Quantification of anisotropy and fiber orientation in human brain histological sections

Frequency-specific functional difference between gyri and sulci in naturalistic paradigm fMRI

Disentangling functional difference between cortical folding patterns of gyri and sulci provides novel insights into the relationship between brain structure and function. Previous studies using resting-state functional magnetic resonance imaging (rsfMRI) have revealed that sulcal signals exhibit stronger high-frequency but weaker low-frequency components compared to gyral ones, suggesting that gyri may serve as functional integration centers while sulci are segregated local processing units. In this study, we utilize naturalistic paradigm fMRI (nfMRI) to explore the functional difference between gyri and sulci as it has proven to record stronger functional integrations compared to rsfMRI. We adopt a convolutional neural network (CNN) to classify gyral and sulcal fMRI signals in the whole brain (the global model) and within functional brain networks (the local models). The frequency-specific difference between gyri and sulci is then inferred from the power spectral density (PSD) profiles of the learned filters in the CNN model. Our experimental results show that nfMRI shows higher gyral-sulcal PSD contrast effect sizes in the global model compared to rsfMRI. In the local models, the effect sizes are either increased or decreased depending on frequency bands and functional complexity of the FBNs. This study highlights the advantages of nfMRI in depicting the functional difference between gyri and sulci, and provides novel insights into unraveling the relationship between brain structure and function.

Toward a better understanding of how a gyrified brain develops

The size and shape of the cerebral cortex have changed dramatically across evolution. For some species, the cortex remains smooth (lissencephalic) throughout their lifetime, while for other species, including humans and other primates, the cortex increases substantially in size and becomes folded (gyrencephalic). A folded cortex boasts substantially increased surface area, cortical thickness, and neuronal density, and it is therefore associated with higher-order cognitive abilities. The mechanisms that drive gyrification in some species, while others remain lissencephalic despite many shared neurodevelopmental features, have been a topic of investigation for many decades, giving rise to multiple perspectives of how the gyrified cerebral cortex acquires its unique shape. Recently, a structurally unique germinal layer, known as the outer subventricular zone, and the specialized cell type that populates it, called basal radial glial cells, were identified, and these have been shown to be indispensable for cortical expansion and folding. Transcriptional analyses and gene manipulation models have provided an invaluable insight into many of the key cellular and genetic drivers of gyrification. However, the degree to which certain biomechanical, genetic, and cellular processes drive gyrification remains under investigation. This review considers the key aspects of cerebral expansion and folding that have been identified to date and how theories of gyrification have evolved to incorporate this new knowledge.

Mapping the individual human cortex using multidimensional MRI and unsupervised learning

Human evolution has seen the development of higher-order cognitive and social capabilities in conjunction with the unique laminar cytoarchitecture of the human cortex. Moreover, early-life cortical maldevelopment has been associated with various neurodevelopmental diseases. Despite these connections, there is currently no noninvasive technique available for imaging the detailed cortical laminar structure. This study aims to address this scientific and clinical gap by introducing an approach for imaging human cortical lamina. This method combines diffusion-relaxation multidimensional MRI with a tailored unsupervised machine learning approach that introduces enhanced microstructural sensitivity. This new imaging method simultaneously encodes the microstructure, the local chemical composition and importantly their correlation within complex and heterogenous tissue. To validate our approach, we compared the intra-cortical layers obtained using our ex vivo MRI-based method with those derived from Nissl staining of postmortem human brain specimens. The integration of unsupervised learning with diffusion-relaxation correlation MRI generated maps that demonstrate sensitivity to areal differences in cytoarchitectonic features observed in histology. Significantly, our observations revealed layer-specific diffusion-relaxation signatures, showing reductions in both relaxation times and diffusivities at the deeper cortical levels. These findings suggest a radial decrease in myelin content and changes in cell size and anisotropy, reflecting variations in both cytoarchitecture and myeloarchitecture. Additionally, we demonstrated that 1D relaxation and high-order diffusion MRI scalar indices, even when aggregated and used jointly in a multimodal fashion, cannot disentangle the cortical layers. Looking ahead, our technique holds the potential to open new avenues of research in human neurodevelopment and the vast array of disorders caused by disruptions in neurodevelopment.

Temporal fingerprints of cortical gyrification in marmosets and humans

Recent neuroimaging studies in humans have reported distinct temporal dynamics of gyri and sulci, which may be associated with putative functions of cortical gyrification. However, the complex folding patterns of the human cortex make it difficult to explain temporal patterns of gyrification. In this study, we used the common marmoset as a simplified model to examine the temporal characteristics and compare them with the complex gyrification of humans. Using a brain-inspired deep neural network, we obtained reliable temporal-frequency fingerprints of gyri and sulci from the awake rs-fMRI data of marmosets and humans. Notably, the temporal fingerprints of one region successfully classified the gyrus/sulcus of another region in both marmosets and humans. Additionally, the temporal-frequency fingerprints were remarkably similar in both species. We then analyzed the resulting fingerprints in several domains and adopted the Wavelet Transform Coherence approach to characterize the gyro-sulcal coupling patterns. In both humans and marmosets, sulci exhibited higher frequency bands than gyri, and the two were temporally coupled within the same range of phase angles. This study supports the notion that gyri and sulci possess unique and evolutionarily conserved features that are consistent across functional areas, and advances our understanding of the functional role of cortical gyrification.

An open resource combining multi-contrast MRI and microscopy in the macaque brain

Understanding brain structure and function often requires combining data across different modalities and scales to link microscale cellular structures to macroscale features of whole brain organisation. Here we introduce the BigMac dataset, a resource combining in vivo MRI, extensive postmortem MRI and multi-contrast microscopy for multimodal characterisation of a single whole macaque brain. The data spans modalities (MRI and microscopy), tissue states (in vivo and postmortem), and four orders of spatial magnitude, from microscopy images with micrometre or sub-micrometre resolution, to MRI signals on the order of millimetres. Crucially, the MRI and microscopy images are carefully co-registered together to facilitate quantitative multimodal analyses. Here we detail the acquisition, curation, and first release of the data, that together make BigMac a unique, openly-disseminated resource available to researchers worldwide. Further, we demonstrate example analyses and opportunities afforded by the data, including improvement of connectivity estimates from ultra-high angular resolution diffusion MRI, neuroanatomical insight provided by polarised light imaging and myelin-stained histology, and the joint analysis of MRI and microscopy data for reconstruction of the microscopy-inspired connectome. All data and code are made openly available.

Gyral peaks and patterns in human brains

Cortical folding patterns are related to brain function, cognition, and behavior. Since the relationship has not been fully explained on a coarse scale, many efforts have been devoted to the identification of finer grained cortical landmarks, such as sulcal pits and gyral peaks, which were found to remain invariant across subjects and ages and the invariance may be related to gene mediated proto-map. However, gyral peaks were only investigated on macaque monkey brains, but not on human brains where the investigation is challenged due to high inter-individual variabilities. To this end, in this work, we successfully identified 96 gyral peaks both on the left and right hemispheres of human brains, respectively. These peaks are spatially consistent across individuals. Higher or sharper peaks are more consistent across subjects. Both structural and functional graph metrics of peaks are significantly different from other cortical regions, and more importantly, these nodal graph metrics are anti-correlated with the spatial consistency metrics within peaks. In addition, the distribution of peaks and various cortical anatomical, structural/functional connective features show hemispheric symmetry. These findings provide new clues to understanding the cortical landmarks, as well as their relationship with brain functions, cognition, behavior in both healthy and aberrant brains.

A comparison of altered white matter microstructure in youth born with congenital heart disease or born preterm

Introduction

Alterations to white matter microstructure as detected by diffusion tensor imaging have been documented in both individuals born with congenital heart disease (CHD) and individuals born preterm. However, it remains unclear if these disturbances are the consequence of similar underlying microstructural disruptions. This study used multicomponent driven equilibrium single pulse observation of T₁ and T₂ (mcDESPOT) and neurite orientation dispersion and density imaging (NODDI) to characterize and compare alterations to three specific microstructural elements of white matter - myelination, axon density, and axon orientation - in youth born with CHD or born preterm.

