Receptor mapping: architecture of the human cerebral cortex

Multimodal mapping of macaque monkey somatosensory cortex

The somatosensory cortex is a brain region responsible for receiving and processing sensory information from across the body and is structurally and functionally heterogeneous. Since the chemoarchitectonic segregation of the cerebral cortex can be revealed by transmitter receptor distribution patterns, by using a quantitative multireceptor architectonical analysis, we determined the number and extent of distinct areas of the macaque somatosensory cortex. We identified three architectonically distinct cortical entities within the primary somatosensory cortex (i.e., 3bm, 3bli, 3ble), four within the anterior parietal cortex (i.e., 3am, 3al, 1 and 2) and six subdivisions (i.e., S2l, S2m, PVl, PVm, PRl and PRm) within the lateral fissure. We provide an ultra-high resolution 3D atlas of macaque somatosensory areas in stereotaxic space, which integrates cyto- and receptor architectonic features of identified areas. Multivariate analyses of the receptor fingerprints revealed four clusters of identified areas based on the degree of (dis)similarity of their receptor architecture. Each of these clusters can be associated with distinct levels of somatosensory processing, further demonstrating that the functional segregation of cortical areas is underpinned by differences in their molecular organization.

InSpectro-Gadget: A Tool for Estimating Neurotransmitter and Neuromodulator Receptor Distributions for MRS Voxels

Magnetic resonance spectroscopy (MRS) is widely used to estimate concentrations of glutamate and γ -aminobutyric acid (GABA) in specific regions of the living human brain. As cytoarchitectural properties differ across the brain, interpreting these measurements can be assisted by having knowledge of such properties for the MRS region(s) studied. In particular, some knowledge of likely local neurotransmitter receptor patterns can potentially give insights into the mechanistic environment GABA- and glutamatergic neurons are functioning in. This may be of particular utility when comparing two or more regions, given that the receptor populations may differ substantially across them. At the same time, when studying MRS data from multiple participants or timepoints, the homogeneity of the sample becomes relevant, as measurements taken from areas with different cytoarchitecture may be difficult to compare. To provide insights into the likely cytoarchitectural environment of user-defined regions-of-interest, we produced an easy to use tool - InSpectro-Gadget - that interfaces with receptor mRNA expression information from the Allen Human Brain Atlas. This Python tool allows users to input masks and automatically obtain a graphical overview of the receptor population likely to be found within. This includes comparison between multiple masks or participants where relevant. The receptors and receptor subunit genes featured include GABA- and glutamatergic classes, along with a wide range of neuromodulators. The functionality of the tool is explained here and its use is demonstrated through a set of example analyses. The tool is available at https://github.com/lizmcmanus/Inspectro-Gadget .

Analyzing the cortical fine structure as revealed by ex-vivo anatomical MRI

The human cortex has a rich fiber structure as revealed by myelin-staining of histological slices. Myelin also contributes to the image contrast in Magnetic Resonance Imaging (MRI). Recent advances in Magnetic Resonance (MR) scanner and imaging technology allowed the acquisition of an ex-vivo data set at an isotropic resolution of 100 µm. This study focused on a computational analysis of this data set with the aim of bridging between histological knowledge and MRI-based results. This work highlights: (1) the design and implementation of a processing chain that extracts intracortical features from a high-resolution MR image; (2) a demonstration of the correspondence between MRI-based cortical intensity profiles and the myelo-architectonic layering of the cortex; (3) the characterization and classification of four basic myelo-architectonic profile types; (4) the distinction of cortical regions based on myelo-architectonic features; and (5) the segmentation of cortical modules in the entorhinal cortex.

Cytoarchitectonic, receptor distribution and functional connectivity analyses of the macaque frontal lobe

Based on quantitative cyto- and receptor architectonic analyses, we identified 35 prefrontal areas, including novel subdivisions of Walker's areas 10, 9, 8B, and 46. Statistical analysis of receptor densities revealed regional differences in lateral and ventrolateral prefrontal cortex. Indeed, structural and functional organization of subdivisions encompassing areas 46 and 12 demonstrated significant differences in the interareal levels of α2 receptors. Furthermore, multivariate analysis included receptor fingerprints of previously identified 16 motor areas in the same macaque brains and revealed 5 clusters encompassing frontal lobe areas. We used the MRI datasets from the non-human primate data sharing consortium PRIME-DE to perform functional connectivity analyses using the resulting frontal maps as seed regions. In general, rostrally located frontal areas were characterized by bigger fingerprints, that is, higher receptor densities, and stronger regional interconnections. Whereas more caudal areas had smaller fingerprints, but showed a widespread connectivity pattern with distant cortical regions. Taken together, this study provides a comprehensive insight into the molecular structure underlying the functional organization of the cortex and, thus, reconcile the discrepancies between the structural and functional hierarchical organization of the primate frontal lobe. Finally, our data are publicly available via the EBRAINS and BALSA repositories for the entire scientific community.

A new 3D myeloarchitectonic map of the human neocortex based on data from the Vogt-Vogt school

During the period extending from 1900 to 1970, Oskar and Cécile Vogt and their numerous collaborators ('the Vogt-Vogt school') published a large number of studies on the myeloarchitecture of the human cerebral cortex. During the last decade, we have concerned ourselves with a detailed meta-analysis of these now almost totally forgotten studies, with the aim to bringing them into the modern era of science. This scrutiny yielded inter alia a myeloarchitectonic map of the human neocortex, showing a parcellation into 182 areas (Nieuwenhuys et al. in Brain Struct Funct 220:2551-2573, 2015; Erratum in Brain Struct Funct 220: 3753-3755, 2015). This map, termed 2D'15, which is based on data derived from all of the 20 publications constituting the myeloarchitectonic legacy of the Vogt-Vogt school, has the limitation that it is two-dimensional i.e. it shows only the parts of the cortex exposed at the free surface of the cerebral hemispheres and not the extensive stretches of cortex hidden in the cortical sulci. However, a limited set of data, derived from four of the 20 publications available, has enabled us to create a 3D map, showing the myeloarchitectonic parcellation of the entire human neocortex. This map, designated as 3D'23, contains 182 areas: 64 frontal, 30 parietal, 6 insular, 19 occipital and 63 temporal. We have also prepared a 2D version (2D'23), of this 3D'23 map to serve as a link between the latter and our original 2D'15 map. Detailed comparison of the parcellations visualized in our three maps (2D'15, 2D'23 and 3D'23) warrants the conclusion that our new 3D'23 map may be considered as representative for the entire myeloarchitectural legacy of the Vogt-Vogt School. Hence it is now possible to compare the rich amount of myeloarchitectonic data assembled by that school directly with the results of current 3D analyses of the architecture of the human cortex, such as the meticulous quantitative cyto- and receptor architectonic studies of Zilles, Amunts and their numerous associates (Amunts et al. in Science 369:988-992, 2020), and the multimodal parcellation of the human cortex based on magnetic resonance images from the Human Connectome Project, performed by Glasser et al. in Nature 536:171-178, 2016).

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.

A whole-brain 3D myeloarchitectonic atlas: Mapping the Vogt-Vogt legacy to the cortical surface

Building precise and detailed parcellations of anatomically and functionally distinct brain areas has been a major focus in Neuroscience. Pioneer anatomists parcellated the cortical manifold based on extensive histological studies of post-mortem brain, harnessing local variations in cortical cyto- and myeloarchitecture to define areal boundaries. Compared to the cytoarchitectonic field, where multiple neuroimaging studies have recently translated this old legacy data into useful analytical resources, myeloarchitectonics, which parcellate the cortex based on the organization of myelinated fibers, has received less attention. Here, we present the neocortical surface-based myeloarchitectonic atlas based on the histology-derived maps of the Vogt-Vogt school and its 2D translation by Nieuwenhuys. In addition to a myeloarchitectonic parcellation, our package includes intracortical laminar profiles of myelin content based on Vogt-Vogt-Hopf original publications. Histology-derived myelin density mapped on our atlas demonstrated a close overlap with in vivo quantitative MRI markers for myelin and relates to cytoarchitectural features. Complementing the existing battery of approaches for digital cartography, the whole-brain myeloarchitectonic atlas offers an opportunity to validate imaging surrogate markers of myelin in both health and disease.

