Mapping the structure-function relationship along macroscale gradients in the human brain
Evan CollinsOmar ChishtiSami ObaïdHari McGrathAlex KingXilin ShenJagriti AroraXenophon PapademetrisR. Todd ConstableDennis D. SpencerHitten P. Zaveri
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Functional coactivation between human brain regions is partly explained by white matter connections; however, how the structure-function relationship varies by function remains unclear. Here, we reference large data repositories to compute maps of structure-function correspondence across hundreds of specific functions and brain regions. We use natural language processing to accurately predict structure-function correspondence for specific functions and to identify macroscale gradients across the brain that correlate with structure-function correspondence as well as cortical thickness. Our findings suggest structure-function correspondence unfolds along a sensory-fugal organizational axis, with higher correspondence in primary sensory and motor cortex for perceptual and motor functions, and lower correspondence in association cortex for cognitive functions. Our study bridges neuroscience and natural language to describe how structure-function coupling varies by region and function in the brain, offering insight into the diversity and evolution of neural network properties.Keywords:
Coactivation
Human brain
Brain mapping
Structure function
Abstract The human pulvinar is the largest thalamic area in terms of size and cortical connectivity. Although much is known about regional pulvinar structural anatomy, relatively little is known about pulvinar functional anatomy in humans. Cooccurrence of experimentally induced brain activity is a traditional metric used to establish interregional brain connectivity and forms the foundation of functional neuroimaging connectivity analyses. Because functional neuroimaging studies report task‐related coactivations within a standardized space, meta‐analysis of many whole‐brain studies can define the brain's interregional coactivation across many tasks. Such an analysis can also detect and define variations in functional coactivations within a particular region. Here we use coactivation profiles reported in ∼ 7,700 functional neuroimaging studies to parcellate and define the pulvinar's functional anatomy. Parcellation of the pulvinar's coactivation profile identified five clusters per pulvinar of distinct functional coactivation. These clusters showed a high degree of symmetry across hemispheres and correspondence with the human pulvinar's cytoarchitecture. We investigated the functional coactivation profiles of each resultant pulvinar cluster with meta‐analytic methods. By referencing existent neuroimaging and lesion‐deficit literature, these profiles make a case for regional pulvinar specialization within the larger human attention‐controlling network. Reference to this literature also informs specific hypotheses that can be tested in subsequent studies in healthy and clinical populations. Hum Brain Mapp 36:2417–2431, 2015 . © 2015 Wiley Periodicals, Inc.
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We present the new computerized Human Brain Atlas (HBA) for anatomical and functional mapping studies of the human brain. The HBA is based on many high-resolution magnetic resonance images of normal subjects and provides continuous updating of the mean shape and position of anatomical structures of the human brain. The structures are transformable by linear and nonlinear global and local transformations applied anywhere in 3-D pictures to fit the anatomical structures of individual brains, which, by reformatting, are transformed into a high-resolution standard anatomical format. The power of the HBA to reduce anatomical variations was evaluated on a randomized selection of anatomical landmarks in brains of 27 young normal male volunteers who were different from those on whom the standard brain was selected. The HBA, even when based only on standard brain surface and central structures, reduced interindividual anatomical variance to the level of the variance in structure position between the right and left hemisphere in individual brains. © 1994 Wiley-Liss, Inc.
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Understanding the interactions among different brain regions is fundamental to our understanding of brain function.Here we describe a complete map of functional connections in the human brain derived by an automatic meta-analysis of 825 neuroimaging articles, representing 3402 experiments.The likelihood of a functional connection between regions was estimated by studying the interdependence of their ''activity,'' as reported in each experiment, across all experiments.We obtained a dense coactivation map that recovers some fundamental principles of the brain's functional connectivity, such as the symmetric interhemispheric connections, and important functional networks, such as the fronto-parietal attention network, the resting state network and the motor network.
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Similarities between twins have been widely demonstrated, underscoring the remarkable influence of genetics across numerous traits. In this study, we explore the genetic underpinnings of the human brain by examining MRI data from the Queensland Twin Imaging study. Specifically, this study seeks to compare brain structure and function between twins and unrelated subjects, with an emphasis on describing the effects of genetic factors. To achieve these goals, we employed the source-based morphometry method to extract intrinsic components and elucidate recognizable patterns. Our results show that twins exhibit a higher degree of similarity in gray and white matter density compared with unrelated individuals. In addition, four distinct states of brain activity were identified using coactivation patterns analysis. Furthermore, twins demonstrated a greater degree of similarity in the temporal and spatial features of each state compared with unrelated subjects. Taken together, these results support the hypothesis that twins show greater similarity in both brain structure and dynamic functional brain activity. Further exploration of these methods may advance our understanding of the complex interplay between genes, environment, and brain networks.
