Organizational principles of human visual cortex revealed by receptor mapping

Computational model links normalization to chemoarchitecture in the human visual system

A goal of cognitive neuroscience is to provide computational accounts of brain function. Canonical computations-mathematical operations used by the brain in many contexts-fulfill broad information-processing needs by varying their algorithmic parameters. A key question concerns the identification of biological substrates for these computations and their algorithms. Chemoarchitecture-the spatial distribution of neurotransmitter receptor densities-shapes brain function. Here, we propose that local variations in specific receptor densities implement algorithmic modulations of canonical computations. To test this hypothesis, we combine mathematical modeling of brain responses with chemoarchitecture data. We compare parameters of divisive normalization obtained from 7-tesla functional magnetic resonance imaging with receptor density maps obtained from positron emission tomography. We find evidence that serotonin and γ-aminobutyric acid receptor densities are the biological substrate for algorithmic modulations of divisive normalization in the human visual system. Our model links computational and biological levels of vision, explaining how canonical computations allow the brain to fulfill broad information-processing needs.

One Size Does Not Fit All: Methodological Considerations for Brain-Based Predictive Modeling in Psychiatry

Psychiatric illnesses are heterogeneous in nature. No illness manifests in the same way across individuals, and no two patients with a shared diagnosis exhibit identical symptom profiles. Over the last several decades, group-level analyses of in vivo neuroimaging data have led to fundamental advances in our understanding of the neurobiology of psychiatric illnesses. More recently, access to computational resources and large, publicly available datasets alongside the rise of predictive modeling and precision medicine approaches have facilitated the study of psychiatric illnesses at an individual level. Data-driven machine learning analyses can be applied to identify disease-relevant biological subtypes, predict individual symptom profiles, and recommend personalized therapeutic interventions. However, when developing these predictive models, methodological choices must be carefully considered to ensure accurate, robust, and interpretable results. Choices pertaining to algorithms, neuroimaging modalities and states, data transformation, phenotypes, parcellations, sample sizes, and populations we are specifically studying can influence model performance. Here, we review applications of neuroimaging-based machine learning models to study psychiatric illnesses and discuss the effects of different methodological choices on model performance. An understanding of these effects is crucial for the proper implementation of predictive models in psychiatry and will facilitate more accurate diagnoses, prognoses, and therapeutics.

Improved correspondence of fMRI visual field localizer data after cortex-based macroanatomical alignment

Studying the visual system with fMRI often requires using localizer paradigms to define regions of interest (ROIs). However, the considerable interindividual variability of the cerebral cortex represents a crucial confound for group-level analyses. Cortex-based alignment (CBA) techniques reliably reduce interindividual macroanatomical variability. Yet, their utility has not been assessed for visual field localizer paradigms, which map specific parts of the visual field within retinotopically organized visual areas. We evaluated CBA for an attention-enhanced visual field localizer, mapping homologous parts of each visual quadrant in 50 participants. We compared CBA with volume-based alignment and a surface-based analysis, which did not include macroanatomical alignment. CBA led to the strongest increase in the probability of activation overlap (up to 86%). At the group level, CBA led to the most consistent increase in ROI size while preserving vertical ROI symmetry. Overall, our results indicate that in addition to the increased signal-to-noise ratio of a surface-based analysis, macroanatomical alignment considerably improves statistical power. These findings confirm and extend the utility of CBA for the study of the visual system in the context of group analyses. CBA should be particularly relevant when studying neuropsychiatric disorders with abnormally increased interindividual macroanatomical variability.

Receptor architecture of macaque and human early visual areas: not equal, but comparable

Existing cytoarchitectonic maps of the human and macaque posterior occipital cortex differ in the number of areas they display, thus hampering identification of homolog structures. We applied quantitative in vitro receptor autoradiography to characterize the receptor architecture of the primary visual and early extrastriate cortex in macaque and human brains, using previously published cytoarchitectonic criteria as starting point of our analysis. We identified 8 receptor architectonically distinct areas in the macaque brain (mV1d, mV1v, mV2d, mV2v, mV3d, mV3v, mV3A, mV4v), and their respective counterpart areas in the human brain (hV1d, hV1v, hV2d, hV2v, hV3d, hV3v, hV3A, hV4v). Mean densities of 14 neurotransmitter receptors were quantified in each area, and ensuing receptor fingerprints used for multivariate analyses. The 1st principal component segregated macaque and human early visual areas differ. However, the 2nd principal component showed that within each species, area-specific differences in receptor fingerprints were associated with the hierarchical processing level of each area. Subdivisions of V2 and V3 were found to cluster together in both species and were segregated from subdivisions of V1 and from V4v. Thus, comparative studies like this provide valuable architectonic insights into how differences in underlying microstructure impact evolutionary changes in functional processing of the primate brain and, at the same time, provide strong arguments for use of macaque monkey brain as a suitable animal model for translational studies.

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.

The Neurotransmitter Receptor Architecture of the Mouse Olfactory System

The uptake, transmission and processing of sensory olfactory information is modulated by inhibitory and excitatory receptors in the olfactory system. Previous studies have focused on the function of individual receptors in distinct brain areas, but the receptor architecture of the whole system remains unclear. Here, we analyzed the receptor profiles of the whole olfactory system of adult male mice. We examined the distribution patterns of glutamatergic (AMPA, kainate, mGlu_2/3, and NMDA), GABAergic (GABA_A, GABA_A(BZ), and GABA_B), dopaminergic (D_1/5) and noradrenergic (α₁ and α₂) neurotransmitter receptors by quantitative in vitro receptor autoradiography combined with an analysis of the cyto- and myelo-architecture. We observed that each subarea of the olfactory system is characterized by individual densities of distinct neurotransmitter receptor types, leading to a region- and layer-specific receptor profile. Thereby, the investigated receptors in the respective areas and strata showed a heterogeneous expression. Generally, we detected high densities of mGlu_2/3Rs, GABA_A(BZ)Rs and GABA_BRs. Noradrenergic receptors revealed a highly heterogenic distribution, while the dopaminergic receptor D_1/5 displayed low concentrations, except in the olfactory tubercle and the dorsal endopiriform nucleus. The similarities and dissimilarities of the area-specific multireceptor profiles were analyzed by a hierarchical cluster analysis. A three-cluster solution was found that divided the areas into the (1) olfactory relay stations (main and accessory olfactory bulb), (2) the olfactory cortex (anterior olfactory cortex, dorsal peduncular cortex, taenia tecta, piriform cortex, endopiriform nucleus, entorhinal cortex, orbitofrontal cortex) and the (3) olfactory tubercle, constituting its own cluster. The multimodal receptor-architectonic analysis of each component of the olfactory system provides new insights into its neurochemical organization and future possibilities for pharmaceutic targeting.