Methods

Participants aged 16 to 26 years with operated CHD or born ≤33 weeks gestational age and a group of healthy peers of the same age underwent a brain MRI including mcDESPOT and high angular resolution diffusion imaging acquisitions. Using tractometry, average values of myelin water fraction (MWF), neurite density index (NDI), and orientation dispersion index (ODI) were first calculated and compared between groups for 30 white matter bundles. Afterwards, bundle profiling was performed to further characterize the topology of the detected microstructural alterations.

Results

The CHD and preterm groups both presented with widespread bundles and bundle segments with lower MWF, accompanied by some occurrences of lower NDI, relative to controls. While there were no differences in ODI between the CHD and control groups, the preterm group presented with both higher and lower ODI compared to the control group and lower ODI compared to the CHD group.

Discussion

While youth born with CHD or born preterm both presented with apparent deficits in white matter myelination and axon density, youth born preterm presented with a unique profile of altered axonal organization. Future longitudinal studies should aim to better understand the emergence of these common and distinct microstructural alterations, which could orient the development of novel therapeutic approaches.

Music impacts brain cortical microstructural maturation in very preterm infants: A longitudinal diffusion MR imaging study

Preterm birth disrupts important neurodevelopmental processes occurring from mid-fetal to term-age. Musicotherapy, by enriching infants' sensory input, might enhance brain maturation during this critical period of activity-dependent plasticity. To study the impact of music on preterm infants' brain structural changes, we recruited 54 very preterm infants randomized to receive or not a daily music intervention, that have undergone a longitudinal multi-shell diffusion MRI acquisition, before the intervention (at 33 weeks' gestational age) and after it (at term-equivalent-age). Using whole-brain fixel-based (FBA) and NODDI analysis (n = 40), we showed a longitudinal increase of fiber cross-section (FC) and fiber density (FD) in all major cerebral white matter fibers. Regarding cortical grey matter, FD decreased while FC and orientation dispersion index (ODI) increased, reflecting intracortical multidirectional complexification and intracortical myelination. The music intervention resulted in a significantly higher longitudinal increase of FC and ODI in cortical paralimbic regions, namely the insulo-orbito-temporopolar complex, precuneus/posterior cingulate gyrus, as well as the auditory association cortex. Our results support a longitudinal early brain macro and microstructural maturation of white and cortical grey matter in preterm infants. The music intervention led to an increased intracortical complexity in regions important for socio-emotional development, known to be impaired in preterm infants.

Mapping astrogliosis in the individual human brain using multidimensional MRI

There are currently no non-invasive imaging methods available for astrogliosis assessment or mapping in the central nervous system despite its essential role in the response to many disease states, such as infarcts, neurodegenerative conditions, traumatic brain injury and infection. Multidimensional MRI is an increasingly employed imaging modality that maximizes the amount of encoded chemical and microstructural information by probing relaxation (T1 and T2) and diffusion mechanisms simultaneously. Here, we harness the exquisite sensitivity of this imagining modality to derive a signature of astrogliosis and disentangle it from normative brain at the individual level using machine learning. We investigated ex vivo cerebral cortical tissue specimens derived from seven subjects who sustained blast-induced injuries, which resulted in scar-border forming astrogliosis without being accompanied by other types of neuropathological abnormality, and from seven control brain donors. By performing a combined post-mortem radiology and histopathology correlation study we found that astrogliosis induces microstructural and chemical changes that are robustly detected with multidimensional MRI, and which can be attributed to astrogliosis because no axonal damage, demyelination or tauopathy were histologically observed in any of the cases in the study. Importantly, we showed that no one-dimensional T1, T2 or diffusion MRI measurement can disentangle the microscopic alterations caused by this neuropathology. Based on these findings, we developed a within-subject anomaly detection procedure that generates MRI-based astrogliosis biomarker maps ex vivo, which were significantly and strongly correlated with co-registered histological images of increased glial fibrillary acidic protein deposition (r = 0.856, P < 0.0001; r = 0.789, P < 0.0001; r = 0.793, P < 0.0001, for diffusion-T2, diffusion-T1 and T1-T2 multidimensional data sets, respectively). Our findings elucidate the underpinning of MRI signal response from astrogliosis, and the demonstrated high spatial sensitivity and specificity in detecting reactive astrocytes at the individual level, and if reproduced in vivo, will significantly impact neuroimaging studies of injury, disease, repair and aging, in which astrogliosis has so far been an invisible process radiologically.

Modeling functional difference between gyri and sulci within intrinsic connectivity networks

Recently, the functional roles of the human cortical folding patterns have attracted increasing interest in the neuroimaging community. However, most existing studies have focused on the gyro-sulcal functional relationship on a whole-brain scale but possibly overlooked the localized and subtle functional differences of brain networks. Actually, accumulating evidences suggest that functional brain networks are the basic unit to realize the brain function; thus, the functional relationships between gyri and sulci still need to be further explored within different functional brain networks. Inspired by these evidences, we proposed a novel intrinsic connectivity network (ICN)-guided pooling-trimmed convolutional neural network (I-ptFCN) to revisit the functional difference between gyri and sulci. By testing the proposed model on the task functional magnetic resonance imaging (fMRI) datasets of the Human Connectome Project, we found that the classification accuracy of gyral and sulcal fMRI signals varied significantly for different ICNs, indicating functional heterogeneity of cortical folding patterns in different brain networks. The heterogeneity may be contributed by sulci, as only sulcal signals show heterogeneous frequency features across different ICNs, whereas the frequency features of gyri are homogeneous. These results offer novel insights into the functional difference between gyri and sulci and enlighten the functional roles of cortical folding patterns.

Microstructural Neurodegeneration of the Entorhinal-Hippocampus Pathway along the Alzheimer's Disease Continuum

BACKGROUND

Conventional neuroimaging biomarkers for the neurodegeneration of Alzheimer's disease (AD) are not sensitive enough to detect neurodegenerative alterations during the preclinical stage of AD individuals.

OBJECTIVE

We examined whether neurodegeneration of the entorhinal-hippocampal pathway could be detected along the AD continuum using ultra-high-field diffusion tensor imaging and tractography for ex vivo brain tissues.

METHODS

Postmortem brain specimens from a cognitively unimpaired individual without AD pathological changes (non-AD), a cognitively unimpaired individual with AD pathological changes (preclinical AD), and a demented individual with AD pathological changes (AD dementia) were scanned with an 11.7T diffusion magnetic resonance imaging. Fractional anisotropy (FA) values of the entorhinal layer II and number of perforant path fibers counted by tractography were compared among the AD continuum. Following the imaging analyses, the status of myelinated fibers and neuronal cells were verified by subsequent serial histological examinations.

RESULTS

At 250μm (zipped to 125μm) isotropic resolution, the entorhinal layer II islands and the perforant path fibers could be identified in non-AD and preclinical AD, but not in AD dementia, followed by histological verification. The FA value of the entorhinal layer II was the highest among the entorhinal laminae in non-AD and preclinical AD, whereas the FA values in the entorhinal laminae were homogeneously low in AD dementia. The FA values and number of perforant path fibers decreased along the AD continuum (non-AD>preclinical AD > AD dementia).

CONCLUSION

We successfully detected neurodegenerative alterations of the entorhinal-hippocampal pathway at the preclinical stage of the AD continuum.

COnstrained Reference frame diffusion TEnsor Correlation Spectroscopic (CORTECS) MRI: A practical framework for high-resolution diffusion tensor distribution imaging

High-resolution imaging studies have consistently shown that in cortical tissue water diffuses preferentially along radial and tangential orientations with respect to the cortical surface, in agreement with histology. These dominant orientations do not change significantly even if the relative contributions from microscopic water pools to the net voxel signal vary across experiments that use different diffusion times, b-values, TEs, and TRs. With this in mind, we propose a practical new framework for imaging non-parametric diffusion tensor distributions (DTDs) by constraining the microscopic diffusion tensors of the DTD to be diagonalized using the same orthonormal reference frame of the mesoscopic voxel. In each voxel, the constrained DTD (cDTD) is completely determined by the correlation spectrum of the microscopic principal diffusivities associated with the axes of the voxel reference frame. Consequently, all cDTDs are inherently limited to the domain of positive definite tensors and can be reconstructed efficiently using Inverse Laplace Transform methods. Moreover, the cDTD reconstruction can be performed using only data acquired efficiently with single diffusion encoding, although it also supports datasets with multiple diffusion encoding. In tissues with a well-defined architecture, such as the cortex, we can further constrain the cDTD to contain only cylindrically symmetric diffusion tensors and measure the 2D correlation spectra of principal diffusivities along the radial and tangential orientation with respect to the cortical surface. To demonstrate this framework, we perform numerical simulations and analyze high-resolution dMRI data from a fixed macaque monkey brain. We estimate 2D cDTDs in the cortex and derive, in each voxel, the marginal distributions of the microscopic principal diffusivities, the corresponding distributions of the microscopic fractional anisotropies and mean diffusivities along with their 2D correlation spectra to quantify the cDTD shape-size characteristics. Signal components corresponding to specific bands in these cDTD-derived spectra show high specificity to cortical laminar structures observed with histology. Our framework drastically simplifies the measurement of non-parametric DTDs in high-resolution datasets with mesoscopic voxel sizes much smaller than the radius of curvature of the underlying anatomy, e.g., cortical surface, and can be applied retrospectively to analyze existing diffusion MRI data from fixed cortical tissues.