Prediction of Obsessive-Compulsive Disorder: Importance of Neurobiology-Aided Feature Design and Cross-Diagnosis Transfer Learning

BACKGROUND

Machine learning applications using neuroimaging provide a multidimensional, data-driven approach that captures the level of complexity necessary for objectively aiding diagnosis and prognosis in psychiatry. However, models learned from small training samples often have limited generalizability, which continues to be a problem with automated diagnosis of mental illnesses such as obsessive-compulsive disorder (OCD). Earlier studies have shown that features incorporating prior neurobiological knowledge of brain function and combining brain parcellations from various sources can potentially improve the overall prediction. However, it is unknown whether such knowledge-driven methods can provide a performance that is comparable to state-of-the-art approaches based on neural networks.

METHODS

In this study, we apply a transparent and explainable multiparcellation ensemble learning framework EMPaSchiz (Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction) to the task of predicting OCD, based on a resting-state functional magnetic resonance imaging dataset of 350 subjects. Furthermore, we apply transfer learning using the features found effective for schizophrenia to OCD to leverage the commonality in brain alterations across these psychiatric diagnoses.

RESULTS

We show that our knowledge-based approach leads to a prediction performance of 80.3% accuracy for OCD diagnosis that is better than domain-agnostic and automated feature design using neural networks. Furthermore, we show that a selection of reduced feature sets can be transferred from schizophrenia to the OCD prediction model without significant loss in prediction performance.

CONCLUSIONS

This study presents a machine learning framework for OCD prediction with neurobiology-aided feature design using resting-state functional magnetic resonance imaging that is generalizable and reasonably interpretable.

Combined analysis of cytoarchitectonic, molecular and transcriptomic patterns reveal differences in brain organization across human functional brain systems

Brain areas show specific cellular, molecular, and gene expression patterns that are linked to function, but their precise relationships are largely unknown. To unravel these structure-function relationships, a combined analysis of 53 neurotransmitter receptor genes, receptor densities of six transmitter systems and cytoarchitectonic data of the auditory, somatosensory, visual, motor systems was conducted. Besides covariation of areal gene expression with receptor density, the study reveals specific gene expression patterns in functional systems, which are most prominent for the inhibitory GABA_A and excitatory glutamatergic NMDA receptors. Furthermore, gene expression-receptor relationships changed in a systematic manner according to information flow from primary to higher associative areas. The findings shed new light on the relationship of anatomical, functional, and molecular and transcriptomic principles of cortical segregation towards a more comprehensive understanding of human brain organization.

Behavioral Training Related Neurotransmitter Receptor Expression Dynamics in the Nidopallium Caudolaterale and the Hippocampal Formation of Pigeons

Learning and memory are linked to dynamic changes at the level of synapses in brain areas that are involved in cognitive tasks. For example, changes in neurotransmitter receptors are prerequisite for tuning signals along local circuits and long-range networks. However, it is still unclear how a series of learning events promotes plasticity within the system of neurotransmitter receptors and their subunits to shape information processing at the neuronal level. Therefore, we investigated the expression of different glutamatergic NMDA (GRIN) and AMPA (GRIA) receptor subunits, the GABAergic GABARG2 subunit, dopaminergic DRD1, serotonergic 5HTR1A and noradrenergic ADRA1A receptors in the pigeon’s brain. We studied the nidopallium caudolaterale, the avian analogue of the prefrontal cortex, and the hippocampal formation, after training the birds in a rewarded stimulus-response association (SR) task and in a simultaneous-matching-to-sample (SMTS) task. The results show that receptor expression changed differentially after behavioral training compared to an untrained control group. In the nidopallium caudolaterale, GRIN2B, GRIA3, GRIA4, DRD1D, and ADRA1A receptor expression was altered after SR training and remained constantly decreased after the SMTS training protocol, while GRIA2 and DRD1A decreased only under the SR condition. In the hippocampal formation, GRIN2B decreased and GABARG2 receptor expression increased after SR training. After SMTS sessions, GRIN2B remained decreased, GABARG2 remained increased if compared to the control group. None of the investigated receptors differed directly between both conditions, although differentially altered. The changes in both regions mostly occur in favor of the stimulus response task. Thus, the present data provide evidence that neurotransmitter receptor expression dynamics play a role in the avian prefrontal cortex and the hippocampal formation for behavioral training and is uniquely, regionally and functionally associated to cognitive processes including learning and memory.

Linking Brain Structure, Activity, and Cognitive Function through Computation

Understanding the human brain is a “Grand Challenge” for 21st century research. Computational approaches enable large and complex datasets to be addressed efficiently, supported by artificial neural networks, modeling and simulation. Dynamic generative multiscale models, which enable the investigation of causation across scales and are guided by principles and theories of brain function, are instrumental for linking brain structure and function. An example of a resource enabling such an integrated approach to neuroscientific discovery is the BigBrain, which spatially anchors tissue models and data across different scales and ensures that multiscale models are supported by the data, making the bridge to both basic neuroscience and medicine. Research at the intersection of neuroscience, computing and robotics has the potential to advance neuro-inspired technologies by taking advantage of a growing body of insights into perception, plasticity and learning. To render data, tools and methods, theories, basic principles and concepts interoperable, the Human Brain Project (HBP) has launched EBRAINS, a digital neuroscience research infrastructure, which brings together a transdisciplinary community of researchers united by the quest to understand the brain, with fascinating insights and perspectives for societal benefits.

A sub+cortical fMRI-based surface parcellation

Both cortical and subcortical structures are organized into a large number of distinct areas reflecting functional and cytoarchitectonic differences. Mapping these areas is of fundamental importance to neuroscience. A central obstacle to this task is the inaccuracy associated with bringing results from individuals into a common space. The vast individual differences in morphology pose a serious problem for volumetric registration. Surface‐based approaches fare substantially better, but have thus far been used only for cortical parcellation, leaving subcortical parcellation in volumetric space. We extend the surface‐based approach to include also the subcortical deep gray‐matter structures, thus achieving a uniform representation across both cortex and subcortex, suitable for use with surface‐based metrics that span these structures, for example, white/gray contrast. Using data from the Enhanced Nathan Klein Institute—Rockland Sample, limited to individuals between 19 and 69 years of age, we generate a functional parcellation of both the cortical and subcortical surfaces. To assess this extended parcellation, we show that (a) our parcellation provides greater homogeneity of functional connectivity patterns than do arbitrary parcellations matching in the number and size of parcels; (b) our parcels align with known cortical and subcortical architecture; and (c) our extended functional parcellation provides an improved fit to the complexity of life‐span (6–85 years) changes in white/gray contrast data compared to arbitrary parcellations matching in the number and size of parcels, supporting its use with surface‐based measures. We provide our extended functional parcellation for the use of the neuroimaging community.