Mapping migraine to a common brain network

Inconsistent findings from migraine neuroimaging studies have limited attempts to localize migraine symptomatology. Novel brain network mapping techniques offer a new approach for linking neuroimaging findings to a common neuroanatomical substrate and localizing therapeutic targets. In this study, we attempted to determine whether neuroanatomically heterogeneous neuroimaging findings of migraine localize to a common brain network. We used meta-analytic coordinates of decreased grey matter volume in migraineurs as seed regions to generate resting state functional connectivity network maps from a normative connectome (n = 1000). Network maps were overlapped to identify common regions of connectivity across all coordinates. Specificity of our findings was evaluated using a whole-brain Bayesian spatial generalized linear mixed model and a region of interest analysis with comparison groups of chronic pain and a neurologic control (Alzheimer's disease). We found that all migraine coordinates (11/11, 100%) were negatively connected (t ≥ ±7, P < 10-6 family-wise error corrected for multiple comparisons) to a single location in left extrastriate visual cortex overlying dorsal V3 and V3A subregions. More than 90% of coordinates (10/11) were also positively connected with bilateral insula and negatively connected with the hypothalamus. Bayesian spatial generalized linear mixed model whole-brain analysis identified left V3/V3A as the area with the most specific connectivity to migraine coordinates compared to control coordinates (voxel-wise probability of ≥90%). Post hoc region of interest analyses further supported the specificity of this finding (ANOVA P = 0.02; pairwise t-tests P = 0.03 and P = 0.003, respectively). In conclusion, using coordinate-based network mapping, we show that regions of grey matter volume loss in migraineurs localize to a common brain network defined by connectivity to visual cortex V3/V3A, a region previously implicated in mechanisms of cortical spreading depression in migraine. Our findings help unify migraine neuroimaging literature and offer a migraine-specific target for neuromodulatory treatment.

Transient cholinergic enhancement does not significantly affect either the magnitude or selectivity of perceptual learning of visual texture discrimination

Perceptual learning (PL), often characterized by improvements in perceptual performance with training that are specific to the stimulus conditions used during training, exemplifies experience-dependent cortical plasticity. An improved understanding of how neuromodulatory systems shape PL promises to provide new insights into the mechanisms of plasticity, and by extension how PL can be generated and applied most efficiently. Previous studies have reported enhanced PL in human subjects following administration of drugs that increase signaling through acetylcholine (ACh) receptors, and physiological evidence indicates that ACh sharpens neuronal selectivity, suggesting that this neuromodulator supports PL and its stimulus specificity. Here we explored the effects of enhancing endogenous cholinergic signaling during PL of a visual texture discrimination task. We found that training on this task in the lower visual field yielded significant behavioral improvement at the trained location. However, a single dose of the cholinesterase inhibitor donepezil, administered before training, did not significantly impact either the magnitude or the location specificity of texture discrimination learning compared with placebo. We discuss potential explanations for discrepant findings in the literature regarding the role of ACh in visual PL, including possible differences in plasticity mechanisms in the dorsal and ventral cortical processing streams.

Ant Colony Clustering for ROI Identification in Functional Magnetic Resonance Imaging

Brain network analysis using functional magnetic resonance imaging (fMRI) is a widely used technique. The first step of brain network analysis in fMRI is to detect regions of interest (ROIs). The signals from these ROIs are then used to evaluate neural networks and quantify neuronal dynamics. The two main methods to identify ROIs are based on brain atlas registration and clustering. This work proposes a bioinspired method that combines both paradigms. The method, dubbed HAnt, consists of an anatomical clustering of the signal followed by an ant clustering step. The method is evaluated empirically in both in silico and in vivo experiments. The results show a significantly better performance of the proposed approach compared to other brain parcellations obtained using purely clustering-based strategies or atlas-based parcellations.

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.

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.

The effect of a single dose of escitalopram on sensorimotor networks

INTRODUCTION

Serving as a pilot study of poststroke pharmacotherapy, the present investigation was intended to establish the effect of a single dose of escitalopram on motor task performance in normal volunteers.

METHODS

Ten healthy volunteers of median age 63 years including four females performed a well-studied tactile manipulation task in two fMRI sessions using a double-blind cross-over design. The sessions began approximately three hours after ingestion of 20 mg escitalopram or placebo presented in pseudorandom order. The fMRI image sequences were submitted to principal component analysis (PCA).

RESULTS

Based on volume correlations of task-related principal components with the mean component images derived in our previous study, we established the reproducibility of two networks of sensorimotor activity proposed there. The network reflecting motor control (cerebral pattern I) appeared invariably in placebo and verum conditions. In contrast, the other network, attributed to diminished motor control due to distracting mental processing (cerebral pattern II), emerged less regularly and exhibited more variability. Second-level PCAs of both conditions confirmed the findings of the initial analysis. Specifically, it validated the dominant and invariable expression of cerebral pattern I after application of a single dose of escitalopram. Dynamic causal modeling confirmed enhanced motor output as a result of a significantly increased connectivity between primary motor cortex and dorsal premotor cortex.

CONCLUSION

This pilot study suggests the promise of stimulation by a specific serotonin reuptake inhibitor in regard to recovery and preservation of motor control after stroke.