Cortex2vector: anatomical embedding of cortical folding patterns

Current brain mapping methods highly depend on the regularity, or commonality, of anatomical structure, by forcing the same atlas to be matched to different brains. As a result, individualized structural information can be overlooked. Recently, we conceptualized a new type of cortical folding pattern called the 3-hinge gyrus (3HG), which is defined as the conjunction of gyri coming from three directions. Many studies have confirmed that 3HGs are not only widely existing on different brains, but also possess both common and individual patterns. In this work, we put further effort, based on the identified 3HGs, to establish the correspondences of individual 3HGs. We developed a learning-based embedding framework to encode individual cortical folding patterns into a group of anatomically meaningful embedding vectors (cortex2vector). Each 3HG can be represented as a combination of these embedding vectors via a set of individual specific combining coefficients. In this way, the regularity of folding pattern is encoded into the embedding vectors, while the individual variations are preserved by the multi-hop combination coefficients. Results show that the learned embeddings can simultaneously encode the commonality and individuality of cortical folding patterns, as well as robustly infer the complicated many-to-many anatomical correspondences among different brains.

High-resolution cortical MAP-MRI reveals areal borders and laminar substructures observed with histological staining

The variations in cellular composition and tissue architecture measured with histology provide the biological basis for partitioning the brain into distinct cytoarchitectonic areas and for characterizing neuropathological tissue alterations. Clearly, there is an urgent need to develop whole-brain neuroradiological methods that can assess cortical cyto- and myeloarchitectonic features non-invasively. Mean apparent propagator (MAP) MRI is a clinically feasible diffusion MRI method that quantifies efficiently and comprehensively the net microscopic displacements of water molecules diffusing in tissues. We investigate the sensitivity of high-resolution MAP-MRI to detecting areal and laminar variations in cortical cytoarchitecture and compare our results with observations from corresponding histological sections in the entire brain of a rhesus macaque monkey. High-resolution images of MAP-derived parameters, in particular the propagator anisotropy (PA), non-gaussianity (NG), and the return-to-axis probability (RTAP) reveal cortical area-specific lamination patterns in good agreement with the corresponding histological stained sections. In a few regions, the MAP parameters provide superior contrast to the five histological stains used in this study, delineating more clearly boundaries and transition regions between cortical areas and laminar substructures. Throughout the cortex, various MAP parameters can be used to delineate transition regions between specific cortical areas observed with histology and to refine areal boundaries estimated using atlas registration-based cortical parcellation. Using surface-based analysis of MAP parameters we quantify the cortical depth dependence of diffusion propagators in multiple regions-of-interest in a consistent and rigorous manner that is largely independent of the cortical folding geometry. The ability to assess cortical cytoarchitectonic features efficiently and non-invasively, its clinical feasibility, and translatability make high-resolution MAP-MRI a promising 3D imaging tool for studying whole-brain cortical organization, characterizing abnormal cortical development, improving early diagnosis of neurodegenerative diseases, identifying targets for biopsies, and complementing neuropathological investigations.

Gyral and sulcal connectivity in the human cerebral cortex

The rapid evolution of image acquisition and data analytic methods has established in vivo whole-brain tractography as a routine technology over the last 20 years. Imaging-based methods provide an additional approach to classic neuroanatomical studies focusing on biomechanical principles of anatomical organization and can in turn overcome the complexity of inter-individual variability associated with histological and tractography studies. In this work we propose a novel, reliable framework for determining brain tracts resolving the anatomical variance of brain regions. We distinguished 4 region types based on anatomical considerations: (i) gyral regions at borders between cortical communities; (ii) gyral regions within communities; (iii) sulcal regions at invariant locations across subjects; and (iv) other sulcal regions. Region types showed strikingly different anatomical and connection properties. Results allowed complementing the current understanding of the brain’s communication structure with a model of its anatomical underpinnings.

Using Advanced Diffusion-Weighted Imaging to Predict Cell Counts in Gray Matter: Potential and Pitfalls

Recent advances in diffusion imaging have given it the potential to non-invasively detect explicit neurobiological properties, beyond what was previously possible with conventional structural imaging. However, there is very little known about what cytoarchitectural properties these metrics, especially those derived from newer multi-shell models like Neurite Orientation Dispersion and Density Imaging (NODDI) correspond to. While these diffusion metrics do not promise any inherent cell type specificity, different brain cells have varying morphologies, which could influence the diffusion signal in distinct ways. This relationship is currently not well-characterized. Understanding the possible cytoarchitectural signatures of diffusion measures could allow them to estimate important neurobiological properties like cell counts, potentially resulting in a powerful clinical diagnostic tool. Here, using advanced diffusion imaging (NODDI) in the mouse brain, we demonstrate that different regions have unique relationships between cell counts and diffusion metrics. We take advantage of this exclusivity to introduce a framework to predict cell counts of different types of cells from the diffusion metrics alone, in a region-specific manner. We also outline the challenges of reliably developing such a model and discuss the precautions the field must take when trying to tie together medical imaging modalities and histology.

Higher-order multi-shell diffusion measures complement tensor metrics and volume in gray matter when predicting age and cognition

Recent advances in diffusion-weighted imaging have enabled us to probe the microstructure of even gray matter non-invasively. However, these advanced multi-shell protocols are often not included in large-scale studies as they significantly increase scan time. In this study, we investigated whether one set of multi-shell diffusion metrics commonly used in gray matter (as derived from Neurite Orientation Dispersion and Density Imaging, NODDI) provide enough additional information over typical tensor and volume metrics to justify the increased acquisition time, using the cognitive aging framework in the human hippocampus as a testbed. We first demonstrated that NODDI metrics are robust and reliable by replicating previous findings from our lab in a larger population of 79 younger (20.41 ± 1.89 years, 46 females) and 75 older (73.56 ± 6.26 years, 45 females) adults, showing that these metrics in the hippocampal subfields are sensitive to age and memory performance. We then asked how these subfield specific hippocampal NODDI metrics compared with standard tensor metrics and volume in predicting age and memory ability. We discovered that both NODDI and tensor measures separately predicted age and cognition in comparable capacities. However, integrating these modalities together considerably increased the predictive power of our logistic models, indicating that NODDI and tensor measures may be capturing independent microstructural information. We use these findings to encourage neuroimaging data collection consortiums to include a multi-shell diffusion sequence in their protocols since existing NODDI measures (and potential future multi-shell measures) may be able to capture microstructural variance that is missed by traditional approaches, even in studies exclusively examining gray matter.

Orientation dependence of inhomogeneous magnetization transfer and dipolar order relaxation rate in phospholipid bilayers

Inhomogeneous magnetization transfer (ihMT) is a novel MRI technique used to measure white matter myelination in the brain and spinal cord. In the brain, ihMT has a strong orientation dependence which is likely to arise from the anisotropy of dipolar couplings between protons on oriented lipids in the myelin bilayers. We measured the orientation dependence of the second moment (M₂) of the lineshape, dipolar order relaxation rate (R_1D), and ihMT ratio (ihMTR) in an oriented phospholipid bilayer at 9.4 T. We found a strong orientation dependence in all three parameters. ihMTR and R_1D were maximized when the bilayers were aligned perpendicular to B₀ and minimized near the magic angle (∼54.7°). M₂ followed an orientation dependence given by the second Legendre polynomial squared as predicted by the form of the secular dipolar Hamiltonian. These results were used to calculate the orientation dependence of R_1D and ihMTR in a diffusionless myelin sheath model, which showed ihMTR was maximised for fibers perpendicular to B₀ and minimised at 45°, similar to ex-vivo spinal cord with a larger prepulse frequency offset, but in contrast to in vivo brain findings. Adding fiber dispersion to this model smoothed the orientation dependence curve as expected. Our results suggest the importance of the effects of lipid diffusion and prepulse offset frequency on ihMTR.