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Abstract The original article to which this Erratum refers was published in the March 2005 issue of Human Brain Mapping Human Brain Mapping (2005) 24(3) 184–192 .
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The relationship between brain areal activity and the entire brain’s activity is unknown, and understanding this relationship is imperative for understanding the neural mechanisms of human brain function at systems level. The complex activity of human brains varies from area to area and from time to time across the whole brain. BOLD-fMRI measures this spatiotemporal activity at a large-scale systems level. The BOLD time signal of an area reflects a collective neuronal activity of over one million neurons under that area, and the temporal correlation of this time signal with that of every point in the brain yields a full spatial map that characterizes the entire brain’s functional co-activity (FC) relative to that area’s activity. Here we show a quantitative relationship between brain areal activity and the activity of the entire brain. The temporal correlation coefficient r of the signal time courses of two areas quantifies the degree of co-activity between the two areas, and the spatial correlation coefficient R of their corresponding two FC maps quantifies the co-activity between these two maps. We found that a modified sigmoid function quantified this R with r, i.e., Rr=1+ra−1−ra1+ra+1−ra, revealing a relationship between the activity of brain areas and that of the entire brain. The parameter a in this equation was found to be associated with the mean degree of the temporal co-activity among all brain areas, and its value was brain functional state dependent too. Our study demonstrated a novel approach for analyzing fMRI data to holistically characterize the entire brain’s activity quantitatively for any brain functional state in individual humans.
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An important issue in neuroscience is the characterization for the underlying architectures of complex brain networks. However, little is known about the network of anatomical connections in the human brain. Here, we investigated large-scale anatomical connection patterns of the human cerebral cortex using cortical thickness measurements from magnetic resonance images. Two areas were considered anatomically connected if they showed statistically significant correlations in cortical thickness and we constructed the network of such connections using 124 brains from the International Consortium for Brain Mapping database. Significant short- and long-range connections were found in both intra- and interhemispheric regions, many of which were consistent with known neuroanatomical pathways measured by human diffusion imaging. More importantly, we showed that the human brain anatomical network had robust small-world properties with cohesive neighborhoods and short mean distances between regions that were insensitive to the selection of correlation thresholds. Additionally, we also found that this network and the probability of finding a connection between 2 regions for a given anatomical distance had both exponentially truncated power-law distributions. Our results demonstrated the basic organizational principles for the anatomical network in the human brain compatible with previous functional networks studies, which provides important implications of how functional brain states originate from their structural underpinnings. To our knowledge, this study provides the first report of small-world properties and degree distribution of anatomical networks in the human brain using cortical thickness measurements.
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Abstract Neuroimaging provides a method to locate areas of the brain active when organisms perceive or respond to sensory events or carry out a wide variety of tasks. The methods have made it possible to examine where in the brain cognitive and emotional systems are located, thus providing new approaches to understanding normal and pathological human information processing. Positron emission tomography accomplishes this by detecting concentrations of radioactive oxygen, glucose, or neurotransmitter molecules in the brain. High‐density multichannel electrical activity recorded from the scalp electroencephalogram supplements important information about the time course of these neurophysiological events. Functional magnetic resonance imaging allows to measure the blood oxygenation level in the brain during carrying out a wide variety of tasks. Recent methodological advances are moving beyond the localisation of task‐related activations to functional connectivity of remote brain areas and detection of patterns of remote brain areas in a variety of states and tasks. Key Concepts: Neuroimaging provides methods to locate areas of the human brain that are active during certain tasks or behaviours. PET and functional MRI allow to map functional anatomy of the human brain noninvasively in healthy volunteers. Mapping electrical activity of the human brain can supply important additional information about the time course of these local brain activations in various tasks or behaviours. Later approaches to functional mapping of the human brain function by fMRI have focussed on the connectivity of remote brain areas. Newest approaches to the functional mapping of the human brain focus on multiple pattern recognition algorithms to try to characterise each task or behavioural act by a pattern or set of multiple remote brain areas active at the moment.
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Significance Understanding the structure and function of the human brain at a cellular level is a fundamental aim of neuroscience. Tremendous progress has been made in recent years based on different in vivo and ex vivo approaches, including major advances in brain MRI. However, uncertainties remain in determining how brain MRI measurements relate to the brain’s underlying cellular composition. In this paper we use a recently developed MRI technique, quantitative gradient recalled echo (qGRE), and information on gene profiles in the human brain available from the Allen Human Brain Atlas. We demonstrate that qGRE and related MRI techniques can be used to probe the underlying cellular composition of the human brain in vivo.
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