The development of human visual cortex and clinical implications

The primary visual cortex (V1) is the first cortical area that processes visual information. Normal development of V1 depends on binocular vision during the critical period, and age-related losses of vision are linked with neurobiological changes in V1. Animal studies have provided important details about the neurobiological mechanisms in V1 that support normal vision or are changed by visual diseases. There is very little information, however, about those neurobiological mechanisms in human V1. That lack of information has hampered the translation of biologically inspired treatments from preclinical models to effective clinical treatments. We have studied human V1 to characterize the expression of neurobiological mechanisms that regulate visual perception and neuroplasticity. We have identified five stages of development for human V1 that start in infancy and continue across the life span. Here, we describe these stages, compare them with visual and anatomical milestones, and discuss implications for translating treatments for visual disorders that depend on neuroplasticity of V1 function.

Vascular-metabolic and GABAergic Inhibitory Correlates of Neural Variability Modulation. A Combined fMRI and PET Study

Neural activity varies continually from moment to moment. Such temporal variability (TV) has been highlighted as a functionally specific brain property playing a fundamental role in cognition. We sought to investigate the mechanisms involved in TV changes between two basic behavioral states, namely having the eyes open (EO) or eyes closed (EC) in vivo in humans. To these ends we acquired BOLD fMRI, ASL, and [¹⁸F]-fluoro-deoxyglucose PET in a group of healthy participants (n = 15), along with BOLD fMRI and [¹⁸F]-flumazenil PET in a separate group (n = 19). Focusing on an EO- vs EC-sensitive region in the occipital cortex (identified in an independent sample), we show that TV is constrained in the EO condition compared to EC. This reduction is correlated with an increase in energy consumption and with regional GABA_A receptor density. This suggests that the modulation of TV by behavioral state involves an increase in overall neural activity that is related to an increased effect from GABAergic inhibition in addition to any excitatory changes. These findings contribute to our understanding of the mechanisms underlying activity variability in the human brain and its control.

Differential Sampling of Visual Space in Ventral and Dorsal Early Visual Cortex

A fundamental feature of cortical visual processing is the separation of visual processing for the upper and lower visual fields. In early visual cortex (EVC), the upper visual field is processed ventrally, with the lower visual field processed dorsally. This distinction persists into several category-selective regions of occipitotemporal cortex, with ventral and lateral scene-, face-, and object-selective regions biased for the upper and lower visual fields, respectively. Here, using an elliptical population receptive field (pRF) model, we systematically tested the sampling of visual space within ventral and dorsal divisions of human EVC in both male and female participants. We found that (1) pRFs tend to be elliptical and oriented toward the fovea with distinct angular distributions for ventral and dorsal divisions of EVC, potentially reflecting a radial bias; and (2) pRFs in ventral areas were larger (∼1.5×) and more elliptical (∼1.2×) than those in dorsal areas. These differences potentially reflect a tendency for receptive fields in ventral temporal cortex to overlap the fovea with less emphasis on precise localization and isotropic representation of space compared with dorsal areas. Collectively, these findings suggest that ventral and dorsal divisions of EVC sample visual space differently, likely contributing to and/or stemming from the functional differentiation of visual processing observed in higher-level regions of the ventral and dorsal cortical visual pathways.SIGNIFICANCE STATEMENT The processing of visual information from the upper and lower visual fields is separated in visual cortex. Although ventral and dorsal divisions of early visual cortex (EVC) are commonly assumed to sample visual space equivalently, we demonstrate systematic differences using an elliptical population receptive field (pRF) model. Specifically, we demonstrate that (1) ventral and dorsal divisions of EVC exhibit diverging distributions of pRF angle, which are biased toward the fovea; and (2) ventral pRFs exhibit higher aspect ratios and cover larger areas than dorsal pRFs. These results suggest that ventral and dorsal divisions of EVC sample visual space differently and that such differential sampling likely contributes to different functional roles attributed to the ventral and dorsal pathways, such as object recognition and visually guided attention, respectively.

Structural and functional correlates of visual field asymmetry in the human brain by diffusion kurtosis MRI and functional MRI

Human visual performance has been observed to show superiority in localized regions of the visual field across many classes of stimuli. However, the underlying neural mechanisms remain unclear. This study aims to determine whether the visual information processing in the human brain is dependent on the location of stimuli in the visual field and the corresponding neuroarchitecture using blood-oxygenation-level-dependent functional MRI (fMRI) and diffusion kurtosis MRI, respectively, in 15 healthy individuals at 3 T. In fMRI, visual stimulation to the lower hemifield showed stronger brain responses and larger brain activation volumes than the upper hemifield, indicative of the differential sensitivity of the human brain across the visual field. In diffusion kurtosis MRI, the brain regions mapping to the lower visual field showed higher mean kurtosis, but not fractional anisotropy or mean diffusivity compared with the upper visual field. These results suggested the different distributions of microstructural organization across visual field brain representations. There was also a strong positive relationship between diffusion kurtosis and fMRI responses in the lower field brain representations. In summary, this study suggested the structural and functional brain involvements in the asymmetry of visual field responses in humans, and is important to the neurophysiological and psychological understanding of human visual information processing.

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.

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.

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.

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.

Topographic organization of the cerebral cortex and brain cartography

One of the most specific but also challenging properties of the brain is its topographic organization into distinct modules or cortical areas. In this paper, we first review the concept of topographic organization and its historical development. Next, we provide a critical discussion of the current definition of what constitutes a cortical area, why the concept has been so central to the field of neuroimaging and the challenges that arise from this view. A key aspect in this discussion is the issue of spatial scale and hierarchy in the brain. Focusing on in-vivo brain parcellation as a rapidly expanding field of research, we highlight potential limitations of the classical concept of cortical areas in the context of multi-modal parcellation and propose a revised interpretation of cortical areas building on the concept of neurobiological atoms that may be aggregated into larger units within and across modalities. We conclude by presenting an outlook on the implication of this revised concept for future mapping studies and raise some open questions in the context of brain parcellation.

