Anatomical Basis for Functional Specialization

Generative Modelling of Cortical Receptor Distributions from Cytoarchitectonic Images in the Macaque Brain

Neurotransmitter receptor densities are relevant for understanding the molecular architecture of brain regions. Quantitative in vitro receptor autoradiography, has been introduced to map neurotransmitter receptor distributions of brain areas. However, it is very time and cost-intensive, which makes it challenging to obtain whole-brain distributions. At the same time, high-throughput light microscopy and 3D reconstructions have enabled high-resolution brain maps capturing measures of cell density across the whole human brain. Aiming to bridge gaps in receptor measurements for building detailed whole-brain atlases, we study the feasibility of predicting realistic neurotransmitter density distributions from cell-body stainings. Specifically, we utilize conditional Generative Adversarial Networks (cGANs) to predict the density distributions of the M2 receptor of acetylcholine and the kainate receptor for glutamate in the macaque monkey's primary visual (V1) and motor cortex (M1), based on light microscopic scans of cell-body stained sections. Our model is trained on corresponding patches from aligned consecutive sections that display cell-body and receptor distributions, ensuring a mapping between the two modalities. Evaluations of our cGANs, both qualitative and quantitative, show their capability to predict receptor densities from cell-body stained sections while maintaining cortical features such as laminar thickness and curvature. Our work underscores the feasibility of cross-modality image translation problems to address data gaps in multi-modal brain atlases.

Visual Cortical Thickness Increases with Prolonged Artificial Vision Restoration

The Argus II retinal prosthesis restores visual perception to late blind patients. It has been shown that structural changes occur in the brain due to late-onset blindness, including cortical thinning in visual regions of the brain. Following vision restoration, it is not yet known whether these visual regions are reinvigorated and regain a normal cortical thickness or retain the diminished thickness from blindness. We evaluated the cortical thicknesses of ten Argus II Retinal Prostheses patients, ten blind patients, and thirteen sighted participants. The Argus II patients on average had a thicker left Cuneus Cortex and Lateral Occipital Cortex relative to the blind patients. The duration of the Argus II use (time since implant in active users) significantly partially correlated with thicker visual cortical regions in the left hemisphere. Furthermore, in the two case studies (scanned before and after implantation), the patient with longer device use (44.5 months) had an increase in the cortical thickness of visual regions, whereas the shorter-using patient did not (6.5 months). Finally, a third case, scanned at three time points post-implantation, showed an increase in cortical thickness in the Lateral Occipital Cortex between 43.5 and 57 months, which was maintained even after 3 years of disuse (106 months). Overall, the Argus II patients' cortical thickness was on average significantly rejuvenated in two higher visual regions and, patients using the implant for a longer duration had thicker visual regions. This research raises the possibility of structural plasticity reversing visual cortical atrophy in late-blind patients with prolonged vision restoration.

Mapping Cytoarchitectonics and Receptor Architectonics to Understand Brain Function and Connectivity

This review focuses on cytoarchitectonics and receptor architectonics as biological correlates of function and connectivity. It introduces the 3-dimensional cytoarchitectonic probabilistic maps of cortical areas and nuclei of the Julich-Brain Atlas, available at EBRAINS, to study structure-function relationships. The maps are linked to the BigBrain as microanatomical reference model and template space. The siibra software tool suite enables programmatic access to the maps and to receptor architectonic data that are anchored to brain areas. Such cellular and molecular data are tools for studying magnetic resonance connectivity including modeling and simulation. At the end, we highlight perspectives of the Julich-Brain as well as methodological considerations. Thus, microstructural maps as part of a multimodal atlas help elucidate the biological correlates of large-scale networks and brain function with a high level of anatomical detail, which provides a basis to study brains of patients with psychiatric disorders.

The role of the corpus callosum in language network connectivity in children

The specific role of the corpus callosum (CC) in language network organization remains unclear, two contrasting models have been proposed: inhibition of homotopic areas allowing for independent functioning of the hemispheres versus integration of information from both hemispheres. This study aimed to add to this discussion with the first investigation of language network connectivity in combination with CC volume measures. In 38 healthy children aged 6–12, we performed task‐based functional magnetic resonance imaging to measure language network connectivity, used structural magnetic resonance imaging to quantify CC subsection volumes, and administered various language tests to examine language abilities. We found an increase in left intrahemispheric and bilateral language network connectivity and a decrease in right intrahemispheric connectivity associated with larger volumes of the posterior, mid‐posterior, and central subsections of the CC. Consistent with that, larger volumes of the posterior parts of the CC were significantly associated with better verbal fluency and vocabulary, the anterior CC volume was positively correlated with verbal span. Thus, children with larger volumes of CC subsections showed increased interhemispheric language network connectivity and were better in different language domains. This study presents the first evidence that the CC is directly linked to language network connectivity and underlines the excitatory role of the CC in the integration of information from both hemispheres.

