Hierarchical Complexity of the Adult Human Structural Connectome

AbstractThe structural network of the human brain has a rich topology which many have sought to characterise using standard network science measures and concepts. However, this characterisation remains incomplete and the non-obvious features of this topology have largely confounded attempts towards comprehensive constructive modelling. This calls for new perspectives. Hierarchical complexity is an emerging paradigm of complex network topology based on the observation that complex systems are composed of hierarchies within which the roles of hierarchically equivalent nodes display highly variable connectivity patterns. Here we test the hierarchical complexity of the human structural connectomes of a group of seventy-nine healthy adults. Binary connectomes are found to be more hierarchically complex than three benchmark random network models. This provides a new key description of brain structure, revealing a rich diversity of connectivity patterns within hierarchically equivalent nodes. Dividing the connectomes into four tiers based on degree magnitudes indicates that the most complex nodes are neither those with the highest nor lowest degrees but are instead found in the middle tiers. Spatial mapping of the brain regions in each hierarchical tier reveals consistency with the current anatomical, functional and neuropsychological knowledge of the human brain. The most complex tier (Tier 3) involves regions believed to bridge high-order cognitive (Tier 1) and low-order sensorimotor processing (Tier 2). We then show that such diversity of connectivity patterns aligns with the diversity of functional roles played out across the brain, demonstrating that hierarchical complexity can characterise functional diversity strictly from the network topology.

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Large-scale network integration in the human brain tracks temporal fluctuations in memory encoding performance

eLife ◽

10.7554/elife.32696 ◽

2018 ◽

Vol 7 ◽

Cited By ~ 4

Author(s):

Ruedeerat Keerativittayayut ◽

Ryuta Aoki ◽

Mitra Taghizadeh Sarabi ◽

Koji Jimura ◽

Kiyoshi Nakahara

Keyword(s):

Functional Connectivity ◽

Human Brain ◽

Large Scale ◽

Brain Regions ◽

Brain Network ◽

Time Varying ◽

Memory Encoding ◽

Graph Metrics ◽

Connectivity Patterns ◽

Network States

Although activation/deactivation of specific brain regions has been shown to be predictive of successful memory encoding, the relationship between time-varying large-scale brain networks and fluctuations of memory encoding performance remains unclear. Here, we investigated time-varying functional connectivity patterns across the human brain in periods of 30–40 s, which have recently been implicated in various cognitive functions. During functional magnetic resonance imaging, participants performed a memory encoding task, and their performance was assessed with a subsequent surprise memory test. A graph analysis of functional connectivity patterns revealed that increased integration of the subcortical, default-mode, salience, and visual subnetworks with other subnetworks is a hallmark of successful memory encoding. Moreover, multivariate analysis using the graph metrics of integration reliably classified the brain network states into the period of high (vs. low) memory encoding performance. Our findings suggest that a diverse set of brain systems dynamically interact to support successful memory encoding.

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Hierarchical Complexity of the Macro-Scale Neonatal Brain

Cerebral Cortex ◽

10.1093/cercor/bhaa345 ◽

2020 ◽

Author(s):

Manuel Blesa ◽

Paola Galdi ◽

Simon R Cox ◽

Gemma Sullivan ◽

David Q Stoye ◽

...

Keyword(s):