Modulatory compartments in cortex and local regulation of cholinergic tone

Neuromodulatory signaling is generally considered broad in its impact across cortex. However, variations in the characteristics of cortical circuits may introduce regionally-specific responses to diffuse modulatory signals. Features such as patterns of axonal innervation, tissue tortuosity and molecular diffusion, effectiveness of degradation pathways, subcellular receptor localization, and patterns of receptor expression can lead to local modification of modulatory inputs. We propose that modulatory compartments exist in cortex and can be defined by variation in structural features of local circuits. Further, we argue that these compartments are responsible for local regulation of neuromodulatory tone. For the cholinergic system, these modulatory compartments are regions of cortical tissue within which signaling conditions for acetylcholine are relatively uniform, but between which signaling can vary profoundly. In the visual system, evidence for the existence of compartments indicates that cholinergic modulation likely differs across the visual pathway. We argue that the existence of these compartments calls for thinking about cholinergic modulation in terms of finer-grained control of local cortical circuits than is implied by the traditional view of this system as a diffuse modulator. Further, an understanding of modulatory compartments provides an opportunity to better understand and perhaps correct signal modifications that lead to pathological states.

Sensitivity to the visual field origin of natural image patches in human low-level visual cortex

Asymmetries in the response to visual patterns in the upper and lower visual fields (above and below the centre of gaze) have been associated with ecological factors relating to the structure of typical visual environments. Here, we investigated whether the content of the upper and lower visual field representations in low-level regions of human visual cortex are specialised for visual patterns that arise from the upper and lower visual fields in natural images. We presented image patches, drawn from above or below the centre of gaze of an observer navigating a natural environment, to either the upper or lower visual fields of human participants (n = 7) while we used functional magnetic resonance imaging (fMRI) to measure the magnitude of evoked activity in the visual areas V1, V2, and V3. We found a significant interaction between the presentation location (upper or lower visual field) and the image patch source location (above or below fixation); the responses to lower visual field presentation were significantly greater for image patches sourced from below than above fixation, while the responses in the upper visual field were not significantly different for image patches sourced from above and below fixation. This finding demonstrates an association between the representation of the lower visual field in human visual cortex and the structure of the visual input that is likely to be encountered below the centre of gaze.

Unraveling the multiscale structural organization and connectivity of the human brain: the role of diffusion MRI

The structural architecture and the anatomical connectivity of the human brain show different organizational principles at distinct spatial scales. Histological staining and light microscopy techniques have been widely used in classical neuroanatomical studies to unravel brain organization. Using such techniques is a laborious task performed on 2-dimensional histological sections by skilled anatomists possibly aided by semi-automated algorithms. With the recent advent of modern magnetic resonance imaging (MRI) contrast mechanisms, cortical layers and columns can now be reliably identified and their structural properties quantified post-mortem. These developments are allowing the investigation of neuroanatomical features of the brain at a spatial resolution that could be interfaced with that of histology. Diffusion MRI and tractography techniques, in particular, have been used to probe the architecture of both white and gray matter in three dimensions. Combined with mathematical network analysis, these techniques are increasingly influential in the investigation of the macro-, meso-, and microscopic organization of brain connectivity and anatomy, both in vivo and ex vivo. Diffusion MRI-based techniques in combination with histology approaches can therefore support the endeavor of creating multimodal atlases that take into account the different spatial scales or levels on which the brain is organized. The aim of this review is to illustrate and discuss the structural architecture and the anatomical connectivity of the human brain at different spatial scales and how recently developed diffusion MRI techniques can help investigate these.

Connectomics and new approaches for analyzing human brain functional connectivity

Estimating the functional interactions between brain regions and mapping those connections to corresponding inter-individual differences in cognitive, behavioral and psychiatric domains are central pursuits for understanding the human connectome. The number and complexity of functional interactions within the connectome and the large amounts of data required to study them position functional connectivity research as a “big data” problem. Maximizing the degree to which knowledge about human brain function can be extracted from the connectome will require developing a new generation of neuroimaging analysis algorithms and tools. This review describes several outstanding problems in brain functional connectomics with the goal of engaging researchers from a broad spectrum of data sciences to help solve these problems. Additionally it provides information about open science resources consisting of raw and preprocessed data to help interested researchers get started.

Common molecular basis of the sentence comprehension network revealed by neurotransmitter receptor fingerprints

The language network is a well-defined large-scale neural network of anatomically and functionally interacting cortical areas. The successful language process requires the transmission of information between these areas. Since neurotransmitter receptors are key molecules of information processing, we hypothesized that cortical areas which are part of the same functional language network may show highly similar multireceptor expression pattern ("receptor fingerprint"), whereas those that are not part of this network should have different fingerprints. Here we demonstrate that the relation between the densities of 15 different excitatory, inhibitory and modulatory receptors in eight language-related areas are highly similar and differ considerably from those of 18 other brain regions not directly involved in language processing. Thus, the fingerprints of all cortical areas underlying a large-scale cognitive domain such as language is a characteristic, functionally relevant feature of this network and an important prerequisite for the underlying neuronal processes of language functions.

Which fMRI clustering gives good brain parcellations?

Analysis and interpretation of neuroimaging data often require one to divide the brain into a number of regions, or parcels, with homogeneous characteristics, be these regions defined in the brain volume or on the cortical surface. While predefined brain atlases do not adapt to the signal in the individual subject images, parcellation approaches use brain activity (e.g., found in some functional contrasts of interest) and clustering techniques to define regions with some degree of signal homogeneity. In this work, we address the question of which clustering technique is appropriate and how to optimize the corresponding model. We use two principled criteria: goodness of fit (accuracy), and reproducibility of the parcellation across bootstrap samples. We study these criteria on both simulated and two task-based functional Magnetic Resonance Imaging datasets for the Ward, spectral and k-means clustering algorithms. We show that in general Ward’s clustering performs better than alternative methods with regard to reproducibility and accuracy and that the two criteria diverge regarding the preferred models (reproducibility leading to more conservative solutions), thus deferring the practical decision to a higher level alternative, namely the choice of a trade-off between accuracy and stability.