BigBrain 3D atlas of cortical layers: Cortical and laminar thickness gradients diverge in sensory and motor cortices

Histological atlases of the cerebral cortex, such as those made famous by Brodmann and von Economo, are invaluable for understanding human brain microstructure and its relationship with functional organization in the brain. However, these existing atlases are limited to small numbers of manually annotated samples from a single cerebral hemisphere, measured from 2D histological sections. We present the first whole-brain quantitative 3D laminar atlas of the human cerebral cortex. It was derived from a 3D histological atlas of the human brain at 20-micrometer isotropic resolution (BigBrain), using a convolutional neural network to segment, automatically, the cortical layers in both hemispheres. Our approach overcomes many of the historical challenges with measurement of histological thickness in 2D, and the resultant laminar atlas provides an unprecedented level of precision and detail. We utilized this BigBrain cortical atlas to test whether previously reported thickness gradients, as measured by MRI in sensory and motor processing cortices, were present in a histological atlas of cortical thickness and which cortical layers were contributing to these gradients. Cortical thickness increased across sensory processing hierarchies, primarily driven by layers III, V, and VI. In contrast, motor-frontal cortices showed the opposite pattern, with decreases in total and pyramidal layer thickness from motor to frontal association cortices. These findings illustrate how this laminar atlas will provide a link between single-neuron morphology, mesoscale cortical layering, macroscopic cortical thickness, and, ultimately, functional neuroanatomy.

Using deep learning to segment the layers of the cerebral cortex, this study presents the first whole brain quantitative atlas of cortical and laminar structure. This laminar atlas provides a novel framework for bridging between the scales of neuroscience.

The role of diffusion MRI in neuroscience

Diffusion-weighted imaging has pushed the boundaries of neuroscience by allowing us to examine the white matter microstructure of the living human brain. By doing so, it has provided answers to fundamental neuroscientific questions, launching a new field of research that had been largely inaccessible. We briefly summarize key questions that have historically been raised in neuroscience concerning the brain's white matter. We then expand on the benefits of diffusion-weighted imaging and its contribution to the fields of brain anatomy, functional models and plasticity. In doing so, this review highlights the invaluable contribution of diffusion-weighted imaging in neuroscience, presents its limitations and proposes new challenges for future generations who may wish to exploit this powerful technology to gain novel insights.

Visual brain plasticity induced by central and peripheral visual field loss

Disorders that specifically affect central and peripheral vision constitute invaluable models to study how the human brain adapts to visual deafferentation. We explored cortical changes after the loss of central or peripheral vision. Cortical thickness (CoTks) and resting-state cortical entropy (rs-CoEn), as a surrogate for neural and synaptic complexity, were extracted in 12 Stargardt macular dystrophy, 12 retinitis pigmentosa (tunnel vision stage), and 14 normally sighted subjects. When compared to controls, both groups with visual loss exhibited decreased CoTks in dorsal area V3d. Peripheral visual field loss also showed a specific CoTks decrease in early visual cortex and ventral area V4, while central visual field loss in dorsal area V3A. Only central visual field loss exhibited increased CoEn in LO-2 area and FG1. Current results revealed biomarkers of brain plasticity within the dorsal and the ventral visual streams following central and peripheral visual field defects.

Rostro-caudal Architecture of the Frontal Lobes in Humans

The nature of the inputs and outputs of a brain region defines its functional specialization. The frontal portion of the brain is essential for goal-directed behaviors, however, the biological basis for its functional organization is unknown. Here, exploring structural connectomic properties, we delineated 12 frontal areas, defined by the pattern of their white matter connections. This result was highly reproducible across neuroimaging centers, acquisition parameters, and participants. These areas corresponded to regions functionally engaged in specific tasks, organized along a rostro-caudal axis from the most complex high-order association areas to the simplest idiotopic areas. The rostro-caudal axis along which the 12 regions were organized also reflected a gradient of cortical thickness, myelination, and cell body density. Importantly, across the identified regions, this gradient of microstructural features was strongly associated with the varying degree of information processing complexity. These new anatomical signatures shed light onto the structural organization of the frontal lobes and could help strengthen the prediction or diagnosis of neurodevelopmental and neurodegenerative disorders.