Functional Specialization ◽

Newborn Period ◽

Diverse Range ◽

Sensorimotor Processing ◽

Macro Scale ◽

Hierarchical Complexity ◽

Connectivity Patterns ◽

Cognitive Information ◽

The Brain ◽

Atypical Brain Development

Abstract The human adult structural connectome has a rich nodal hierarchy, with highly diverse connectivity patterns aligned to the diverse range of functional specializations in the brain. The emergence of this hierarchical complexity in human development is unknown. Here, we substantiate the hierarchical tiers and hierarchical complexity of brain networks in the newborn period, assess correspondences with hierarchical complexity in adulthood, and investigate the effect of preterm birth, a leading cause of atypical brain development and later neurocognitive impairment, on hierarchical complexity. We report that neonatal and adult structural connectomes are both composed of distinct hierarchical tiers and that hierarchical complexity is greater in term born neonates than in preterms. This is due to diversity of connectivity patterns of regions within the intermediate tiers, which consist of regions that underlie sensorimotor processing and its integration with cognitive information. For neonates and adults, the highest tier (hub regions) is ordered, rather than complex, with more homogeneous connectivity patterns in structural hubs. This suggests that the brain develops first a more rigid structure in hub regions allowing for the development of greater and more diverse functional specialization in lower level regions, while connectivity underpinning this diversity is dysmature in infants born preterm.

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Associations of Vitamin D and Vitamin K and Their Metabolites Across Four Regions of the Human Brain: The Memory and Aging Project (MAP) (FS05-02-19)

Current Developments in Nutrition ◽

10.1093/cdn/nzz052.fs05-02-19 ◽

2019 ◽

Vol 3 (Supplement_1) ◽

Author(s):

Xueyan Fu ◽

Will Patterson ◽

Gregory Dolnikowski ◽

Bess Dawson-Hughes ◽

Martha Morris ◽

...

Keyword(s):

Vitamin D ◽

Human Brain ◽

Vitamin K ◽

Vitamin D3 ◽

Rank Order ◽

Temporal Cortex ◽

Correlation Coefficients ◽

Brain Regions ◽

Multiple Regions ◽

The Brain

Abstract Objectives Very little is known about the forms of vitamin D and vitamin K in the human brain. The objective of this study is to evaluate concentrations of vitamin D and vitamin K forms in human brain and their correlations across four human brain regions. Methods Vitamin D [D3, 25(OH)D and 1,25(OH)2D] and vitamin K [phylloquinone and menaquinone-4 (MK4)] concentrations were measured by LC/MS/MS and HPLC, respectively, in four brain regions from post-mortem samples obtained from participants in the Rush Memory and Aging Project (n = 130, mean age 82 yrs, 81% female). The brain regions analyzed were the mid-frontal cortex (MF) and mid-temporal cortex (MT) [two regions important for memory in Alzheimer's Disease (AD)], the cerebellum (CR, a region not affected by AD), and the anterior watershed white matter (AWS, a region associated with vascular disease). The correlations among the vitamin forms across brain regions were calculated using Spearman rank order correlation coefficients. Significance was set at P < 0.001. Results The average concentrations of vitamin D3, 25(OH)D and MK4 were 604 pg/g, 535 pg/g, and 3.4 pmol/g, respectively. 25(OH)D and MK4 were detected in >95% of the brain samples. Nearly 92% of 1,25(OH)2D and 80% of phylloquinone samples had concentrations below the limit of assay detection (LOD) 1,25(OH)2D = 20 ng/g, phylloquinone = 0.1 pmol/g). Vitamin D3 and 25(OH)D concentrations were positively correlated across all four regions (all Spearman r ≥ 0.78, P < 0.0001). The 1,25(OH)2D was significantly correlated between the MF and CR regions only (Spearman r = 0.30, P < 0.001, all other P ≥ 0.002). MK4 and PK were positively correlated across the four regions studied (MK4 all Spearman r ≥ 0.78, phylloquinone r ≥ 0.49, all P < 0.001). Conclusions To the best of our knowledge, this study is the first evaluation of the concentrations of vitamin D and vitamin K forms in multiple regions of the human brain. Overall, the vitamin D and vitamin K forms were each positively correlated across the four brain regions studied. Future studies are needed to clarify the roles of these nutrients in AD and dementia. Funding Sources National Institute of Aging.

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STAB: a spatio-temporal cell atlas of the human brain

Nucleic Acids Research ◽

10.1093/nar/gkaa762 ◽

2020 ◽

Vol 49 (D1) ◽

pp. D1029-D1037

Author(s):

Liting Song ◽

Shaojun Pan ◽

Zichao Zhang ◽

Longhao Jia ◽

Wei-Hua Chen ◽

...