Meta-analytic connectivity modeling revisited: controlling for activation base rates

Co-activation of distinct brain regions is a measure of functional interaction, or connectivity, between those regions. The co-activation pattern of a given region can be investigated using seed-based activation likelihood estimation meta-analysis of functional neuroimaging data stored in databases such as BrainMap. This method reveals inter-regional functional connectivity by determining brain regions that are consistently co-activated with a given region of interest (the "seed") across a broad range of experiments. In current implementations of this meta-analytic connectivity modeling (MACM), significant spatial convergence (i.e. consistent co-activation) is distinguished from noise by comparing it against an unbiased null-distribution of random spatial associations between experiments according to which all gray-matter voxels have the same chance of convergence. As the a priori probability of finding activation in different voxels markedly differs across the brain, computing such a quasi-rectangular null-distribution renders the detection of significant convergence more likely in those voxels that are frequently activated. Here, we propose and test a modified MACM approach that takes this activation frequency bias into account. In this new specific co-activation likelihood estimation (SCALE) algorithm, a null-distribution is generated that reflects the base rate of reporting activation in any given voxel and thus equalizes the a priori chance of finding across-study convergence in each voxel of the brain. Using four exemplary seed regions (right visual area V4, left anterior insula, right intraparietal sulcus, and subgenual cingulum), our tests corroborated the enhanced specificity of the modified algorithm, indicating that SCALE may be especially useful for delineating distinct core networks of co-activation.

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

The human cerebral cortex contains numerous myelinated fibres, the arrangement and density of which is by no means homogeneous throughout the cortex. Local differences in the spatial organization of these fibres render it possible to recognize areas with a different myeloarchitecture. The neuroanatomical subdiscipline aimed at the identification and delineation of such areas is known as myeloarchitectonics. During the period extending from 1910 to 1970, Oscar and Cécile Vogt and their numerous collaborators (The Vogt-Vogt school) published a large number of myeloarchitectonic studies on the cortex of the various lobes of the human cerebrum. Recently, one of us (Nieuwenhuys in Brain Struct Funct 218: 303-352, 2013) extensively reviewed these studies. It was concluded that the data available are adequate and sufficient for the composition of a myeloarchitectonic map of the entire human neocortex. The present paper is devoted to the creation of this map. Because the data provided by the Vogt-Vogt school are derived from many different brains, a standard brain had to be introduced to which all data available could be transferred. As such, the colin27 structural scan, aligned to the MNI305 template was selected. The procedure employed in this transfer involved computer-aided transformations of the lobar maps available in the literature, to the corresponding regions of the standard brain, as well as local adjustments in the border zones of the various lobes. The resultant map includes 180 myeloarchitectonic areas, 64 frontal, 30 parietal, 6 insular, 17 occipital and 63 temporal. The designation of the various areas with simple Arabic numbers, introduced by Oscar Vogt for the frontal and parietal cortices, has been extended over the entire neocortex. It may be expected that combination of the myeloarchitectonic data of the Vogt-Vogt school, as expressed in our map, with the results of the detailed cytoarchitectonic and receptor architectonic studies of Karl Zilles and Katrin Amunts and their numerous associates, will yield a comprehensive 'supermap' of the structural organization of the human neocortex. For the time being, i. e., as long as this 'supermap' is not yet available, our map may provide a tentative frame of reference for (a) the morphological interpretation of the results of functional neuroimaging studies; (b) the selection of starting points (seed voxels, regions-of-interest) in diffusion tractography studies and

Cytoarchitectonic mapping of the human dorsal extrastriate cortex

The dorsal visual stream consists of several functionally specialized areas, but most of their cytoarchitectonic correlates have not yet been identified in the human brain. The cortex adjacent to Brodmann area 18/V2 was therefore analyzed in serial sections of ten human post-mortem brains using morphometrical and multivariate statistical analyses for the definition of areal borders. Two previously unknown cytoarchitectonic areas (hOc3d, hOc4d) were detected. They occupy the medial and, to a smaller extent, lateral surface of the occipital lobe. The larger area, hOc3d, is located dorso-lateral to area V2 in the region of superior and transverse occipital, as well as parieto-occipital sulci. Area hOc4d was identified rostral to hOc3d; it differed from the latter by larger pyramidal cells in lower layer III, thinner layers V and VI, and a sharp cortex-white-matter borderline. The delineated areas were superimposed in the anatomical MNI space, and probabilistic maps were calculated. They show a relatively high intersubject variability in volume and position. Based on their location and neighborhood relationship, areas hOc3d and hOc4d are putative anatomical substrates of functionally defined areas V3d and V3a, a hypothesis that can now be tested by comparing probabilistic cytoarchitectonic maps and activation studies of the living human brain.

The myeloarchitectonic studies on the human cerebral cortex of the Vogt-Vogt school, and their significance for the interpretation of functional neuroimaging data