A unified 3D map of microscopic architecture and MRI of the human brain

We present the first three-dimensional (3D) concordance maps of cyto- and fiber architecture of the human brain, combining histology, immunohistochemistry, and 7-T quantitative magnetic resonance imaging (MRI), in two individual specimens. These 3D maps each integrate data from approximately 800 microscopy sections per brain, showing neuronal and glial cell bodies, nerve fibers, and interneuronal populations, as well as ultrahigh-field quantitative MRI, all coaligned at the 200-μm scale to the stacked blockface images obtained during sectioning. These unprecedented 3D multimodal datasets are shared without any restrictions and provide a unique resource for the joint study of cell and fiber architecture of the brain, detailed anatomical atlasing, or modeling of the microscopic underpinnings of MRI contrasts.

Callosal Fiber Length Scales with Brain Size According to Functional Lateralization, Evolution, and Development

Brain size significantly impacts the organization of white matter fibers. Fiber length scaling, the degree to which fiber length varies according to brain size, was overlooked. We investigated how fiber lengths within the corpus callosum, the most prominent white matter tract, vary according to brain size. The results showed substantial variation in length scaling among callosal fibers, replicated in two large healthy cohorts (∼2000 human subjects, including both sexes). The underscaled callosal fibers mainly connected the precentral gyrus and parietal cortices, whereas the overscaled callosal fibers mainly connected the prefrontal cortices. The variation in such length scaling was biologically meaningful: larger scaling corresponded to larger neurite density index but smaller fractional anisotropy values; cortical regions connected by the callosal fibers with larger scaling were more lateralized functionally as well as phylogenetically and ontogenetically more recent than their counterparts. These findings highlight an interaction between interhemispheric communication and organizational and adaptive principles underlying brain development and evolution.SIGNIFICANCE STATEMENT Brain size varies across evolution, development, and individuals. Relative to small brains, the neural fiber length in large brains is inevitably increased, but the degree of such increase may differ between fiber tracts. Such a difference, if it exists, is valuable for understanding adaptive neural principles in large versus small brains during evolution and development. The present study showed a substantial difference in the length increase between the callosal fibers that connect the two hemispheres, replicated in two large healthy cohorts. Together, our study demonstrates that reorganization of interhemispheric fibers length according to brain size is intrinsically related to fiber composition, functional lateralization, cortical myelin content, and evolutionary and developmental expansion.

Quantitative mapping of the brain's structural connectivity using diffusion MRI tractography: A review

Diffusion magnetic resonance imaging (dMRI) tractography is an advanced imaging technique that enables in vivo reconstruction of the brain's white matter connections at macro scale. It provides an important tool for quantitative mapping of the brain's structural connectivity using measures of connectivity or tissue microstructure. Over the last two decades, the study of brain connectivity using dMRI tractography has played a prominent role in the neuroimaging research landscape. In this paper, we provide a high-level overview of how tractography is used to enable quantitative analysis of the brain's structural connectivity in health and disease. We focus on two types of quantitative analyses of tractography, including: 1) tract-specific analysis that refers to research that is typically hypothesis-driven and studies particular anatomical fiber tracts, and 2) connectome-based analysis that refers to research that is more data-driven and generally studies the structural connectivity of the entire brain. We first provide a review of methodology involved in three main processing steps that are common across most approaches for quantitative analysis of tractography, including methods for tractography correction, segmentation and quantification. For each step, we aim to describe methodological choices, their popularity, and potential pros and cons. We then review studies that have used quantitative tractography approaches to study the brain's white matter, focusing on applications in neurodevelopment, aging, neurological disorders, mental disorders, and neurosurgery. We conclude that, while there have been considerable advancements in methodological technologies and breadth of applications, there nevertheless remains no consensus about the "best" methodology in quantitative analysis of tractography, and researchers should remain cautious when interpreting results in research and clinical applications.

Regenerating the Injured Spinal Cord at the Chronic Phase by Engineered iPSCs-Derived 3D Neuronal Networks

Cell therapy using induced pluripotent stem cell-derived neurons is considered a promising approach to regenerate the injured spinal cord (SC). However, the scar formed at the chronic phase is not a permissive microenvironment for cell or biomaterial engraftment or for tissue assembly. Engineering of a functional human neuronal network is now reported by mimicking the embryonic development of the SC in a 3D dynamic biomaterial-based microenvironment. Throughout the in vitro cultivation stage, the system's components have a synergistic effect, providing appropriate cues for SC neurogenesis. While the initial biomaterial supported efficient cell differentiation in 3D, the cells remodeled it to provide an inductive microenvironment for the assembly of functional SC implants. The engineered tissues are characterized for morphology and function, and their therapeutic potential is investigated, revealing improved structural and functional outcomes after acute and chronic SC injuries. Such technology is envisioned to be translated to the clinic to rewire human injured SC.

Cortical development coupling between surface area and sulcal depth on macaque brains

Postnatal development of cerebral cortex is associated with a variety of neuronal processes and is thus critical to development of brain function and cognition. Longitudinal changes of cortical morphology and topology, such as postnatal cortical thinning and flattening have been widely studied. However, thorough and systematic investigation of such cortical change, including how to quantify it from multiple spatial directions and how to relate it to surface topology, is rarely found. In this work, based on a longitudinal macaque neuroimaging dataset, we quantified local changes in gyral white matter's surface area and sulcal depth during early development. We also investigated how these two metrics are coupled and how this coupling is linked to cortical surface topology, underlying white matter, and positions of functional areas. Semi-parametric generalized additive models were adopted to quantify the longitudinal changes of surface area (A) and sulcal depth (D), and the coupling patterns between them. This resulted in four classes of regions, according to how they change compared with global change throughout early development: slower surface area change and slower sulcal depth change (slowA_slowD), slower surface area change and faster sulcal depth change (slowA_fastD), faster surface area change and slower sulcal depth change (fastA_slowD), and faster surface area change and faster sulcal depth change (fastA_fastD). We found that cortex-related metrics, including folding pattern and cortical thickness, vary along slowA_fastD-fastA_slowD axis, and structural connection-related metrics vary along fastA_fastD-slowA_slowD axis, with which brain functional sites align better. It is also found that cortical landmarks, including sulcal pits and gyral hinges, spatially reside on the borders of the four patterns. These findings shed new lights on the relationship between cortex development, surface topology, axonal wiring pattern and brain functions.

Neurite density of white matter significantly correlates with tuberous sclerosis complex disease severity

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Whole-brain white matter neurite density significantly reduces with TSC severity.

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A white matter quantification may be important for the evaluation of TSC patients.

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Low neurite density clusters are larger in severe TSC patients.

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Neurite density is an accurate MRI metric for the evaluation of TSC white-matter.

Objective

To assess whether white matter (WM) diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) derived measures correlate with tuberous sclerosis complex (TSC) disease severity.

Cohort and methods

A multi-shell diffusion protocol was added to the clinical MRI brain scans of thirteen patients including 6 males and 7 females with a mean ± std age of 17.2 ± 5.8 years. Fractional anisotropy (FA) and mean diffusivity (MD) were generated from DTI and neurite density index (NDI), orientation dispersion index (ODI) and free water index (fiso) were generated from NODDI. A clinical score was determined for each patient according to the existence of epilepsy, developmental delay, autism or psychiatric disorders. Whole-brain segmented WM was averaged for each parametric map and 3 group k-means clustering was performed on the NDI and FA maps. MRI quantitative parameters were correlated with the clinical scores.

Results

Segmented whole brain WM averages of MD and NDI values showed significant negative (p = 0.0058) and positive (p = 0.0092) correlations with the clinical scores, respectively. Additionally, the contribution of the low and high NDI-based clusters to the whole brain WM significantly correlated with the clinical scores (p = 0.03 and p = 0.00047, respectively). No correlation was found when the clusters were based on the FA maps.