Detailed T1-Weighted Profiles from the Human Cortex Measured in Vivo at 3 Tesla MRI

Studies into cortical thickness in psychiatric diseases based on T1-weighted MRI frequently report on aberrations in the cerebral cortex. Due to limitations in image resolution for studies conducted at conventional MRI field strengths (e.g. 3 Tesla (T)) this information cannot be used to establish which of the cortical layers may be implicated. Here we propose a new analysis method that computes one high-resolution average cortical profile per brain region extracting myeloarchitectural information from T1-weighted MRI scans that are routinely acquired at a conventional field strength. To assess this new method, we acquired standard T1-weighted scans at 3 T and compared them with state-of-the-art ultra-high resolution T1-weighted scans optimised for intracortical myelin contrast acquired at 7 T. Average cortical profiles were computed for seven different brain regions. Besides a qualitative comparison between the 3 T scans, 7 T scans, and results from literature, we tested if the results from dynamic time warping-based clustering are similar for the cortical profiles computed from 7 T and 3 T data. In addition, we quantitatively compared cortical profiles computed for V1, V2 and V7 for both 7 T and 3 T data using a priori information on their relative myelin concentration. Although qualitative comparisons show that at an individual level average profiles computed for 7 T have more pronounced features than 3 T profiles the results from the quantitative analyses suggest that average cortical profiles computed from T1-weighted scans acquired at 3 T indeed contain myeloarchitectural information similar to profiles computed from the scans acquired at 7 T. The proposed method therefore provides a step forward to study cortical myeloarchitecture in vivo at conventional magnetic field strength both in health and disease.

The impact of B1+ correction on MP2RAGE cortical T1 and apparent cortical thickness at 7T

Determination of cortical thickness using MRI has often been criticized due to the presence of various error sources. Specifically, anatomical MRI relying on T₁ contrast may be unreliable due to spatially variable image contrast between gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF). Especially at ultra‐high field (≥ 7T) MRI, transmit and receive B₁‐related image inhomogeneities can hamper correct classification of tissue types. In the current paper, we demonstrate that residual B1+ (transmit) inhomogeneities in the T₁‐weighted and quantitative T₁ images using the MP2RAGE sequence at 7T lead to biases in cortical thickness measurements. As expected, post‐hoc correction for the spatially varying B1+ profile reduced the apparent T₁ values across the cortex in regions with low B1+, and slightly increased apparent T₁ in regions with high B1+. As a result, improved contrast‐to‐noise ratio both at the GM‐CSF and GM‐WM boundaries can be observed leading to more accurate surface reconstructions and cortical thickness estimates. Overall, the changes in cortical thickness ranged between a 5% decrease to a 70% increase after B1+ correction, reducing the variance of cortical thickness values across the brain dramatically and increasing the comparability with normative data. More specifically, the cortical thickness estimates increased in regions characterized by a strong decrease of apparent T₁ after B1+ correction in regions with low B1+ due to improved detection of the pial surface_. The current results suggest that cortical thickness can be more accurately determined using MP2RAGE data at 7T if B1+ inhomogeneities are accounted for.

Uniformity and Deviation of Intra-axonal Cross-sectional Area Coverage of the Gray-to-White Matter Interface

Diffusion magnetic resonance imaging (dMRI) is a compelling tool for investigating the structure and geometry of brain tissue based on indirect measurement of the diffusion anisotropy of water. Recent developments in global top-down tractogram optimizations enable the estimation of streamline weights, which characterize the connection between gray matter areas. In this work, the intra-axonal cross-sectional area coverage of the gray-to-white matter interface was examined by intersecting tractography streamlines with cortical regions of interest. The area coverage is the ratio of streamline weights divided by the surface area at the gray-to-white matter interface and assesses the estimated percentage which is covered by intra-axonal space. A high correlation (r = 0.935) between streamline weights and the cortical surface area was found across all regions of interest in all subjects. The variance across different cortical regions exhibits similarities to myelin maps. Additionally, we examined the effect of different diffusion gradient subsets at a lower, clinically feasible spatial resolution. Subsampling of the initial high-resolution diffusion dataset did not alter the tendency of the area coverage at the gray-to-white matter interface across cortical areas and subjects. However, single-shell acquisition schemes with lower b-values lead to a steady increase in area coverage in comparison to the full acquisition scheme at high resolution.