The human cerebral cortex contains numerous myelinated fibres, many of which are concentrated in tangentially organized layers and radially oriented bundles. The spatial organization of these fibres is by no means homogeneous throughout the cortex. Local differences in the thickness and compactness of the fibre layers, and in the length and strength of the radial bundles renders it possible to recognize areas with a different myeloarchitecture. The neuroanatomical subdiscipline aimed at the identification and delineation of such areas is known as myeloarchitectonics. There is another, closely related neuroanatomical subdiscipline, named cytoarchitectonics. The aims and scope of this subdiscipline are the same as those of myeloarchitectonics, viz. parcellation. However, this subdiscipline focuses, as its name implies, on the size, shape and arrangement of the neuronal cell bodies in the cortex, rather than on the myelinated fibres. At the beginning of the twentieth century, two young investigators, Oskar and Cécile Vogt founded a centre for brain research, aimed to be devoted to the study of the (cyto + myelo) architecture of the cerebral cortex. The study of the cytoarchitecture was entrusted to their collaborator Korbinian Brodmann, who gained great fame with the creation of a cytoarchitectonic map of the human cerebral cortex. Here, we focus on the myeloarchitectonic studies on the cerebral cortex of the Vogt-Vogt school, because these studies are nearly forgotten in the present attempts to localize functional activations and to interprete findings in modern neuroimaging studies. Following introductory sections on the principles of myeloarchitectonics, and on the achievements of three myeloarchitectonic pioneers who did not belong to the Vogt-Vogt school, the pertinent literature is reviewed in some detail. These studies allow the conclusion that the human neocortex contains about 185 myeloarchitectonic areas, 70 frontal, 6 insular, 30 parietal, 19 occipital, and 60 temporal. It is emphasized that the data available, render it possible to compose a myeloarchitectonic map of the human neocortex, which is at least as reliable as any of the classic architectonic maps. During the realization of their myeloarchitectonic research program, in which numerous able collaborators were involved, the Vogts gradually developed a general concept of the organization of the cerebral cortex. The essence of this concept is that this structure is composed of about 200 distinct, juxtaposed 'Rindenfelder' or 'topistische Einheiten', which represent fundamental structural as well as functional entities. The second main part of this article is devoted to a discussion and evaluation of this 'Vogt-Vogt concept'. It is concluded that there is converging quantitative cytoarchitectonic, receptor architectonic, myeloarchitectonic, hodological, and functional evidence, indicating that this concept is essentially correct. The third, and final part of this article deals with the problem of relating particular cortical functions, as determined with neuroimaging techniques, to particular cortical structures. At present, these 'translation' operations are generally based on adapted, three-dimensional versions of Brodmann's famous map. However, it has become increasingly clear that these maps do not provide the neuroanatomical precision to match the considerable degree of functional segregation, suggested by neuroimaging studies. Therefore, we strongly recommend an attempt at combining and synthesizing the results of Brodmann's cytoarchitectonic analysis, with those of the detailed myeloarchitectonic studies of the Vogt-Vogt school. These studies may also be of interest for the interpretation of the myeloarchitectonic features, visualized in modern in vivo mappings of the human cortex.

Long-term memory search across the visual brain

Signal transmission from the human retina to visual cortex and connectivity of visual brain areas are relatively well understood. How specific visual perceptions transform into corresponding long-term memories remains unknown. Here, I will review recent Blood Oxygenation Level-Dependent functional Magnetic Resonance Imaging (BOLD fMRI) in humans together with molecular biology studies (animal models) aiming to understand how the retinal image gets transformed into so-called visual (retinotropic) maps. The broken object paradigm has been chosen in order to illustrate the complexity of multisensory perception of simple objects subject to visual —rather than semantic— type of memory encoding. The author explores how amygdala projections to the visual cortex affect the memory formation and proposes the choice of experimental techniques needed to explain our massive visual memory capacity. Maintenance of the visual long-term memories is suggested to require recycling of GluR2-containing α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPAR) and β₂-adrenoreceptors at the postsynaptic membrane, which critically depends on the catalytic activity of the N-ethylmaleimide-sensitive factor (NSF) and protein kinase PKMζ.

Architecture and organizational principles of Broca's region

Identifying cortical areas for language and speech processing is a prerequisite for cognitive neuroscience and clinical research. Although Broca's region is one of the essential nodes in the language network, its anatomical constituents are ill-defined and multiple definitions of Broca's region exist. Sanides' concept of microstructural gradations interpreted Broca's region as developing from neighboring motor, dorsolateral-prefrontal, and insular cortices. Recent mapping approaches based on cytoarchitecture, transmitter receptor distribution, and connectivity revealed a highly differentiated segregation of this region far beyond Brodmann's classical scheme. This novel segregational concept of structural and functional architecture more adequately reflects the various functions of Broca's region in cognitive and/or linguistic processes.

Abnormal brain activation in neurofibromatosis type 1: a link between visual processing and the default mode network

Neurofibromatosis type 1 (NF1) is one of the most common single gene disorders affecting the human nervous system with a high incidence of cognitive deficits, particularly visuospatial. Nevertheless, neurophysiological alterations in low-level visual processing that could be relevant to explain the cognitive phenotype are poorly understood. Here we used functional magnetic resonance imaging (fMRI) to study early cortical visual pathways in children and adults with NF1. We employed two distinct stimulus types differing in contrast and spatial and temporal frequencies to evoke relatively different activation of the magnocellular (M) and parvocellular (P) pathways. Hemodynamic responses were investigated in retinotopically-defined regions V1, V2 and V3 and then over the acquired cortical volume. Relative to matched control subjects, patients with NF1 showed deficient activation of the low-level visual cortex to both stimulus types. Importantly, this finding was observed for children and adults with NF1, indicating that low-level visual processing deficits do not ameliorate with age. Moreover, only during M-biased stimulation patients with NF1 failed to deactivate or even activated anterior and posterior midline regions of the default mode network. The observation that the magnocellular visual pathway is impaired in NF1 in early visual processing and is specifically associated with a deficient deactivation of the default mode network may provide a neural explanation for high-order cognitive deficits present in NF1, particularly visuospatial and attentional. A link between magnocellular and default mode network processing may generalize to neuropsychiatric disorders where such deficits have been separately identified.