Conclusion

Advanced diffusion MRI of TSC patients revealed widespread WM alterations. Neurite density showed significant correlations with disease severity and is therefore suggested to reflect an underlying biological process in TSC WM. The quantification of WM alterations by advanced diffusion MRI may be an additional biomarker for TSC and may be advantageous as a complementary MR protocol for the evaluation of TSC patients.

Gyral Hinges Account for the Highest Cost and the Highest Communication Capacity in a Corticocortical Network

Prior studies reported the global structure of brain networks exhibits the "small-world" and "rich-world" attributes. However, the underlying structural and functional architecture highlighted by these graph theory findings hasn't been explicitly related to the morphology of the cortex. This could be attributed to the lower resolution of used folding patterns, such as gyro-sulcal patterns. By defining a novel gyral folding pattern, termed gyral hinge (GH), which is the conjunction of ordinary gyri from multiple directions, we found GHs possess the highest length and cost in the white matter fiber connective network, and the shortest paths in the network tend to travel through GHs in their middle part. Based on these findings, we would hypothesize GHs could reside in the centers of a network core, thereby accounting for the highest cost and the highest communication capacity in a corticocortical network. The following results further support our hypothesis: 1) GHs possess stronger functional network integration capacity. 2) Higher cost is found on the connection with GHs to hinges and GHs to GHs. 3) Moving GHs introduces higher extra network cost. Our findings and hypotheses could reveal a profound relationship among the cortical folding patterns, axonal wiring architectures, and brain functions.

The glial framework reveals white matter fiber architecture in human and primate brains

[Figure: see text].

Diffuse axonal injury has a characteristic multidimensional MRI signature in the human brain

Axonal injury is a major contributor to the clinical symptomatology in patients with traumatic brain injury. Conventional neuroradiological tools, such as CT and MRI, are insensitive to diffuse axonal injury (DAI) caused by trauma. Diffusion tensor MRI parameters may change in DAI lesions; however, the nature of these changes is inconsistent. Multidimensional MRI is an emerging approach that combines T1, T2, and diffusion, and replaces voxel-averaged values with distributions, which allows selective isolation of specific potential abnormal components. By performing a combined post-mortem multidimensional MRI and histopathology study, we aimed to investigate T1-T2-diffusion changes linked to DAI and to define their histopathological correlates. Corpora callosa derived from eight subjects who had sustained traumatic brain injury, and three control brain donors underwent post-mortem ex vivo MRI at 7 T. Multidimensional, diffusion tensor, and quantitative T1 and T2 MRI data were acquired and processed. Following MRI acquisition, slices from the same tissue were tested for amyloid precursor protein (APP) immunoreactivity to define DAI severity. A robust image co-registration method was applied to accurately match MRI-derived parameters and histopathology, after which 12 regions of interest per tissue block were selected based on APP density, but blind to MRI. We identified abnormal multidimensional T1-T2, diffusion-T2, and diffusion-T1 components that are strongly associated with DAI and used them to generate axonal injury images. We found that compared to control white matter, mild and severe DAI lesions contained significantly larger abnormal T1-T2 component (P = 0.005 and P < 0.001, respectively), and significantly larger abnormal diffusion-T2 component (P = 0.005 and P < 0.001, respectively). Furthermore, within patients with traumatic brain injury the multidimensional MRI biomarkers differentiated normal-appearing white matter from mild and severe DAI lesions, with significantly larger abnormal T1-T2 and diffusion-T2 components (P = 0.003 and P < 0.001, respectively, for T1-T2; P = 0.022 and P < 0.001, respectively, for diffusion-T2). Conversely, none of the conventional quantitative MRI parameters were able to differentiate lesions and normal-appearing white matter. Lastly, we found that the abnormal T1-T2, diffusion-T1, and diffusion-T2 components and their axonal damage images were strongly correlated with quantitative APP staining (r = 0.876, P < 0.001; r = 0.727, P < 0.001; and r = 0.743, P < 0.001, respectively), while producing negligible intensities in grey matter and in normal-appearing white matter. These results suggest that multidimensional MRI may provide non-invasive biomarkers for detection of DAI, which is the pathological substrate for neurological disorders ranging from concussion to severe traumatic brain injury.

Synchrotron X-ray micro-CT as a validation dataset for diffusion MRI in whole mouse brain

PURPOSE

To introduce synchrotron X-ray microcomputed tomography (microCT) and demonstrate its use as a natively isotropic, nondestructive, 3D validation modality for diffusion MRI in whole, fixed mouse brain.

METHODS

Postmortem diffusion MRI and microCT data were acquired of the same whole mouse brain. Diffusion data were processed using constrained spherical deconvolution. Synchrotron data were acquired at an isotropic voxel size of 1.17 μm. Structure tensor analysis was used to calculate fiber orientation distribution functions from the microCT data. A pipeline was developed to spatially register the 2 datasets in order to perform qualitative comparisons of fiber geometries represented by fiber orientation distribution functions. Fiber orientations from both modalities were used to perform whole-brain deterministic tractography to demonstrate validation of long-range white matter pathways.

RESULTS

Fiber orientation distribution functions were able to be extracted throughout the entire microCT dataset, with spatial registration to diffusion MRI simplified due to the whole brain extent of the microCT data. Fiber orientations and tract pathways showed good agreement between modalities.

CONCLUSION

Synchrotron microCT is a potentially valuable new tool for future multi-scale diffusion MRI validation studies, providing comparable value to optical histology validation methods while addressing some key limitations in data acquisition and ease of processing.

Gyral-sulcal contrast in intrinsic functional brain networks across task performances

Functional mechanism of the brain and its relationship with the brain structural substrate have been an interest for multiple disciplines for centuries. Recently, gyri and sulci, two basic cortical folding patterns, have been demonstrated to act different functional roles. Specifically, a variety of functional MRI (fMRI) studies have consistently suggested that gyri represent a global functional center while sulci serve as a local functional unit under either resting state or task stimulus, which are further supported by brain structural analysis reporting that gyri have thicker cortex and denser long-distance axonal fibers. However, the consistency of such gyral-sulcal functional difference across different task stimuli, as well as its association with task conditions, remains to be explored. To this end, we used intrinsic networks as the testbed for cross-task comparison, and adopted a computational framework of dictionary learning and sparse representation of whole-brain fMRI signals to systematically examine the potential gyral-sulcal difference in signal representation residual (SRR) which reflected the degree of global functional communication. Using all seven task-based fMRI datasets in Human Connectome Project Q1 release, we found that within the intrinsic functional networks, the fMRI SRR was significantly smaller on gyral regions than on sulcal regions across different task stimuli, indicating that gyral regions were more involved in global functions of the brain and interregional communications. Moreover, the magnitudes of such gyral-sulcal difference varied across task conditions and intrinsic networks. Our work adds novel explanation and insight to the existing knowledge of functional differences between gyri and sulci.

Nanostructure-specific X-ray tomography reveals myelin levels, integrity and axon orientations in mouse and human nervous tissue

Myelin insulates neuronal axons and enables fast signal transmission, constituting a key component of brain development, aging and disease. Yet, myelin-specific imaging of macroscopic samples remains a challenge. Here, we exploit myelin’s nanostructural periodicity, and use small-angle X-ray scattering tensor tomography (SAXS-TT) to simultaneously quantify myelin levels, nanostructural integrity and axon orientations in nervous tissue. Proof-of-principle is demonstrated in whole mouse brain, mouse spinal cord and human white and gray matter samples. Outcomes are validated by 2D/3D histology and compared to MRI measurements sensitive to myelin and axon orientations. Specificity to nanostructure is exemplified by concomitantly imaging different myelin types with distinct periodicities. Finally, we illustrate the method’s sensitivity towards myelin-related diseases by quantifying myelin alterations in dysmyelinated mouse brain. This non-destructive, stain-free molecular imaging approach enables quantitative studies of myelination within and across samples during development, aging, disease and treatment, and is applicable to other ordered biomolecules or nanostructures.

Small-angle X-ray scattering (SAXS) combines the high tissue penetration of X-rays with specificity to periodic nanostructures. The authors use SAXS tensor tomography (SAXS-TT) on intact mouse and human brain tissue samples, to quantify myelin levels and determine myelin integrity, myelinated axon orientation, and fibre tracts non-destructively.