Current and Future Challenges of Functional MRI and Diffusion Tractography in the Surgical Setting: From Eloquent Brain Mapping to Neural Plasticity

Decades ago, Spetzler (1986) and Sawaya (1998) provided a rough brain segmentation of the eloquent areas of the brain, aimed to help surgical decisions in cases of vascular malformations and tumors, respectively. Currently in clinical use, their criteria are in need of revision. Defining functions (eg, sensorimotor, language and visual) that should be preserved during surgery seems a straightforward task. In practice, locating the specific areas that could cause a permanent vs transient deficit is not an easy task. This is particularly true for the associative cortex and cognitive domains such as language. The old model, with Broca's and Wernicke's areas at the forefront, has been superseded by a dual-stream model of parallel language processing; named ventral and dorsal pathways. This complicated network of cortical hubs and subcortical white matter pathways needing preservation during surgery is a work in progress. Preserving not only cortical regions but most importantly preserving the connections, or white matter fiber bundles, of core regions in the brain is the new paradigm. For instance, the arcuate fascicululs and inferior fronto-occipital fasciculus are key components of the dorsal and ventral language pathways, respectively; and their damage result in permanent language deficits. Interestedly, the damage of the temporal portions of these bundles -where there is a crossroad with other multiple bundles-, appears to be more important (permanent) than the damage of the frontal portions - where plasticity and contralateral activation could help. Although intraoperative direct cortical and subcortical stimulation have contributed largely, advanced MR techniques such as functional MRI (fMRI) and diffusion tractography (DT), are at the epi-center of our current understanding. Nevertheless, these techniques posse important challenges: such as neurovascular uncoupling or venous bias on fMRI; and appropriate anatomical validation or accurate representation of crossing fibers on DT. These limitations should be well understood and taken into account in clinical practice. Unifying multidisciplinary research and clinical efforts is desirable, so these techniques could contribute more efficiently not only to locate eloquent areas but to improve outcomes and our understanding of neural plasticity. Finally, although there are constant anatomical and functional regions at the individual level, there is a known variability at the inter-individual level. This concept should strengthen the importance of a personalized approach when evaluating these regions on fMRI and DT. It should strengthen the importance of personalized treatments as well, aimed to meet tailored needs and expectations.

Broca's area and the search for anatomical asymmetry: commentary and perspectives

We present a brief commentary on the field's search for an anatomical asymmetry between Broca's area and its homologue in the non-dominant hemisphere, focusing on a selection of studies, including research from the last decade. We demonstrate that, several years after the influential review of Keller and colleagues from 2009, and despite recent advances in neuroimaging, the existence of a structural asymmetry of Broca's area is still controversial. This is especially the case for studies of the macroanatomy of this region. We point out the inconsistencies in methodology across studies that could account for the discrepancy in results. Investigations of the microstructure of Broca's area show a trend of a leftward asymmetry, but it is still unclear how these results relate to language dominance. We suggest that it may be necessary to combine multiple metrics in a systematic manner to find robust asymmetries and to expand the regional scope of structural investigations. Finally, based on the current state of the literature, we should not rule out the possibility that language dominance may simply not be reflected in local anatomical differences in the brain.

The natural axis of transmitter receptor distribution in the human cerebral cortex

Communication between cells in the brain relies on different types of transmitter receptors. Can we uncover organizational principles that harness the diversity of such signatures across the brain? We focus on the human cerebral cortex and demonstrate that the distribution of receptors forms a natural axis that stretches from association to sensory areas. Moreover, traversing this axis entails changes in the diversity, excitability, and mirrored density that reflect a basic division in receptor types, that is, ionotropic and metabotropic receptors. The unraveled principles offer explanatory depth for diverse phenomena and entail concrete, testable predictions.

Transmitter receptors constitute a key component of the molecular machinery for intercellular communication in the brain. Recent efforts have mapped the density of diverse transmitter receptors across the human cerebral cortex with an unprecedented level of detail. Here, we distill these observations into key organizational principles. We demonstrate that receptor densities form a natural axis in the human cerebral cortex, reflecting decreases in differentiation at the level of laminar organization and a sensory-to-association axis at the functional level. Along this natural axis, key organizational principles are discerned: progressive molecular diversity (increase of the diversity of receptor density); excitation/inhibition (increase of the ratio of excitatory-to-inhibitory receptor density); and mirrored, orderly changes of the density of ionotropic and metabotropic receptors. The uncovered natural axis formed by the distribution of receptors aligns with the axis that is formed by other dimensions of cortical organization, such as the myelo- and cytoarchitectonic levels. Therefore, the uncovered natural axis constitutes a unifying organizational feature linking multiple dimensions of the cerebral cortex, thus bringing order to the heterogeneity of cortical organization.

Organization of the macaque monkey inferior parietal lobule based on multimodal receptor architectonics

The macaque monkey inferior parietal lobe (IPL) is a structurally heterogeneous brain region, although the number of areas it contains and the anatomical/functional relationship of identified subdivisions remains controversial. Neurotransmitter receptor distribution patterns not only reveal the position of the cortical borders, but also segregate areas associated to different functional systems. Thus we carried out a multimodal quantitative analysis of the cyto- and receptor architecture of the macaque IPL to determine the number and extent of distinct areas it encompasses. We identified four areas on the IPL convexity arranged in a caudo-rostral sequence, as well as two areas in the parietal operculum, which we projected onto the Yerkes19 surface. We found rostral areas to have relatively smaller receptor fingerprints than the caudal ones, which is in an agreement with the functional gradient along the caudo-rostral axis described in previous studies. The hierarchical analysis segregated IPL areas into two clusters: the caudal one, contains areas involved in multisensory integration and visual-motor functions, and rostral cluster, encompasses areas active during motor planning and action-related functions. The results of the present study provide novel insights into clarifying the homologies between human and macaque IPL areas. The ensuing 3D map of the macaque IPL, and the receptor fingerprints are made publicly available to the neuroscientific community via the Human Brain Project and BALSA repositories for future cyto- and/or receptor architectonically driven analyses of functional imaging studies in non-human primates.

Comparing spatial null models for brain maps

Technological and data sharing advances have led to a proliferation of high-resolution structural and functional maps of the brain. Modern neuroimaging research increasingly depends on identifying correspondences between the topographies of these maps; however, most standard methods for statistical inference fail to account for their spatial properties. Recently, multiple methods have been developed to generate null distributions that preserve the spatial autocorrelation of brain maps and yield more accurate statistical estimates. Here, we comprehensively assess the performance of ten published null frameworks in statistical analyses of neuroimaging data. To test the efficacy of these frameworks in situations with a known ground truth, we first apply them to a series of controlled simulations and examine the impact of data resolution and spatial autocorrelation on their family-wise error rates. Next, we use each framework with two empirical neuroimaging datasets, investigating their performance when testing (1) the correspondence between brain maps (e.g., correlating two activation maps) and (2) the spatial distribution of a feature within a partition (e.g., quantifying the specificity of an activation map within an intrinsic functional network). Finally, we investigate how differences in the implementation of these null models may impact their performance. In agreement with previous reports, we find that naive null models that do not preserve spatial autocorrelation consistently yield elevated false positive rates and unrealistically liberal statistical estimates. While spatially-constrained null models yielded more realistic, conservative estimates, even these frameworks suffer from inflated false positive rates and variable performance across analyses. Throughout our results, we observe minimal impact of parcellation and resolution on null model performance. Altogether, our findings highlight the need for continued development of statistically-rigorous methods for comparing brain maps. The present report provides a harmonised framework for benchmarking and comparing future advancements.