Cytoarchitectonical analysis and probabilistic mapping of two extrastriate areas of the human posterior fusiform gyrus

The human extrastriate visual cortex comprises numerous functionally defined areas, which are not identified in the widely used cytoarchitectonical map of Brodmann. The ventral part of the extrastriate cortex is particularly devoted to the identification of visual objects, faces and word forms. We analyzed the region immediately antero-lateral to hOc4v in serially sectioned (20 μm) and cell body-stained human brains using a quantitative observer-independent cytoarchitectonical approach to further identify the anatomical organization of the extrastriate cortex. Two novel cytoarchitectonical areas, FG1 and FG2, were identified on the posterior fusiform gyrus. The results of ten postmortem brains were then registered to their MRI volumes (acquired before histological processing), 3D reconstructed, and spatially normalized to the Montreal Neurological Institute reference brain. Finally, probabilistic maps were generated for each cytoarchitectonical area by superimposing the areas of the individual brains in the reference space. Comparison with recent functional imaging studies yielded that both areas are located within the object-related visual cortex. FG1 fills the gap between the retinotopically mapped area VO-1 and a posterior fusiform face patch. FG2 is probably the correlate of this face patch.

Organization of the human inferior parietal lobule based on receptor architectonics

Human inferior parietal lobule (IPL) plays a key role in various cognitive functions. Its functional diversity, including attention, language, and action processing, is reflected by its structural segregation into 7 cytoarchitectonically distinct areas, each with characteristic connectivity patterns. We hypothesized that commonalities of the cytoarchitectonic, connectional, and functional diversity of the IPL should be reflected by a correlated transmitter receptor-based organization. Since the function of a cortical area requires a well-tuned receptor balance, the densities of 15 different receptors were measured in each IPL area. A hierarchical cluster analysis of the receptor balance revealed a tripartite segregation of the IPL into a rostral, middle, and caudal group. Comparison with other cortical areas showed strong similarities with Broca's region for all 3 groups, with the superior parietal cortex for the middle, and with extrastriate visual areas for the caudal group. Notably, caudal-most area PGp has a receptor fingerprint very similar to that of ventral extrastriate visual cortex. We therefore propose a new organizational model of the human IPL, consisting of 3 clusters, which corresponds to its known cytoarchitectonic, connectional, and functional diversity at the molecular level. This might reflect a general organizational principle of human IPL, beyond specific functional domains.

Co-activation patterns distinguish cortical modules, their connectivity and functional differentiation

The organization of the cerebral cortex into distinct modules may be described along several dimensions, most importantly, structure, connectivity and function. Identification of cortical modules by differences in whole-brain connectivity profiles derived from diffusion tensor imaging or resting state correlations has already been shown. These approaches, however, carry no task-related information. Hence, inference on the functional relevance of the ensuing parcellation remains tentative. Here, we demonstrate, that Meta-Analytic Connectivity Modeling (MACM) allows the delineation of cortical modules based on their whole-brain co-activation pattern across databased neuroimaging results. Using a model free approach, two regions of the medial pre-motor cortex, SMA and pre-SMA were differentiated solely based on their functional connectivity. Assessing the behavioral domain and paradigm class meta-data of the experiments associated with the clusters derived from the co-activation based parcellation moreover allows the identification of their functional characteristics. The ensuing hypotheses about functional differentiation and distinct functional connectivity between pre-SMA and SMA were then explicitly tested and confirmed in independent datasets using functional and resting state fMRI. Co-activation based parcellation thus provides a new perspective for identifying modules of functional connectivity and linking them to functional properties, hereby generating new and subsequently testable hypotheses about the organization of cortical modules.

Imaging retinotopic maps in the human brain

A quarter-century ago visual neuroscientists had little information about the number and organization of retinotopic maps in human visual cortex. The advent of functional magnetic resonance imaging (MRI), a non-invasive, spatially-resolved technique for measuring brain activity, provided a wealth of data about human retinotopic maps. Just as there are differences amongst non-human primate maps, the human maps have their own unique properties. Many human maps can be measured reliably in individual subjects during experimental sessions lasting less than an hour. The efficiency of the measurements and the relatively large amplitude of functional MRI signals in visual cortex make it possible to develop quantitative models of functional responses within specific maps in individual subjects. During this last quarter-century, there has also been significant progress in measuring properties of the human brain at a range of length and time scales, including white matter pathways, macroscopic properties of gray and white matter, and cellular and molecular tissue properties. We hope the next 25years will see a great deal of work that aims to integrate these data by modeling the network of visual signals. We do not know what such theories will look like, but the characterization of human retinotopic maps from the last 25years is likely to be an important part of future ideas about visual computations.

Microstructural Parcellation of the Human Cerebral Cortex - From Brodmann's Post-Mortem Map to in vivo Mapping with High-Field Magnetic Resonance Imaging

The year 2009 marked the 100th anniversary of the publication of the famous brain map of Korbinian Brodmann. Although a “classic” guide to microanatomical parcellation of the cerebral cortex, it is – from today's state-of-the-art neuroimaging perspective – problematic to use Brodmann's map as a structural guide to functional units in the cortex. In this article we discuss some of the reasons, especially the problematic compatibility of the “post-mortem world” of microstructural brain maps with the “in vivo world” of neuroimaging. We conclude with some prospects for the future of in vivo structural brain mapping: a new approach which has the enormous potential to make direct correlations between microstructure and function in living human brains: “in vivo Brodmann mapping” with high-field magnetic resonance imaging.

Gateways of ventral and dorsal streams in mouse visual cortex

It is widely held that the spatial processing functions underlying rodent navigation are similar to those encoding human episodic memory (Doeller et al., 2010). Spatial and nonspatial information are provided by all senses including vision. It has been suggested that visual inputs are fed to the navigational network in cortex and hippocampus through dorsal and ventral intracortical streams (Whitlock et al., 2008), but this has not been shown directly in rodents. We have used cytoarchitectonic and chemoarchitectonic markers, topographic mapping of receptive fields, and pathway tracing to determine in mouse visual cortex whether the lateromedial field (LM) and the anterolateral field (AL), which are the principal targets of primary visual cortex (V1) (Wang and Burkhalter, 2007) specialized for processing nonspatial and spatial visual information (Gao et al., 2006), are distinct areas with diverse connections. We have found that the LM/AL border coincides with a change in type 2 muscarinic acetylcholine receptor expression in layer 4 and with the representation of the lower visual field periphery. Our quantitative analyses also show that LM strongly projects to temporal cortex as well as the lateral entorhinal cortex, which has weak spatial selectivity (Hargreaves et al., 2005). In contrast, AL has stronger connections with posterior parietal cortex, motor cortex, and the spatially selective medial entorhinal cortex (Haftig et al., 2005). These results support the notion that LM and AL are architecturally, topographically, and connectionally distinct areas of extrastriate visual cortex and that they are gateways for ventral and dorsal streams.