Investigating the relationship between diffusion kurtosis tensor imaging (DKTI) and histology within the normal human brain

Measurements of water diffusion with MRI have been used as a biomarker of tissue microstructure and heterogeneity. In this study, diffusion kurtosis tensor imaging (DKTI) of the brain was undertaken in 10 healthy volunteers at a clinical field strength of 3 T. Diffusion and kurtosis metrics were measured in regions-of-interest on the resulting maps and compared with quantitative analysis of normal post-mortem tissue histology from separate age-matched donors. White matter regions showed low diffusion (0.60 ± 0.04 × 10-3 mm2/s) and high kurtosis (1.17 ± 0.06), consistent with a structured heterogeneous environment comprising parallel neuronal fibres. Grey matter showed intermediate diffusion (0.80 ± 0.02 × 10-3 mm2/s) and kurtosis (0.82 ± 0.05) values. An important finding is that the subcortical regions investigated (thalamus, caudate and putamen) showed similar diffusion and kurtosis properties to white matter. Histological staining of the subcortical nuclei demonstrated that the predominant grey matter was permeated by small white matter bundles, which could account for the similar kurtosis to white matter. Quantitative histological analysis demonstrated higher mean tissue kurtosis and vector standard deviation values for white matter (1.08 and 0.81) compared to the subcortical regions (0.34 and 0.59). Mean diffusion on DKTI was positively correlated with tissue kurtosis (r = 0.82, p < 0.05) and negatively correlated with vector standard deviation (r = -0.69, p < 0.05). This study demonstrates how DKTI can be used to study regional structural variations in the cerebral tissue microenvironment and could be used to probe microstructural changes within diseased tissue in the future.

Recent Advances in Neuroimaging of Epilepsy

Human neuroimaging has had a major impact on the biological understanding of epilepsy and the relationship between pathophysiology, seizure management, and outcomes. This review highlights notable recent advancements in hardware, sequences, methods, analyses, and applications of human neuroimaging techniques utilized to assess epilepsy. These structural, functional, and metabolic assessments include magnetic resonance imaging (MRI), positron emission tomography (PET), and magnetoencephalography (MEG). Advancements that highlight non-invasive neuroimaging techniques used to study the whole brain are emphasized due to the advantages these provide in clinical and research applications. Thus, topics range across presurgical evaluations, understanding of epilepsy as a network disorder, and the interactions between epilepsy and comorbidities. New techniques and approaches are discussed which are expected to emerge into the mainstream within the next decade and impact our understanding of epilepsies. Further, an increasing breadth of investigations includes the interplay between epilepsy, mental health comorbidities, and aberrant brain networks. In the final section of this review, we focus on neuroimaging studies that assess bidirectional relationships between mental health comorbidities and epilepsy as a model for better understanding of the commonalities between both conditions.

Fundamental functional differences between gyri and sulci: implications for brain function, cognition, and behavior

Folding of the cerebral cortex is a prominent characteristic of mammalian brains. Alterations or deficits in cortical folding are strongly correlated with abnormal brain function, cognition, and behavior. Therefore, a precise mapping between the anatomy and function of the brain is critical to our understanding of the mechanisms of brain structural architecture in both health and diseases. Gyri and sulci, the standard nomenclature for cortical anatomy, serve as building blocks to make up complex folding patterns, providing a window to decipher cortical anatomy and its relation with brain functions. Huge efforts have been devoted to this research topic from a variety of disciplines including genetics, cell biology, anatomy, neuroimaging, and neurology, as well as involving computational approaches based on machine learning and artificial intelligence algorithms. However, despite increasing progress, our understanding of the functional anatomy of gyro-sulcal patterns is still in its infancy. In this review, we present the current state of this field and provide our perspectives of the methodologies and conclusions concerning functional differentiation between gyri and sulci, as well as the supporting information from genetic, cell biology, and brain structure research. In particular, we will further present a proposed framework for attempting to interpret the dynamic mechanisms of the functional interplay between gyri and sulci. Hopefully, this review will provide a comprehensive summary of anatomo-functional relationships in the cortical gyro-sulcal system together with a consideration of how these contribute to brain function, cognition, and behavior, as well as to mental disorders.

Interpolation and Averaging of Diffusion MRI Multi-Compartment Models

Multi-compartment models (MCM) are increasingly used to characterize the brain white matter microstructure from diffusion-weighted imaging (DWI). Their use in clinical studies is however limited by the inability to resample an MCM image towards a common reference frame, or to construct atlases from such brain microstructure models. We propose to solve this problem by first identifying that these two tasks amount to the same problem. We propose to tackle it by viewing it as a simplification problem, solved thanks to spectral clustering and the definition of semi-metrics between several usual compartments encountered in the MCM literature. This generic framework is evaluated for two models: the multi-tensor model where individual fibers are modeled as individual tensors and the diffusion direction imaging (DDI) model that differentiates intra- and extra-axonal components of each fiber. Results on simulated data, simulated transformations and real data show the ability of our method to well interpolate MCM images of these types. We finally present as an application an MCM template of normal controls constructed using our approach.

Peri-hematoma corticospinal tract integrity in intracerebral hemorrhage patients: A diffusion-tensor imaging study

BACKGROUND

The impact of perihematoma edema in Intracerebral Hemorrhage (ICH) on white matter integrity is uncertain. Fractional Anisotropy (FA), as measured with Diffusion Tensor Imaging (DTI), can be used to assess white matter microstructure. We tested the hypotheses that sections of the Corticospinal Tract (CST) passing through perihematoma edema would 1) have low FA relative to the contralateral CST and 2) would predict NIHSS motor score in ICH patients.

METHODS

Patients were prospectively imaged with DTI at 48 h and 7 days after onset. Edema volume/extent was measured on CT at baseline and 24 h. FA, mean, axial and radial diffusivity were measured in the perihematoma edema, contralateral CST and sections of CST passing through the edema ('edematous CST').

RESULTS

Patients (n = 27, mean age 67 ± 13) were scanned with DTI at a median (IQR) of 42.3 (24.5) hours and 7.7 (1.8) days from onset. Median acute ICH volume was 8.8 (22) ml. FA in edematous CST at 72 h was decreased (0.37 ± 0.03) relative to contralateral CST (0.52 ± 0.06; p < 0.0001). Day 7 FA in edematous CST (0.35 ± 0.08) was also decreased compared to contralateral CST (0.54 ± 0.06; p < 0.0001). FA remained stable between 72 h (0.37 ± 0.03) and day 7 (0.35 ± 0.07; p = 0.350). FA at 72 h (ρ = -0.22, p = 0.420) and day 7 (ρ = -0.14, p = 0.624) was unrelated to 90-day motor score.

CONCLUSIONS

FA is decreased in the CST where it passes through the edema. Decreased FA in the edematous CST remained stable over time, was unrelated to motor score, and may represent water infiltration into the tracts rather than axonal injury.

Modelling white matter in gyral blades as a continuous vector field

Many brain imaging studies aim to measure structural connectivity with diffusion tractography. However, biases in tractography data, particularly near the boundary between white matter and cortical grey matter can limit the accuracy of such studies. When seeding from the white matter, streamlines tend to travel parallel to the convoluted cortical surface, largely avoiding sulcal fundi and terminating preferentially on gyral crowns. When seeding from the cortical grey matter, streamlines generally run near the cortical surface until reaching deep white matter. These so-called “gyral biases” limit the accuracy and effective resolution of cortical structural connectivity profiles estimated by tractography algorithms, and they do not reflect the expected distributions of axonal densities seen in invasive tracer studies or stains of myelinated fibres. We propose an algorithm that concurrently models fibre density and orientation using a divergence-free vector field within gyral blades to encourage an anatomically-justified streamline density distribution along the cortical white/grey-matter boundary while maintaining alignment with the diffusion MRI estimated fibre orientations. Using in vivo data from the Human Connectome Project, we show that this algorithm reduces tractography biases. We compare the structural connectomes to functional connectomes from resting-state fMRI, showing that our model improves cross-modal agreement. Finally, we find that after parcellation the changes in the structural connectome are very minor with slightly improved interhemispheric connections (i.e, more homotopic connectivity) and slightly worse intrahemi-spheric connections when compared to tracers.