The nonhuman primate neuroimaging and neuroanatomy project

Multi-modal neuroimaging projects such as the Human Connectome Project (HCP) and UK Biobank are advancing our understanding of human brain architecture, function, connectivity, and their variability across individuals using high-quality non-invasive data from many subjects. Such efforts depend upon the accuracy of non-invasive brain imaging measures. However, 'ground truth' validation of connectivity using invasive tracers is not feasible in humans. Studies using nonhuman primates (NHPs) enable comparisons between invasive and non-invasive measures, including exploration of how "functional connectivity" from fMRI and "tractographic connectivity" from diffusion MRI compare with long-distance connections measured using tract tracing. Our NonHuman Primate Neuroimaging & Neuroanatomy Project (NHP_NNP) is an international effort (6 laboratories in 5 countries) to: (i) acquire and analyze high-quality multi-modal brain imaging data of macaque and marmoset monkeys using protocols and methods adapted from the HCP; (ii) acquire quantitative invasive tract-tracing data for cortical and subcortical projections to cortical areas; and (iii) map the distributions of different brain cell types with immunocytochemical stains to better define brain areal boundaries. We are acquiring high-resolution structural, functional, and diffusion MRI data together with behavioral measures from over 100 individual macaques and marmosets in order to generate non-invasive measures of brain architecture such as myelin and cortical thickness maps, as well as functional and diffusion tractography-based connectomes. We are using classical and next-generation anatomical tracers to generate quantitative connectivity maps based on brain-wide counting of labeled cortical and subcortical neurons, providing ground truth measures of connectivity. Advanced statistical modeling techniques address the consistency of both kinds of data across individuals, allowing comparison of tracer-based and non-invasive MRI-based connectivity measures. We aim to develop improved cortical and subcortical areal atlases by combining histological and imaging methods. Finally, we are collecting genetic and sociality-associated behavioral data in all animals in an effort to understand how genetic variation shapes the connectome and behavior.

A detailed comparison of the cytoarchitectonic and myeloarchitectonic maps of the human neocortex produced by the Vogt-Vogt school

The comprehensive research programme of the Vogt-Vogt (V-V) school, which was active during the period 1900-1970, included detailed cytoarchitectonic and myeloarchitectonic analyses of the human cerebral cortex, with the aim to integrate the data obtained into a map, showing a parcellation of the human cerebral cortex into fundamental structural and potentially functional units. The cytoarchitectonic V-V analyses yielded two maps of the human cerebral cortex, the famous map of Brodmann (Vergleichende Lokalisationslehre der Grosshirnrinde in ihren Prinzipien dargestellt auf Grund des Zellenbaues. Barth, Leipzig, 1909), Brodmann (in: Bruns P (ed) Neue deutsche Chirurgie, Enke, Stuttgart, 1914), and the less known, but more detailed map of Sarkisov et al. (Cytoarchitecture of the human cortex cerebri. Medgiz, Moscow, 1949). Sarkisov et al. used in their cytoarchitectonic parcellation of the cortex the same numbering scheme as Brodmann. They confirmed the presence of most of the areas delineated by the latter, but they subdivided several of these areas into two or more separate areas or subareas. Within the realm of the myeloarchitectonic V-V analyses, numerous meticulous studies of the cortex of individual cerebral lobes were carried out, but these were not united into a single map. Consequently, the envisioned integration of cytoarchitectonic and myeloarchitectonic data mentioned above was never realized. Some years ago, we (Nieuwenhuys et al. in Brain Struct Funct 220:2551-2573, 2015a, Nieuwenhuys et al. in Brain Struct Funct 220:3753-3755, 2015b) reanalyzed the V-V myeloarchitectonic data, and succeeded in constructing a complete myeloarchitectonic map of the human neocortex from these data. Because the data provided by the V-V school were derived from many different brains, a standard brain had to be introduced as a template to which all data available could be transferred. As such the MNI305 template was selected. Having made available now the cytoarchitectonic maps of Brodmann and Sarkisov et al. and the recently prepared myeloarchitectonic map, an attempt is made here to realize at last the original aim of the V-V school, viz. the preparation of a single, combined (cyto + myelo) architectonic map of the human cortex. To this end, the following three steps have been made. First, Brodmann's (BR) map, and the map of Sarkisov et al. (SA) were harmoniously transferred to the same template brain as the one used during the construction of our myeloarchitectonic map. Second, the standardized BR and our myeloarchitectonic (NI) map were compared, and the data contained within these maps were integrated into a single standardized combined BR-NI map (Fig. 11). The standardized SA and NI maps were subjected to the same procedure (Fig. 12). Finally, the standardized combined BR-NI and SA-NI maps were united into a single combined BR-SA-NI map (Fig. 13). This map renders it possible to make direct comparisons between the results of the architectonic studies of the V-V school and current parcellations of the human neocortex.

Receptor-driven, multimodal mapping of cortical areas in the macaque monkey intraparietal sulcus

The intraparietal sulcus (IPS) is structurally and functionally heterogeneous. We performed a quantitative cyto-/myelo- and receptor architectonical analysis to provide a multimodal map of the macaque IPS. We identified 17 cortical areas, including novel areas PEipe, PEipi (external and internal subdivisions of PEip), and MIPd. Multivariate analyses of receptor densities resulted in a grouping of areas based on the degree of (dis)similarity of their receptor architecture: a cluster encompassing areas located in the posterior portion of the IPS and associated mainly with the processing of visual information, a cluster including areas found in the anterior portion of the IPS and involved in sensorimotor processing, and an ‘intermediate’ cluster of multimodal association areas. Thus, differences in cyto-/myelo- and receptor architecture segregate the cortical ribbon within the IPS, and receptor fingerprints provide novel insights into the relationship between the structural and functional segregation of this brain region in the macaque monkey.

Brainstem Modulation of Large-Scale Intrinsic Cortical Activity Correlations

Brain activity fluctuates continuously, even in the absence of changes in sensory input or motor output. These intrinsic activity fluctuations are correlated across brain regions and are spatially organized in macroscale networks. Variations in the strength, topography, and topology of correlated activity occur over time, and unfold upon a backbone of long-range anatomical connections. Subcortical neuromodulatory systems send widespread ascending projections to the cortex, and are thus ideally situated to shape the temporal and spatial structure of intrinsic correlations. These systems are also the targets of the pharmacological treatment of major neurological and psychiatric disorders, such as Parkinson's disease, depression, and schizophrenia. Here, we review recent work that has investigated how neuromodulatory systems shape correlations of intrinsic fluctuations of large-scale cortical activity. We discuss studies in the human, monkey, and rodent brain, with a focus on non-invasive recordings of human brain activity. We provide a structured but selective overview of this work and distil a number of emerging principles. Future efforts to chart the effect of specific neuromodulators and, in particular, specific receptors, on intrinsic correlations may help identify shared or antagonistic principles between different neuromodulatory systems. Such principles can inform models of healthy brain function and may provide an important reference for understanding altered cortical dynamics that are evident in neurological and psychiatric disorders, potentially paving the way for mechanistically inspired biomarkers and individualized treatments of these disorders.

Systems Underlying Human and Old World Monkey Communication: One, Two, or Infinite

Using artificially synthesized stimuli, previous research has shown that cotton-top tamarin monkeys easily learn simple AB grammar sequences, but not the more complex AnBn sequences that require hierarchical structure. Humans have no trouble learning AnBn combinations. A more recent study, using similar artificially created stimuli, showed that there is a neuroanatomical difference in the brain between these two kinds of arrays. While the simpler AB sequences recruit the frontal operculum, the AnBn array recruits the phylogenetically newer Broca's area. We propose that on close inspection, reported vocal repertoires of Old World Monkeys show that these nonhuman primates are capable of calls that have two items in them, but never more than two. These are simple AB sequences, as predicted by previous research. In addition, we suggest the two-item call cannot be the result of a combinatorial operation that we see in human language, where the recursive operation of Merge allows for a potentially infinite array of structures. In our view, the two-item calls of nonhuman primates result from a dual-compartment frame into which each of the calls can fit without having to be combined by an operation such as Merge.

