonstrate its broad applicability by performing mesoscopic reconstruction at sub-micron resolution of mouse, rat, monkey, and human brain samples and by quantifying the different fiber organization in Control and Reeler mouses hippocampal sections.

neuroscience↗