Cortical 3-hinges could serve as hubs in cortico-cortical connective network

Mapping the relation between cortical convolution and structural/functional brain architectures could provide deep insights into the mechanisms of brain development, evolution and diseases. In our previous studies, we found a unique gyral folding pattern, termed a 3-hinge, which was defined as the conjunction of three gyral crests. The uniqueness of the 3-hinge was evidenced by its thicker cortex and stronger fiber connections than other gyral regions. However, the role that 3-hinges play in cortico-cortical connective architecture remains unclear. To this end, we conducted MRI studies by constructing structural cortico-cortical connective networks based on a fine-granular cortical parcellation, the parcels of which were automatically labeled as 3-hinge, 2-hinge (ordinary gyrus) or sulcus. On human brains, 3-hinges possess significantly higher degrees, strengths and betweennesses than 2-hinges, suggesting that 3-hinges could serve more like hubs in the cortico-cortical connective network. This hypothesis gains supports from human functional network analyses, in which 3-hinges are involved in more global functional networks than ordinary gyri. In addition, 3-hinges could serve as 'connector' hubs rather than 'provincial' hubs and they account for a dominant proportion of nodes in the high-level 'backbone' of the network. These structural results are reproduced on chimpanzee and macaque brains, while the roles of 3-hinges as hubs become more pronounced in higher order primates. Our new findings could provide a new window to the relation between cortical convolution, anatomical connection and brain function.

Marmoset Brain ISH Data Revealed Molecular Difference Between Cortical Folding Patterns

Literature studies have demonstrated the structural, connectional, and functional differences between cortical folding patterns in mammalian brains, such as convex and concave patterns. However, the molecular underpinning of such convex/concave differences remains largely unknown. Thanks to public access to a recently released set of marmoset whole-brain in situ hybridization data by RIKEN, Japan; this data's accessibility empowers us to improve our understanding of the organization, regulation, and function of genes and their relation to macroscale metrics of brains. In this work, magnetic resonance imaging and diffusion tensor imaging macroscale neuroimaging data in this dataset were used to delineate convex/concave patterns in marmoset and to examine their structural features. Machine learning and visualization tools were employed to investigate the possible transcriptome difference between cortical convex and concave patterns. Experimental results demonstrated that a collection of genes is differentially expressed in convex and concave patterns, and their expression profiles can robustly characterize and differentiate the two folding patterns. More importantly, neuroscientific interpretations of these differentially expressed genes, as well as axonal guidance pathway analysis and gene enrichment analysis, offer novel understanding of structural and functional differences between cortical folding patterns in different regions from a molecular perspective.

Imaging the Neuroimmune Dynamics Across Space and Time

The immune system is essential for maintaining homeostasis, as well as promoting growth and healing throughout the brain and body. Considering that immune cells respond rapidly to changes in their microenvironment, they are very difficult to study without affecting their structure and function. The advancement of non-invasive imaging methods greatly contributed to elucidating the physiological roles performed by immune cells in the brain across stages of the lifespan and contexts of health and disease. For instance, techniques like two-photon in vivo microscopy were pivotal for studying microglial functional dynamics in the healthy brain. Through these observations, their interactions with neurons, astrocytes, blood vessels and synapses were uncovered. High-resolution electron microscopy with immunostaining and 3D-reconstruction, as well as super-resolution fluorescence microscopy, provided complementary insights by revealing microglial interventions at synapses (phagocytosis, trogocytosis, synaptic stripping, etc.). In addition, serial block-face scanning electron microscopy has provided the first 3D reconstruction of a microglial cell at nanoscale resolution. This review will discuss the technical toolbox that currently allows to study microglia and other immune cells in the brain, as well as introduce emerging methods that were developed and could be used to increase the spatial and temporal resolution of neuroimmune imaging. A special attention will also be placed on positron emission tomography and the development of selective functional radiotracers for microglia and peripheral macrophages, considering their strong potential for research translation between animals and humans, notably when paired with other imaging modalities such as magnetic resonance imaging.

Probing in vivo cortical myeloarchitecture in humans via line-scan diffusion acquisitions at 7 T with 250-500 micron radial resolution

PURPOSE

The goal of this study was to measure diffusion signals within the cerebral cortex using the line-scan technique to achieve extremely high resolution in the radial direction (ie, perpendicular to the cortical surface) and to demonstrate the utility of these measurements for investigating laminar architecture in the living human brain.

METHODS

Line-scan diffusion data with 250-500 micron radial resolution were acquired at 7 T on 8 healthy volunteers, with each line prescribed perpendicularly to primary somatosensory cortex (S1) and primary motor cortex (M1). Apparent diffusion coefficients, fractional anisotropy values, and radiality indices were measured as a function of cortical depth.

RESULTS

In the deep layers of S1, we found evidence for high anisotropy and predominantly tangential diffusion, with low anisotropy observed in superficial S1. In M1, moderate anisotropy and predominantly radial diffusion was seen at almost all cortical depths. These patterns were consistent across subjects and were conspicuous without averaging data across different locations on the cortical sheet.

CONCLUSION

Our results are in accord with the myeloarchitecture of S1 and M1, known from prior histology studies: in S1, dense bands of tangential myelinated fibers run through the deep layers but not the superficial ones, and in M1, radial myelinated fibers are prominent at most cortical depths. This work therefore provides support for the idea that high-resolution diffusion signals, measured with the line-scan technique and receiving a boost in SNR at 7 T, may serve as a sensitive probe of in vivo laminar architecture.

Anatomo-radiological correlation between diffusion tensor imaging and histologic analyses of glial tumors: a preliminary study

BACKGROUND AND PURPOSE

The challenge of the neurosurgical management of gliomas lies in achieving a maximal resection without persistent functional deficit. Diffusion tensor imaging (DTI) allows non-invasive identification of white matter tracts and their interactions with the tumor. Previous DTI validation studies were compared with intraoperative cortical stimulation, but none was performed based on the tumor anatomopathological analysis. This preliminary study evaluates the correlation between the preoperative subcortical DTI tractography and histology in terms of fiber direction as well as potential tumor-related fiber disruption.

METHODS

Eleven patients harboring glial tumors underwent preoperative DTI images. Correlations were performed between the visual color-coded anisotropy (FA) map analysis and the tumor histology after "en bloc" resection. Thirty-one tumor areas were classified according to the degree of tumor infiltration, the destruction of myelin fibers and neurofilaments, the presence of organized white matter fibers, and their orientation in space.

RESULTS

After histologic comparison, the DTI sensitivity and specificity to predict disrupted fiber tracts were respectively of 89% and 90%. The positive and negative predicted values of DTI were 80% and 95%. The DTI data were in line with the histologic myelin fiber orientation in 90% of patients. In our series, the prevalence of destructed fiber was 31%. Glioblastoma WHO grade IV harbored a higher proportion of destructed white matter tracts. Lower WHO grades were associated with higher preservation of subcortical fiber tracts.

CONCLUSION

This DTI/histology study of "en bloc"-resected gliomas reported a high and reproducible concordance of the visual color-coded FA map with the histologic examination to predict subcortical fiber tract disruption. Our series brought consistency to the DTI data that could be performed routinely for glioma surgery to predict the tumor grade and the postoperative clinical outcomes.

Open access resource for cellular-resolution analyses of corticocortical connectivity in the marmoset monkey

Understanding the principles of neuronal connectivity requires tools for efficient quantification and visualization of large datasets. The primate cortex is particularly challenging due to its complex mosaic of areas, which in many cases lack clear boundaries. Here, we introduce a resource that allows exploration of results of 143 retrograde tracer injections in the marmoset neocortex. Data obtained in different animals are registered to a common stereotaxic space using an algorithm guided by expert delineation of histological borders, allowing accurate assignment of connections to areas despite interindividual variability. The resource incorporates tools for analyses relative to cytoarchitectural areas, including statistical properties such as the fraction of labeled neurons and the percentage of supragranular neurons. It also provides purely spatial (parcellation-free) data, based on the stereotaxic coordinates of 2 million labeled neurons. This resource helps bridge the gap between high-density cellular connectivity studies in rodents and imaging-based analyses of human brains.

Understanding principles of neuronal connectivity requires tools for quantification and visualization of large datasets. Here, the authors introduce an online resource encompassing the coordinates of two million neurons labelled by tracer injections in the marmoset cortex, and analysis tools.