Fetal cortical surface atlas parcellation based on growth patterns

Defining anatomically and functionally meaningful parcellation maps on cortical surface atlases is of great importance in surface-based neuroimaging analysis. The conventional cortical parcellation maps are typically defined based on anatomical cortical folding landmarks in adult surface atlases. However, they are not suitable for fetal brain studies, due to dramatic differences in brain size, shape, and properties between adults and fetuses. To address this issue, we propose a novel data-driven method for parcellation of fetal cortical surface atlases into distinct regions based on the dynamic "growth patterns" of cortical properties (e.g., surface area) from a population of fetuses. Our motivation is that the growth patterns of cortical properties indicate the underlying rapid changes of microstructures, which determine the molecular and functional principles of the cortex. Thus, growth patterns are well suitable for defining distinct cortical regions in development, structure, and function. To comprehensively capture the similarities of cortical growth patterns among vertices, we construct two complementary similarity matrices. One is directly based on the growth trajectories of vertices, and the other is based on the correlation profiles of vertices' growth trajectories in relation to a set of reference points. Then, we nonlinearly fuse these two similarity matrices into a single one, which can better capture both their common and complementary information than by simply averaging them. Finally, based on this fused similarity matrix, we perform spectral clustering to divide the fetal cortical surface atlases into distinct regions. By applying our method on 25 normal fetuses from 26 to 29 gestational weeks, we construct age-specific fetal cortical surface atlases equipped with biologically meaningful parcellation maps based on cortical growth patterns. Importantly, our generated parcellation maps reveal spatially contiguous, hierarchical and bilaterally relatively symmetric patterns of fetal cortical surface development.

Leveraging heterogeneity for neural computation with fading memory in layer 2/3 cortical microcircuits

Complexity and heterogeneity are intrinsic to neurobiological systems, manifest in every process, at every scale, and are inextricably linked to the systems' emergent collective behaviours and function. However, the majority of studies addressing the dynamics and computational properties of biologically inspired cortical microcircuits tend to assume (often for the sake of analytical tractability) a great degree of homogeneity in both neuronal and synaptic/connectivity parameters. While simplification and reductionism are necessary to understand the brain's functional principles, disregarding the existence of the multiple heterogeneities in the cortical composition, which may be at the core of its computational proficiency, will inevitably fail to account for important phenomena and limit the scope and generalizability of cortical models. We address these issues by studying the individual and composite functional roles of heterogeneities in neuronal, synaptic and structural properties in a biophysically plausible layer 2/3 microcircuit model, built and constrained by multiple sources of empirical data. This approach was made possible by the emergence of large-scale, well curated databases, as well as the substantial improvements in experimental methodologies achieved over the last few years. Our results show that variability in single neuron parameters is the dominant source of functional specialization, leading to highly proficient microcircuits with much higher computational power than their homogeneous counterparts. We further show that fully heterogeneous circuits, which are closest to the biophysical reality, owe their response properties to the differential contribution of different sources of heterogeneity.

Neuron density fundamentally relates to architecture and connectivity of the primate cerebral cortex

Studies of structural brain connectivity have revealed many intriguing features of complex cortical networks. To advance integrative theories of cortical organization, an understanding is required of how connectivity interrelates with other aspects of brain structure. Recent studies have suggested that interareal connectivity may be related to a variety of macroscopic as well as microscopic architectonic features of cortical areas. However, it is unclear how these features are inter-dependent and which of them most strongly and fundamentally relate to structural corticocortical connectivity. Here, we systematically investigated the relation of a range of microscopic and macroscopic architectonic features of cortical organization, namely layer III pyramidal cell soma cross section, dendritic synapse count, dendritic synapse density and dendritic tree size as well as area neuron density, to multiple properties of cortical connectivity, using a comprehensive, up-to-date structural connectome of the primate brain. Importantly, relationships were investigated by multi-variate analyses to account for the interrelations of features. Of all considered factors, the classical architectonic parameter of neuron density most strongly and consistently related to essential features of cortical connectivity (existence and laminar patterns of projections, area degree), and in conjoint analyses largely abolished effects of cellular morphological features. These results confirm neuron density as a central architectonic indicator of the primate cerebral cortex that is closely related to essential aspects of brain connectivity and is also highly indicative of further features of the architectonic organization of cortical areas, such as the considered cellular morphological measures. Our findings integrate several aspects of cortical micro- and macroscopic organization, with implications for cortical development and function.

Towards artificial intelligence in mental health by improving schizophrenia prediction with multiple brain parcellation ensemble-learning

In the literature, there are substantial machine learning attempts to classify schizophrenia based on alterations in resting-state (RS) brain patterns using functional magnetic resonance imaging (fMRI). Most earlier studies modelled patients undergoing treatment, entailing confounding with drug effects on brain activity, and making them less applicable to real-world diagnosis at the point of first medical contact. Further, most studies with classification accuracies >80% are based on small sample datasets, which may be insufficient to capture the heterogeneity of schizophrenia, limiting generalization to unseen cases. In this study, we used RS fMRI data collected from a cohort of antipsychotic drug treatment-naive patients meeting DSM IV criteria for schizophrenia (N = 81) as well as age- and sex-matched healthy controls (N = 93). We present an ensemble model -- EMPaSchiz (read as ‘Emphasis’; standing for ‘Ensemble algorithm with Multiple Parcellations for Schizophrenia prediction’) that stacks predictions from several ‘single-source’ models, each based on features of regional activity and functional connectivity, over a range of different a priori parcellation schemes. EMPaSchiz yielded a classification accuracy of 87% (vs. chance accuracy of 53%), which out-performs earlier machine learning models built for diagnosing schizophrenia using RS fMRI measures modelled on large samples (N > 100). To our knowledge, EMPaSchiz is first to be reported that has been trained and validated exclusively on data from drug-naive patients diagnosed with schizophrenia. The method relies on a single modality of MRI acquisition and can be readily scaled-up without needing to rebuild parcellation maps from incoming training images.

Decreased subregional specificity of the putamen in Parkinson's Disease revealed by dynamic connectivity-derived parcellation

Parkinson's Disease (PD) is associated with decreased ability to perform habitual tasks, relying instead on goal-directed behaviour subserved by different cortical/subcortical circuits, including parts of the putamen. We explored the functional subunits in the putamen in PD using novel dynamic connectivity features derived from resting state fMRI recorded from thirty PD subjects and twenty-eight age-matched healthy controls (HC). Dynamic functional segmentation of the putamina was obtained by determining the correlation between each voxel in each putamen along a moving window and applying a joint temporal clustering algorithm to establish cluster membership of each voxel at each window. Contiguous voxels that had consistent cluster membership across all windows were then considered to be part of a homogeneous functional subunit. As PD subjects robustly had two homogenous clusters in the putamina, we also segmented the putamina in HC into two dynamic clusters for a fair comparison. We then estimated the dynamic connectivity using sliding windowed correlation between the mean signal from the identified homogenous subunits and 56 other predefined cortical and subcortical ROIs. Specifically, the mean dynamic connectivity strength and connectivity deviation were then compared to evaluate subregional differences. HC subjects had significant differences in mean dynamic connectivity and connectivity deviation between the two putaminal subunits. The posterior subunit connected strongly to sensorimotor areas, the cerebellum, as well as the middle frontal gyrus. The anterior subunit had strong mean dynamic connectivity to the nucleus accumbens, hippocampus, amygdala, caudate and cingulate. In contrast, PD subjects had fewer differences in mean dynamic connectivity between subunits, indicating a degradation of subregional specificity. Overall UPDRS III and MoCA scores could be predicted using mean dynamic connectivity strength and connectivity deviation. Side of onset of the disease was also jointly related with functional connectivity features. Our results suggest a robust loss of specificity of mean dynamic connectivity and connectivity deviation in putaminal subunits in PD that is sensitive to disease severity. In addition, altered mean dynamic connectivity and connectivity deviation features in PD suggest that looking at connectivity dynamics offers an additional dimension for assessment of neurodegenerative disorders.