Keyword(s):

Human Brain ◽

Single Cell ◽

Temporal Dynamics ◽

Cell Types ◽

Brain Regions ◽

Molecular Characteristics ◽

Great Effort ◽

Brain Functions ◽

Spatio Temporal ◽

The Brain

Abstract The human brain is the most complex organ consisting of billions of neuronal and non-neuronal cells that are organized into distinct anatomical and functional regions. Elucidating the cellular and transcriptome architecture underlying the brain is crucial for understanding brain functions and brain disorders. Thanks to the single-cell RNA sequencing technologies, it is becoming possible to dissect the cellular compositions of the brain. Although great effort has been made to explore the transcriptome architecture of the human brain, a comprehensive database with dynamic cellular compositions and molecular characteristics of the human brain during the lifespan is still not available. Here, we present STAB (a Spatio-Temporal cell Atlas of the human Brain), a database consists of single-cell transcriptomes across multiple brain regions and developmental periods. Right now, STAB contains single-cell gene expression profiling of 42 cell subtypes across 20 brain regions and 11 developmental periods. With STAB, the landscape of cell types and their regional heterogeneity and temporal dynamics across the human brain can be clearly seen, which can help to understand both the development of the normal human brain and the etiology of neuropsychiatric disorders. STAB is available at http://stab.comp-sysbio.org.

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Strategic Cognitive Sequencing: A Computational Cognitive Neuroscience Approach

Computational Intelligence and Neuroscience ◽

10.1155/2013/149329 ◽

2013 ◽

Vol 2013 ◽

pp. 1-18 ◽

Cited By ~ 5

Author(s):

Seth A. Herd ◽

Kai A. Krueger ◽

Trenton E. Kriete ◽

Tsung-Ren Huang ◽

Thomas E. Hazy ◽

...

Keyword(s):

Cognitive Process ◽

Network Models ◽

Brain Regions ◽

Human Cognition ◽

Neural Network Models ◽

Future Directions ◽

Error Learning ◽

Cognitive Actions ◽

Self Instruction ◽

The Brain

We address strategic cognitive sequencing, the “outer loop” of human cognition: how the brain decides what cognitive process to apply at a given moment to solve complex, multistep cognitive tasks. We argue that this topic has been neglected relative to its importance for systematic reasons but that recent work on how individual brain systems accomplish their computations has set the stage for productively addressing how brain regions coordinate over time to accomplish our most impressive thinking. We present four preliminary neural network models. The first addresses how the prefrontal cortex (PFC) and basal ganglia (BG) cooperate to perform trial-and-error learning of short sequences; the next, how several areas of PFC learn to make predictions of likely reward, and how this contributes to the BG making decisions at the level of strategies. The third models address how PFC, BG, parietal cortex, and hippocampus can work together to memorize sequences of cognitive actions from instruction (or “self-instruction”). The last shows how a constraint satisfaction process can find useful plans. The PFC maintains current and goal states and associates from both of these to find a “bridging” state, an abstract plan. We discuss how these processes could work together to produce strategic cognitive sequencing and discuss future directions in this area.

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Frequency-based brain networks: From a multiplex framework to a full multilayer description

Network Neuroscience ◽

10.1162/netn_a_00033 ◽

2018 ◽

Vol 2 (4) ◽

pp. 418-441 ◽

Cited By ~ 15

Author(s):

Javier M. Buldú ◽

Mason A. Porter

Keyword(s):