Joint modelling of diffusion MRI and microscopy

The combination of diffusion MRI (dMRI) with microscopy provides unique opportunities to study microstructural features of tissue, particularly when acquired in the same sample. Microscopy is frequently used to validate dMRI microstructure models, addressing the indirect nature of dMRI signals. Typically, these modalities are analysed separately, and microscopy is taken as a gold standard against which dMRI-derived parameters are validated. Here we propose an alternative approach in which we combine dMRI and microscopy data obtained from the same tissue sample to drive a single, joint model. This simultaneous analysis allows us to take advantage of the breadth of information provided by complementary data acquired from different modalities. By applying this framework to a spherical-deconvolution analysis, we are able to overcome a known degeneracy between fibre dispersion and radial diffusion. Spherical-deconvolution based approaches typically estimate a global fibre response function to determine the fibre orientation distribution in each voxel. However, the assumption of a 'brain-wide' fibre response function may be challenged if the diffusion characteristics of white matter vary across the brain. Using a generative joint dMRI-histology model, we demonstrate that the fibre response function is dependent on local anatomy, and that current spherical-deconvolution based models may be overestimating dispersion and underestimating the number of distinct fibre populations per voxel.

Effect of Residual and Transformation Choice on Computational Aspects of Biomechanical Parameter Estimation of Soft Tissues

Several nonlinear and anisotropic constitutive models have been proposed to describe the biomechanical properties of soft tissues, and reliably estimating the unknown parameters in these models using experimental data is an important step towards developing predictive capabilities. However, the effect of parameter estimation technique on the resulting biomechanical parameters remains under-analyzed. Standard off-the-shelf techniques can produce unreliable results where the parameters are not uniquely identified and can vary with the initial guess. In this study, a thorough analysis of parameter estimation techniques on the resulting properties for four multi-parameter invariant-based constitutive models is presented. It was found that linear transformations have no effect on parameter estimation for the presented cases, and nonlinear transforms are necessary for any improvement. A distinct focus is put on the issue of non-convergence, and we propose simple modifications that not only improve the speed of convergence but also avoid convergence to a wrong solution. The proposed modifications are straightforward to implement and can avoid severe problems in the biomechanical analysis. The results also show that including the fiber angle as an unknown in the parameter estimation makes it extremely challenging, where almost all of the formulations and models fail to converge to the true solution. Therefore, until this issue is resolved, a non-mechanical—such as optical—technique for determining the fiber angle is required in conjunction with the planar biaxial test for a robust biomechanical analysis.

The Cerebral Cortex is Bisectionally Segregated into Two Fundamentally Different Functional Units of Gyri and Sulci

The human cerebral cortex is highly folded into diverse gyri and sulci. Accumulating evidences suggest that gyri and sulci exhibit anatomical, morphological, and connectional differences. Inspired by these evidences, we performed a series of experiments to explore the frequency-specific differences between gyral and sulcal neural activities from resting-state and task-based functional magnetic resonance imaging (fMRI) data. Specifically, we designed a convolutional neural network (CNN) based classifier, which can differentiate gyral and sulcal fMRI signals with reasonable accuracies. Further investigations of learned CNN models imply that sulcal fMRI signals are more diverse and more high frequency than gyral signals, suggesting that gyri and sulci truly play different functional roles. These differences are significantly associated with axonal fiber wiring and cortical thickness patterns, suggesting that these differences might be deeply rooted in their structural and cellular underpinnings. Further wavelet entropy analyses demonstrated the validity of CNN-based findings. In general, our collective observations support a new concept that the cerebral cortex is bisectionally segregated into 2 functionally different units of gyri and sulci.

A Web-Based Atlas Combining MRI and Histology of the Squirrel Monkey Brain

The squirrel monkey (Saimiri sciureus) is a commonly-used surrogate for humans in biomedical research. In the neuroimaging community, MRI and histological atlases serve as valuable resources for anatomical, physiological, and functional studies of the brain; however, no digital MRI/histology atlas is currently available for the squirrel monkey. This paper describes the construction of a web-based multi-modal atlas of the squirrel monkey brain. The MRI-derived information includes anatomical MRI contrast (i.e., T2-weighted and proton-density-weighted) and diffusion MRI metrics (i.e., fractional anisotropy and mean diffusivity) from data acquired both in vivo and ex vivo on a 9.4 Tesla scanner. The histological images include Nissl and myelin stains, co-registered to the corresponding MRI, allowing identification of cyto- and myelo-architecture. In addition, a bidirectional neuronal tracer, biotinylated dextran amine (BDA) was injected into the primary motor cortex, enabling highly specific identification of regions connected to the injection location. The atlas integrates the results of common image analysis methods including diffusion tensor imaging glyphs, labels of 57 white-matter tracts identified using DTI-tractography, and 18 cortical regions of interest identified from Nissl-revealed cyto-architecture. All data are presented in a common space, and all image types are accessible through a web-based atlas viewer, which allows visualization and interaction of user-selectable contrasts and varying resolutions. By providing an easy to use reference system of anatomical information, our web-accessible multi-contrast atlas forms a rich and convenient resource for comparisons of brain findings across subjects or modalities. The atlas is called the Combined Histology-MRI Integrated Atlas of the Squirrel Monkey (CHIASM). All images are accessible through our web-based viewer ( https://chiasm.vuse.vanderbilt.edu /), and data are available for download at ( https://www.nitrc.org/projects/smatlas/ ).

Histological validation of per-bundle water diffusion metrics within a region of fiber crossing following axonal degeneration

Micro-architectural characteristics of white matter can be inferred through analysis of diffusion-weighted magnetic resonance imaging (dMRI). The diffusion-dependent signal can be analyzed through several methods, with the tensor model being the most frequently used due to its straightforward interpretation and low requirements for acquisition parameters. While valuable information can be gained from the tensor-derived metrics in regions of homogeneous tissue organization, this model does not provide reliable microstructural information at crossing fiber regions, which are pervasive throughout human white matter. Several multiple fiber models have been proposed that seem to overcome the limitations of the tensor, with few providing per-bundle dMRI-derived metrics. However, biological interpretations of such metrics are limited by the lack of histological confirmation. To this end, we developed a straightforward biological validation framework. Unilateral retinal ischemia was induced in ten rats, which resulted in axonal (Wallerian) degeneration of the corresponding optic nerve, while the contralateral was left intact; the intact and injured axonal populations meet at the optic chiasm as they cross the midline, generating a fiber crossing region in which each population has different diffusion properties. Five rats served as controls. High-resolution ex vivo dMRI was acquired five weeks after experimental procedures. We correlated and compared histology to per-bundle descriptors derived from three methodologies for dMRI analysis (constrained spherical deconvolution and two multi-tensor representations). We found a tight correlation between axonal density (as evaluated through automatic segmentation of histological sections) with per-bundle apparent fiber density and fractional anisotropy (derived from dMRI). The multi-fiber methods explored were able to correctly identify the damaged fiber populations in a region of fiber crossings (chiasm). Our results provide validation of metrics that bring substantial and clinically useful information about white-matter tissue at crossing fiber regions. Our proposed framework is useful to validate other current and future dMRI methods.

Diffusion MRI microstructural models in the cervical spinal cord - Application, normative values, and correlations with histological analysis

Multi-compartment tissue modeling using diffusion magnetic resonance imaging has proven valuable in the brain, offering novel indices sensitive to the tissue microstructural environment in vivo on clinical MRI scanners. However, application, characterization, and validation of these models in the spinal cord remain relatively under-studied. In this study, we apply a diffusion "signal" model (diffusion tensor imaging, DTI) and two commonly implemented "microstructural" models (neurite orientation dispersion and density imaging, NODDI; spherical mean technique, SMT) in the human cervical spinal cord of twenty-one healthy controls. We first provide normative values of DTI, SMT, and NODDI indices in a number of white matter ascending and descending pathways, as well as various gray matter regions. We then aim to validate the sensitivity and specificity of these diffusion-derived contrasts by relating these measures to indices of the tissue microenvironment provided by a histological template. We find that DTI indices are sensitive to a number of microstructural features, but lack specificity. The microstructural models also show sensitivity to a number of microstructure features; however, they do not capture the specific microstructural features explicitly modelled. Although often regarded as a simple extension of the brain in the central nervous system, it may be necessary to re-envision, or specifically adapt, diffusion microstructural models for application to the human spinal cord with clinically feasible acquisitions - specifically, adjusting, adapting, and re-validating the modeling as it relates to both theory (i.e. relevant biology, assumptions, and signal regimes) and parameter estimation (for example challenges of acquisition, artifacts, and processing).