Parcellating Cerebral Cortex: How Invasive Animal Studies Inform Noninvasive Mapmaking in Humans

The cerebral cortex in mammals contains a mosaic of cortical areas that differ in function, architecture, connectivity, and/or topographic organization. A combination of local connectivity (within-area microcircuitry) and long-distance (between-area) connectivity enables each area to perform a unique set of computations. Some areas also have characteristic within-area mesoscale organization, reflecting specialized representations of distinct types of information. Cortical areas interact with one another to form functional networks that mediate behavior, and each area may be a part of multiple, partially overlapping networks. Given their importance to the understanding of brain organization, mapping cortical areas across species is a major objective of systems neuroscience and has been a century-long challenge. Here, we review recent progress in multi-modal mapping of mouse and nonhuman primate cortex, mainly using invasive experimental methods. These studies also provide a neuroanatomical foundation for mapping human cerebral cortex using noninvasive neuroimaging, including a new map of human cortical areas that we generated using a semiautomated analysis of high-quality, multimodal neuroimaging data. We contrast our semiautomated approach to human multimodal cortical mapping with various extant fully automated human brain parcellations that are based on only a single imaging modality and offer suggestions on how to best advance the noninvasive brain parcellation field. We discuss the limitations as well as the strengths of current noninvasive methods of mapping brain function, architecture, connectivity, and topography and of current approaches to mapping the brain's functional networks.

Cyto- and receptor architectonic mapping of the human brain

Mapping of the human brain is more than the generation of an atlas-based parcellation of brain regions using histologic or histochemical criteria. It is the attempt to provide a topographically informed model of the structural and functional organization of the brain. To achieve this goal a multimodal atlas of the detailed microscopic and neurochemical structure of the brain must be registered to a stereotaxic reference space or brain, which also serves as reference for topographic assignment of functional data, e.g., functional magnet resonance imaging, electroencephalography, or magnetoencephalography, as well as metabolic imaging, e.g., positron emission tomography. Although classic maps remain pioneering steps, they do not match recent concepts of the functional organization in many regions, and suffer from methodic drawbacks. This chapter provides a summary of the recent status of human brain mapping, which is based on multimodal approaches integrating results of quantitative cyto- and receptor architectonic studies with focus on the cerebral cortex in a widely used reference brain. Descriptions of the methods for observer-independent and statistically testable cytoarchitectonic parcellations, quantitative multireceptor mapping, and registration to the reference brain, including the concept of probability maps and a toolbox for using the maps in functional neuroimaging studies, are provided.

GABA Levels in Left and Right Sensorimotor Cortex Correlate across Individuals

Differences in γ-aminobutyric acid (GABA) levels measured with Magnetic Resonance Spectroscopy have been shown to correlate with behavioral performance over a number of tasks and cortical regions. These correlations appear to be regionally and functionally specific. In this study, we test the hypothesis that GABA levels will be correlated within individuals for functionally related regions-the left and right sensorimotor cortex. In addition, we investigate whether this is driven by bulk tissue composition. GABA measurements using edited MRS data were acquired from the left and right sensorimotor cortex in 24 participants. T1-weighted MR images were also acquired and segmented to determine the tissue composition of the voxel. GABA level is shown to correlate significantly between the left and right regions (r = 0.64, p < 0.03). Tissue composition is highly correlated between sides, but does not explain significant variance in the bilateral correlation. In conclusion, individual differences in GABA level, which have previously been described as functionally and regionally specific, are correlated between homologous sensorimotor regions. This correlation is not driven by bulk differences in voxel tissue composition.

Amplification and Suppression of Distinct Brainwide Activity Patterns by Catecholamines

The widely projecting catecholaminergic (norepinephrine and dopamine) neurotransmitter systems profoundly shape the state of neuronal networks in the forebrain. Current models posit that the effects of catecholaminergic modulation on network dynamics are homogeneous across the brain. However, the brain is equipped with a variety of catecholamine receptors with distinct functional effects and heterogeneous density across brain regions. Consequently, catecholaminergic effects on brainwide network dynamics might be more spatially specific than assumed. We tested this idea through the analysis of fMRI measurements performed in humans (19 females, 5 males) at “rest” under pharmacological (atomoxetine-induced) elevation of catecholamine levels. We used a linear decomposition technique to identify spatial patterns of correlated fMRI signal fluctuations that were either increased or decreased by atomoxetine. This yielded two distinct spatial patterns, each expressing reliable and specific drug effects. The spatial structure of both fluctuation patterns resembled the spatial distribution of the expression of catecholamine receptor genes: α₁ norepinephrine receptors (for the fluctuation pattern: placebo > atomoxetine), D₂-like dopamine receptors (pattern: atomoxetine > placebo), and β norepinephrine receptors (for both patterns, with correlations of opposite sign). We conclude that catecholaminergic effects on the forebrain are spatially more structured than traditionally assumed and at least in part explained by the heterogeneous distribution of various catecholamine receptors. Our findings link catecholaminergic effects on large-scale brain networks to low-level characteristics of the underlying neurotransmitter systems. They also provide key constraints for the development of realistic models of neuromodulatory effects on large-scale brain network dynamics.

SIGNIFICANCE STATEMENT The catecholamines norepinephrine and dopamine are an important class of modulatory neurotransmitters. Because of the widespread and diffuse release of these neuromodulators, it has commonly been assumed that their effects on neural interactions are homogeneous across the brain. Here, we present results from the human brain that challenge this view. We pharmacologically increased catecholamine levels and imaged the effects on the spontaneous covariations between brainwide fMRI signals at “rest.” We identified two distinct spatial patterns of covariations: one that was amplified and another that was suppressed by catecholamines. Each pattern was associated with the heterogeneous spatial distribution of the expression of distinct catecholamine receptor genes. Our results provide novel insights into the catecholaminergic modulation of large-scale human brain dynamics.

Molecular composition of the human primary visual cortex profiled by multimodal mass spectrometry imaging

The primary visual cortex (area V1) is an extensively studied part of the cerebral cortex with well-characterized connectivity, cellular and molecular architecture and functions (for recent reviews see Amunts and Zilles, Neuron 88:1086-1107, 2015; Casagrande and Xu, Parallel visual pathways: a comparative perspective. The visual neurosciences, MIT Press, Cambridge, pp 494-506, 2004). In humans, V1 is defined by heavily myelinated fibers arriving from the radiatio optica that form the Gennari stripe in cortical layer IV, which is further subdivided into laminae IVa, IVb, IVcα and IVcβ. Due to this unique laminar pattern, V1 represents an excellent region to test whether multimodal mass spectrometric imaging could reveal novel biomolecular markers for a functionally relevant parcellation of the human cerebral cortex. Here we analyzed histological sections of three post-mortem brains with matrix-assisted laser desorption/ionization mass spectrometry imaging and laser ablation inductively coupled plasma mass spectrometry imaging to investigate the distribution of lipids, proteins and metals in human V1. We identified 71 peptides of 13 different proteins by in situ tandem mass spectrometry, of which 5 proteins show a differential laminar distribution pattern revealing the border between V1 and V2. High-accuracy mass measurements identified 123 lipid species, including glycerolipids, glycerophospholipids and sphingolipids, of which at least 20 showed differential distribution within V1 and V2. Specific lipids labeled not only myelinated layer IVb, but also IVa and especially IVc in a layer-specific manner, but also and clearly separated V1 from V2. Elemental imaging further showed a specific accumulation of copper in layer IV. In conclusion, multimodal mass spectrometry imaging identified novel biomolecular and elemental markers with specific laminar and inter-areal differences. We conclude that mass spectrometry imaging provides a promising new approach toward multimodal, molecule-based cortical parcellation.