Broca's region: novel organizational principles and multiple receptor mapping

There is a considerable contrast between the various functions assigned to Broca's region and its relatively simple subdivision into two cytoarchitectonic areas (44 and 45). Since the regional distribution of transmitter receptors in the cerebral cortex has been proven a powerful indicator of functional diversity, the subdivision of Broca's region was analyzed here using a multireceptor approach. The distribution patterns of six receptor types using in vitro receptor autoradiography revealed previously unknown areas: a ventral precentral transitional cortex 6r1, dorsal and ventral areas 44d and 44v, anterior and posterior areas 45a and 45p, and areas op8 and op9 in the frontal operculum. A significant lateralization of receptors was demonstrated with respect to the cholinergic M(2) receptor, particularly in area 44v+d. We propose a new concept of the anterior language region, which elucidates the relation between premotor cortex, prefrontal cortex, and Broca's region. It offers human brain homologues to the recently described subdivision of area 45, and the segregation of the ventral premotor cortex in macaque brains. The results provide a novel structural basis of the organization of language regions in the brain.

Multifocal frequency-doubling pattern visual evoked responses to dichoptic stimulation

OBJECTIVE

To examine the feasibility of a multifocal visual evoked potential (mfVEP) binocularly, using a variant of the multifocal frequency-doubling (FD) pattern-electroretinogram (MFP).

METHODS

Stimuli were presented in both monocular and dichoptic conditions at eight visual field locations/eye. The incommensurate stimulus frequencies ranged from 15.45 to 21.51 Hz. Five stimulus conditions differing in spatial frequency and orientation were examined for three viewing conditions. The resulting 15 stimulus conditions were examined in 16 normal subjects who repeated all conditions twice.

RESULTS

Several significant independent effects were identified. Response amplitudes were reduced for dichoptic viewing (by 0.85 times, p<4 x 10(-11)); offset by increases in responses for between eye differences of one octave of spatial frequency: lower (1.15 times, 0.1 cpd); higher (1.29 times, 0.4 cpd), both p<1.8 x 10(-7). Crossed orientations produced significant effects upon response phase (p=0.023) but not amplitude (p=0.062).

CONCLUSIONS

The results indicated that dichoptic evoked potentials using multifocal frequency-doubling illusion stimuli are practical. The use of crossed orientation, or differing spatial frequencies, in the two eyes reduced binocular interactions.

SIGNIFICANCE

The results indicate a method wherein several spatial or temporal and frequencies per visual field region can be tested in reasonable time using a multifocal VEP using spatial frequency-doubling stimuli.

Receptor architecture of human cingulate cortex: evaluation of the four-region neurobiological model

The structural and functional organization of the human cingulate cortex is an ongoing focus; however, human imaging studies continue to use the century-old Brodmann concept of a two region cingulate cortex. Recently, a four-region neurobiological model was proposed based on structural, circuitry, and functional imaging observations. It encompasses the anterior cingulate, midcingulate, posterior cingulate, and retrosplenial cortices (ACC, MCC, PCC, and RSC, respectively). For the first time, this study performs multireceptor autoradiography of 15 neurotransmitter receptor ligands and multivariate statistics on human whole brain postmortem samples covering the entire cingulate cortex. We evaluated the validity of Brodmann's duality concept and of the four-region model using a hierarchical clustering analysis of receptor binding according to the degree of similarity of each area's receptor architecture. We could not find support for Brodmann's dual cingulate concept, because the anterior part of his area 24 has significantly higher AMPA, kainate, GABA(B), benzodiazepine, and M(3) but lower NMDA and GABA(A) binding site densities than the posterior part. The hierarchical clustering analysis distinguished ACC, MCC, PCC, and RSC as independent regions. The ACC has highest AMPA, kainate, alpha(2), 5-HT(1A), and D(1) but lowest GABA(A) densities. The MCC has lowest AMPA, kainate, alpha(2), and D(1) densities. Area 25 in ACC is similar in receptor-architecture to MCC, particularly the NMDA, GABA(A), GABA(B), and M(2) receptors. The PCC and RSC differ in the higher M(1) and alpha(1) but lower M(3) densities of PCC. Thus, multireceptor autoradiography supports the four-region neurobiological model of the cingulate cortex.

Receptor mapping: architecture of the human cerebral cortex

PURPOSE OF REVIEW

Cytoarchitectonical brain mapping is of growing interest as a powerful tool for localization of activated brain regions in functional neuroimaging. Mapping of neurotransmitter receptors can provide novel molecular and functionally relevant information to the available cytoarchitectonical brain maps, because receptors are key molecules of neurotransmission. This review highlights the relation between cytoarchitectonical parcellations and the regionally inhomogeneous distribution of receptors. It will demonstrate the potential of receptor mapping for novel and functionally relevant insights into the regional organization of the human cortex.

RECENT FINDINGS

Mapping of a single receptor type can already reveal borders of functionally and cytoarchitectonically distinct cortical regions. The combined mapping of various receptors in each cortical area (receptor fingerprint) represents the balance between different neurotransmitter systems and often reveals hitherto unknown parcellations. Different brain regions are identified as parts of distinct functional systems.

SUMMARY

Receptor mapping of the human brain, particularly multireceptor mapping, provides a novel and multimodal view of its anatomical, functional and molecular organization. It reveals organizational principles of the segregation of cortical and subcortical structures. It improves our understanding of the brain's architecture beyond the limits of cytoarchitectonics and serves as a basis for clinical and pharmacological studies of brain diseases.