Brain Networks ◽

Network Models ◽

Real Data ◽

Laplacian Matrix ◽

Brain Regions ◽

Brain Diseases ◽

Multilayer Networks ◽

Frequency Bands ◽

Multiplex Network ◽

The Brain

We explore how to study dynamical interactions between brain regions by using functional multilayer networks whose layers represent different frequency bands at which a brain operates. Specifically, we investigate the consequences of considering the brain as (i) a multilayer network, in which all brain regions can interact with each other at different frequency bands; and as (ii) a multiplex network, in which interactions between different frequency bands are allowed only within each brain region and not between them. We study the second-smallest eigenvalue λ2 of the combinatorial supra-Laplacian matrix of both the multiplex and multilayer networks, as λ2 has been used previously as an indicator of network synchronizability and as a biomarker for several brain diseases. We show that the heterogeneity of interlayer edge weights and, especially, the fraction of missing edges crucially modify the value of λ2, and we illustrate our results with both synthetic network models and real data obtained from resting-state magnetoencephalography. Our work highlights the differences between using a multiplex approach and a full multilayer approach when studying frequency-based multilayer brain networks.

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Differential Expression of CD31 and Von Willebrand Factor on Endothelial Cells in Different Regions of the Human Brain: Potential Implications for Cerebral Malaria Pathogenesis

Brain Sciences ◽

10.3390/brainsci10010031 ◽

2020 ◽

Vol 10 (1) ◽

pp. 31 ◽

Cited By ~ 4

Author(s):

Smart Ikechukwu Mbagwu ◽

Luis Filgueira

Keyword(s):

Endothelial Cells ◽

Endothelial Cell ◽

Human Brain ◽

Expression Pattern ◽

Von Willebrand Factor ◽

Brain Regions ◽

And Function ◽

Von Willebrand ◽

Willebrand Factor ◽

The Brain

Cerebral microvascular endothelial cells (CMVECs) line the vascular system of the brain and are the chief cells in the formation and function of the blood brain barrier (BBB). These cells are heterogeneous along the cerebral vasculature and any dysfunctional state in these cells can result in a local loss of function of the BBB in any region of the brain. There is currently no report on the distribution and variation of the CMVECs in different brain regions in humans. This study investigated microcirculation in the adult human brain by the characterization of the expression pattern of brain endothelial cell markers in different brain regions. Five different brain regions consisting of the visual cortex, the hippocampus, the precentral gyrus, the postcentral gyrus, and the rhinal cortex obtained from three normal adult human brain specimens were studied and analyzed for the expression of the endothelial cell markers: cluster of differentiation 31 (CD31) and von-Willebrand-Factor (vWF) through immunohistochemistry. We observed differences in the expression pattern of CD31 and vWF between the gray matter and the white matter in the brain regions. Furthermore, there were also regional variations in the pattern of expression of the endothelial cell biomarkers. Thus, this suggests differences in the nature of vascularization in various regions of the human brain. These observations also suggest the existence of variation in structure and function of different brain regions, which could reflect in the pathophysiological outcomes in a diseased state.

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Multilayer Network Approach in EEG Motor Imagery with an Adaptive Threshold

Sensors ◽

10.3390/s21248305 ◽

2021 ◽

Vol 21 (24) ◽

pp. 8305

Author(s):

César Covantes-Osuna ◽

Jhonatan B. López ◽

Omar Paredes ◽

Hugo Vélez-Pérez ◽

Rebeca Romo-Vázquez

Keyword(s):

Motor Imagery ◽

Brain Connectivity ◽

Single Layer ◽

Network Models ◽

Brain Regions ◽

Adaptive Threshold ◽

Brain Network ◽

Multilayer Network ◽

Brain Models ◽

The Brain

The brain has been understood as an interconnected neural network generally modeled as a graph to outline the functional topology and dynamics of brain processes. Classic graph modeling is based on single-layer models that constrain the traits conveyed to trace brain topologies. Multilayer modeling, in contrast, makes it possible to build whole-brain models by integrating features of various kinds. The aim of this work was to analyze EEG dynamics studies while gathering motor imagery data through single-layer and multilayer network modeling. The motor imagery database used consists of 18 EEG recordings of four motor imagery tasks: left hand, right hand, feet, and tongue. Brain connectivity was estimated by calculating the coherence adjacency matrices from each electrophysiological band (δ, θ, α and β) from brain areas and then embedding them by considering each band as a single-layer graph and a layer of the multilayer brain models. Constructing a reliable multilayer network topology requires a threshold that distinguishes effective connections from spurious ones. For this reason, two thresholds were implemented, the classic fixed (average) one and Otsu’s version. The latter is a new proposal for an adaptive threshold that offers reliable insight into brain topology and dynamics. Findings from the brain network models suggest that frontal and parietal brain regions are involved in motor imagery tasks.