A cross-validated cytoarchitectonic atlas of the human ventral visual stream

The human ventral visual stream consists of several areas that are considered processing stages essential for perception and recognition. A fundamental microanatomical feature differentiating areas is cytoarchitecture, which refers to the distribution, size, and density of cells across cortical layers. Because cytoarchitectonic structure is measured in 20-micron-thick histological slices of postmortem tissue, it is difficult to assess (a) how anatomically consistent these areas are across brains and (b) how they relate to brain parcellations obtained with prevalent neuroimaging methods, acquired at the millimeter and centimeter scale. Therefore, the goal of this study was to (a) generate a cross-validated cytoarchitectonic atlas of the human ventral visual stream on a whole brain template that is commonly used in neuroimaging studies and (b) to compare this atlas to a recently published retinotopic parcellation of visual cortex (Wang et al., 2014). To achieve this goal, we generated an atlas of eight cytoarchitectonic areas: four areas in the occipital lobe (hOc1-hOc4v) and four in the fusiform gyrus (FG1-FG4), then we tested how the different alignment techniques affect the accuracy of the resulting atlas. Results show that both cortex-based alignment (CBA) and nonlinear volumetric alignment (NVA) generate an atlas with better cross-validation performance than affine volumetric alignment (AVA). Additionally, CBA outperformed NVA in 6/8 of the cytoarchitectonic areas. Finally, the comparison of the cytoarchitectonic atlas to a retinotopic atlas shows a clear correspondence between cytoarchitectonic and retinotopic areas in the ventral visual stream. The successful performance of CBA suggests a coupling between cytoarchitectonic areas and macroanatomical landmarks in the human ventral visual stream, and furthermore, that this coupling can be utilized for generating an accurate group atlas. In addition, the coupling between cytoarchitecture and retinotopy highlights the potential use of this atlas in understanding how anatomical features contribute to brain function. We make this cytoarchitectonic atlas freely available in both BrainVoyager and FreeSurfer formats (http://vpnl.stanford.edu/vcAtlas). The availability of this atlas will enable future studies to link cytoarchitectonic organization to other parcellations of the human ventral visual stream with potential to advance the understanding of this pathway in typical and atypical populations.

Two New Cytoarchitectonic Areas on the Human Mid-Fusiform Gyrus

Areas of the fusiform gyrus (FG) within human ventral temporal cortex (VTC) process high-level visual information associated with faces, limbs, words, and places. Since classical cytoarchitectonic maps do not adequately reflect the functional and structural heterogeneity of the VTC, we studied the cytoarchitectonic segregation in a region, which is rostral to the recently identified cytoarchitectonic areas FG1 and FG2. Using an observer-independent and statistically testable parcellation method, we identify 2 new areas, FG3 and FG4, in 10 human postmortem brains on the mid-FG. The mid-fusiform sulcus reliably identifies the cytoarchitectonic transition between FG3 and FG4. We registered these cytoarchitectonic areas to the common reference space of the single-subject Montreal Neurological Institute (MNI) template and generated probability maps, which reflect the intersubject variability of both areas. Future studies can relate in vivo neuroimaging data with these microscopically defined cortical areas to functional parcellations. We discuss these results in the context of both large-scale functional maps and fine-scale functional clusters that have been identified within the human VTC. We propose that our observer-independent cytoarchitectonic parcellation of the FG better explains the functional heterogeneity of the FG compared with the homogeneity of classic cytoarchitectonic maps.

Receptor-driven, multimodal mapping of the human amygdala

The human amygdala consists of subdivisions contributing to various functions. However, principles of structural organization at the cellular and molecular level are not well understood. Thus, we re-analyzed the cytoarchitecture of the amygdala and generated cytoarchitectonic probabilistic maps of ten subdivisions in stereotaxic space based on novel workflows and mapping tools. This parcellation was then used as a basis for analyzing the receptor expression for 15 receptor types. Receptor fingerprints, i.e., the characteristic balance between densities of all receptor types, were generated in each subdivision to comprehensively visualize differences and similarities in receptor architecture between the subdivisions. Fingerprints of the central and medial nuclei and the anterior amygdaloid area were highly similar. Fingerprints of the lateral, basolateral and basomedial nuclei were also similar to each other, while those of the remaining nuclei were distinct in shape. Similarities were further investigated by a hierarchical cluster analysis: a two-cluster solution subdivided the phylogenetically older part (central, medial nuclei, anterior amygdaloid area) from the remaining parts of the amygdala. A more fine-grained three-cluster solution replicated our previous parcellation including a laterobasal, superficial and centromedial group. Furthermore, it helped to better characterize the paralaminar nucleus with a molecular organization in-between the laterobasal and the superficial group. The multimodal cyto- and receptor-architectonic analysis of the human amygdala provides new insights into its microstructural organization, intersubject variability, localization in stereotaxic space and principles of receptor-based neurochemical differences.

Transcriptional and Post-Transcriptional Mechanisms of the Development of Neocortical Lamination

The neocortex is a laminated brain structure that is the seat of higher cognitive capacity and responses, long-term memory, sensory and emotional functions, and voluntary motor behavior. Proper lamination requires that progenitor cells give rise to a neuron, that the immature neuron can migrate away from its mother cell and past other cells, and finally that the immature neuron can take its place and adopt a mature identity characterized by connectivity and gene expression; thus lamination proceeds through three steps: genesis, migration, and maturation. Each neocortical layer contains pyramidal neurons that share specific morphological and molecular characteristics that stem from their prenatal birth date. Transcription factors are dynamic proteins because of the cohort of downstream factors that they regulate. RNA-binding proteins are no less dynamic, and play important roles in every step of mRNA processing. Indeed, recent screens have uncovered post-transcriptional mechanisms as being integral regulatory mechanisms to neocortical development. Here, we summarize major aspects of neocortical laminar development, emphasizing transcriptional and post-transcriptional mechanisms, with the aim of spurring increased understanding and study of its intricacies.

Multiple Transmitter Receptors in Regions and Layers of the Human Cerebral Cortex

We measured the densities (fmol/mg protein) of 15 different receptors of various transmitter systems in the supragranular, granular and infragranular strata of 44 areas of visual, somatosensory, auditory and multimodal association systems of the human cerebral cortex. Receptor densities were obtained after labeling of the receptors using quantitative in vitro receptor autoradiography in human postmortem brains. The mean density of each receptor type over all cortical layers and of each of the three major strata varies between cortical regions. In a single cortical area, the multi-receptor fingerprints of its strata (i.e., polar plots, each visualizing the densities of multiple different receptor types in supragranular, granular or infragranular layers of the same cortical area) differ in shape and size indicating regional and laminar specific balances between the receptors. Furthermore, the three strata are clearly segregated into well definable clusters by their receptor fingerprints. Fingerprints of different cortical areas systematically vary between functional networks, and with the hierarchical levels within sensory systems. Primary sensory areas are clearly separated from all other cortical areas particularly by their very high muscarinic M₂ and nicotinic α₄β₂ receptor densities, and to a lesser degree also by noradrenergic α₂ and serotonergic 5-HT₂ receptors. Early visual areas of the dorsal and ventral streams are segregated by their multi-receptor fingerprints. The results are discussed on the background of functional segregation, cortical hierarchies, microstructural types, and the horizontal (layers) and vertical (columns) organization in the cerebral cortex. We conclude that a cortical column is composed of segments, which can be assigned to the cortical strata. The segments differ by their patterns of multi-receptor balances, indicating different layer-specific signal processing mechanisms. Additionally, the differences between the strata-and area-specific fingerprints of the 44 areas reflect the segregation of the cerebral cortex into functionally and topographically definable groups of cortical areas (visual, auditory, somatosensory, limbic, motor), and reveals their hierarchical position (primary and unimodal (early) sensory to higher sensory and finally to multimodal association areas).

Highlights

Densities of transmitter receptors vary between areas of human cerebral cortex.

Multi-receptor fingerprints segregate cortical layers.

The densities of all examined receptor types together reach highest values in the supragranular stratum of all areas.

The lowest values are found in the infragranular stratum.

Multi-receptor fingerprints of entire areas and their layers segregate functional systems

Cortical types (primary sensory, motor, multimodal association) differ in their receptor fingerprints.

Comprehensive cellular-resolution atlas of the adult human brain

Detailed anatomical understanding of the human brain is essential for unraveling its functional architecture, yet current reference atlases have major limitations such as lack of whole‐brain coverage, relatively low image resolution, and sparse structural annotation. We present the first digital human brain atlas to incorporate neuroimaging, high‐resolution histology, and chemoarchitecture across a complete adult female brain, consisting of magnetic resonance imaging (MRI), diffusion‐weighted imaging (DWI), and 1,356 large‐format cellular resolution (1 µm/pixel) Nissl and immunohistochemistry anatomical plates. The atlas is comprehensively annotated for 862 structures, including 117 white matter tracts and several novel cyto‐ and chemoarchitecturally defined structures, and these annotations were transferred onto the matching MRI dataset. Neocortical delineations were done for sulci, gyri, and modified Brodmann areas to link macroscopic anatomical and microscopic cytoarchitectural parcellations. Correlated neuroimaging and histological structural delineation allowed fine feature identification in MRI data and subsequent structural identification in MRI data from other brains. This interactive online digital atlas is integrated with existing Allen Institute for Brain Science gene expression atlases and is publicly accessible as a resource for the neuroscience community. J. Comp. Neurol. 524:3127–3481, 2016. © 2016 The Authors The Journal of Comparative Neurology Published by Wiley Periodicals, Inc.

Cortical layers: Cyto-, myelo-, receptor- and synaptic architecture in human cortical areas

Cortical layers have classically been identified by their distinctive and prevailing cell types and sizes, as well as the packing densities of cell bodies or myelinated fibers. The densities of multiple receptors for classical neurotransmitters also vary across the depth of the cortical ribbon, and thus determine the neurochemical properties of cyto- and myeloarchitectonic layers. However, a systematic comparison of the correlations between these histologically definable layers and the laminar distribution of transmitter receptors is currently lacking. We here analyze the densities of 17 different receptors of various transmitter systems in the layers of eight cytoarchitectonically identified, functionally (motor, sensory, multimodal) and hierarchically (primary and secondary sensory, association) distinct areas of the human cerebral cortex. Maxima of receptor densities are found in different layers when comparing different cortical regions, i.e. laminar receptor densities demonstrate differences in receptorarchitecture between isocortical areas, notably between motor and primary sensory cortices, specifically the primary visual and somatosensory cortices, as well as between allocortical and isocortical areas. Moreover, considerable differences are found between cytoarchitectonical and receptor architectonical laminar patterns. Whereas the borders of cyto- and myeloarchitectonic layers are well comparable, the laminar profiles of receptor densities rarely coincide with the histologically defined borders of layers. Instead, highest densities of most receptors are found where the synaptic density is maximal, i.e. in the supragranular layers, particularly in layers II-III. The entorhinal cortex as an example of the allocortex shows a peculiar laminar organization, which largely deviates from that of all the other cortical areas analyzed here.

Catecholaminergic Neuromodulation Shapes Intrinsic MRI Functional Connectivity in the Human Brain

The brain commonly exhibits spontaneous (i.e., in the absence of a task) fluctuations in neural activity that are correlated across brain regions. It has been established that the spatial structure, or topography, of these intrinsic correlations is in part determined by the fixed anatomical connectivity between regions. However, it remains unclear which factors dynamically sculpt this topography as a function of brain state. Potential candidate factors are subcortical catecholaminergic neuromodulatory systems, such as the locus ceruleus-norepinephrine system, which send diffuse projections to most parts of the forebrain. Here, we systematically characterized the effects of endogenous central neuromodulation on correlated fluctuations during rest in the human brain. Using a double-blind placebo-controlled crossover design, we pharmacologically increased synaptic catecholamine levels by administering atomoxetine, an NE transporter blocker, and examined the effects on the strength and spatial structure of resting-state MRI functional connectivity. First, atomoxetine reduced the strength of inter-regional correlations across three levels of spatial organization, indicating that catecholamines reduce the strength of functional interactions during rest. Second, this modulatory effect on intrinsic correlations exhibited a substantial degree of spatial specificity: the decrease in functional connectivity showed an anterior-posterior gradient in the cortex, depended on the strength of baseline functional connectivity, and was strongest for connections between regions belonging to distinct resting-state networks. Thus, catecholamines reduce intrinsic correlations in a spatially heterogeneous fashion. We conclude that neuromodulation is an important factor shaping the topography of intrinsic functional connectivity.

SIGNIFICANCE STATEMENT

The human brain shows spontaneous activity that is strongly correlated across brain regions. The factors that dynamically sculpt these inter-regional correlation patterns are poorly understood. Here, we test the hypothesis that they are shaped by the catecholaminergic neuromodulators norepinephrine and dopamine. We pharmacologically increased synaptic catecholamine levels and measured the resulting changes in intrinsic fMRI functional connectivity. At odds with common understanding of catecholamine function, we found (1) overall reduced inter-regional correlations across several levels of spatial organization; and (2) a remarkable spatial specificity of this modulatory effect. Our results identify norepinephrine and dopamine as important factors shaping intrinsic functional connectivity and advance our understanding of catecholamine function in the central nervous system.

Transcriptomic Perspectives on Neocortical Structure, Development, Evolution, and Disease

The cerebral cortex is the source of our most complex cognitive capabilities and a vulnerable target of many neurological and neuropsychiatric disorders. Transcriptomics offers a new approach to understanding the cortex at the level of its underlying genetic code, and rapid technological advances have propelled this field to the high-throughput study of the complete set of transcribed genes at increasingly fine resolution to the level of individual cells. These tools have revealed features of the genetic architecture of adult cortical areas, layers, and cell types, as well as spatiotemporal patterning during development. This has allowed a fresh look at comparative anatomy as well, illustrating surprisingly large differences between mammals while at the same time revealing conservation of some features from avians to mammals. Finally, transcriptomics is fueling progress in understanding the causes of neurodevelopmental diseases such as autism, linking genetic association studies to specific molecular pathways and affected brain regions.

Direct Visualization and Mapping of the Spatial Course of Fiber Tracts at Microscopic Resolution in the Human Hippocampus

While hippocampal connectivity is essential to normal memory function, our knowledge of human hippocampal circuitry is largely inferred from animal studies. Using polarized light microscopy at 1.3 µm resolution, we have directly visualized the 3D course of key medial temporal pathways in 3 ex vivo human hemispheres and 2 ex vivo vervet monkey hemispheres. The multiple components of the perforant path system were clearly identified: Superficial sheets of fibers emanating from the entorhinal cortex project to the presubiculum and parasubiculum, intermixed transverse and longitudinal angular bundle fibers perforate the subiculum and then project to the cornu ammonis (CA) fields and dentate molecular layer, and a significant alvear component runs from the angular bundle to the CA fields. From the hilus, mossy fibers localize to regions of high kainate receptor density, and the endfolial pathway, mostly investigated in humans, merges with the Schaffer collaterals. This work defines human hippocampal pathways underlying mnemonic function at an unprecedented resolution.

Synaptic patterning and the timescales of cortical dynamics

Neocortical circuits, as large heterogeneous recurrent networks, can potentially operate and process signals at multiple timescales, but appear to be differentially tuned to operate within certain temporal receptive windows. The modular and hierarchical organization of this selectivity mirrors anatomical and physiological relations throughout the cortex and is likely determined by the regional electrochemical composition. Being consistently patterned and actively regulated, the expression of molecules involved in synaptic transmission constitutes the most significant source of laminar and regional variability. Due to their complex kinetics and adaptability, synapses form a natural primary candidate underlying this regional temporal selectivity. The ability of cortical networks to reflect the temporal structure of the sensory environment can thus be regulated by evolutionary and experience-dependent processes.