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Hemispheric Asymmetry of Human Brain Anatomical Network Revealed by Diffusion Tensor Tractography

BioMed Research International ◽

10.1155/2015/908917 ◽

2015 ◽

Vol 2015 ◽

pp. 1-11 ◽

Cited By ~ 7

Author(s):

Ni Shu ◽

Yaou Liu ◽

Yunyun Duan ◽

Kuncheng Li

Keyword(s):

Human Brain ◽

Large Scale ◽

Diffusion Tensor ◽

Functional Integration ◽

Brain Regions ◽

Hemispheric Asymmetries ◽

Characteristic Path Length ◽

Topological Measures ◽

Structural Connections ◽

The Brain

The topological architecture of the cerebral anatomical network reflects the structural organization of the human brain. Recently, topological measures based on graph theory have provided new approaches for quantifying large-scale anatomical networks. However, few studies have investigated the hemispheric asymmetries of the human brain from the perspective of the network model, and little is known about the asymmetries of the connection patterns of brain regions, which may reflect the functional integration and interaction between different regions. Here, we utilized diffusion tensor imaging to construct binary anatomical networks for 72 right-handed healthy adult subjects. We established the existence of structural connections between any pair of the 90 cortical and subcortical regions using deterministic tractography. To investigate the hemispheric asymmetries of the brain, statistical analyses were performed to reveal the brain regions with significant differences between bilateral topological properties, such as degree of connectivity, characteristic path length, and betweenness centrality. Furthermore, local structural connections were also investigated to examine the local asymmetries of some specific white matter tracts. From the perspective of both the global and local connection patterns, we identified the brain regions with hemispheric asymmetries. Combined with the previous studies, we suggested that the topological asymmetries in the anatomical network may reflect the functional lateralization of the human brain.

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Task-fMRI Group and Functional Connectivity Analysis of the Brain During Faradarmani Consciousness Field Connection

10.20944/preprints202109.0248.v1 ◽

2021 ◽

Author(s):

Mohammad Ali Taheri ◽

Sara Torabi ◽

Noushin Nabavi ◽

Fatemeh Modarresi-Asem ◽

Majid Abbasi Sisara ◽

...

Keyword(s):

Functional Connectivity ◽

Human Brain ◽

Frontal Lobe ◽

Critical Role ◽

Group Analysis ◽

Brain Regions ◽

Connectivity Analysis ◽

Functional Connectivity Analysis ◽

Cognitive Activities ◽

The Brain

Task fMRI has played a critical role in recognizing the specific functions of the different regions of human brain during various cognitive activities. This study aimed to investigate group analysis and functional connectivity in the Faradarmangars brain during the Faradarmani CF (FCF) connection. Using task functional MRI (task-fMRI), we attempted the identification of different activated and deactivated brain regions during the Consciousness Filed connection. Clusters that showed significant differences in peak intensity between task and rest group were selected as seeds for seed-voxel analysis. Connectivity of group differences in functional connectivity analysis was determined following each activation and deactivation network. In this study, we report the fMRI-based representation of the FCF connection at the human brain level. The group analysis of FCF connection task revealed activation of frontal lobe (BA6/BA10/BA11). Moreover, seed based functional connectivity analysis showed decreased connectivity within activated clusters and posterior Cingulate Gyrus (BA31). Moreover, we observed an increased connectivity within deactivated clusters and frontal lobe (BA11/BA47) during the FCF connection. Activation clusters as well as the increased and decreased connectivity between different regions of the brain during the FCF connection, firstly, validates the significant effect of the FCF and secondly, indicates a distinctive pattern of connection with this non-material and non-energetic field, in the brain.

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