Hierarchical modularity in human brain functional networks

The idea that complex systems have a hierarchical modular organization originates in the early 1960s and has recently attracted fresh support from quantitative studies of large scale, real-life networks. Here we investigate the hierarchical modular (or "modules-within-modules") decomposition of human brain functional networks, measured using functional magnetic resonance imaging (fMRI) in 18 healthy volunteers under no-task or resting conditions. We used a customized template to extract networks with more than 1800 regional nodes, and we applied a fast algorithm to identify nested modular structure at several hierarchical levels. We used mutual information, 0 < I < 1, to estimate the similarity of community structure of networks in different subjects, and to identify the individual network that is most representative of the group. Results show that human brain functional networks have a hierarchical modular organization with a fair degree of similarity between subjects, I=0.63. The largest 5 modules at the highest level of the hierarchy were medial occipital, lateral occipital, central, parieto-frontal and fronto-temporal systems; occipital modules demonstrated less sub-modular organization than modules comprising regions of multimodal association cortex. Connector nodes and hubs, with a key role in inter-modular connectivity, were also concentrated in association cortical areas. We conclude that methods are available for hierarchical modular decomposition of large numbers of high resolution brain functional networks using computationally expedient algorithms. This could enable future investigations of Simon's original hypothesis that hierarchy or near-decomposability of physical symbol systems is a critical design feature for their fast adaptivity to changing environmental conditions

Adolescent tuning of association cortex in human structural brain networks

Motivated by prior data on local cortical shrinkage and intracortical myelination, we predicted age-related changes in topological organization of cortical structural networks during adolescence. We estimated structural correlation from magnetic resonance imaging measures of cortical thickness at 308 regions in a sample of N = 297 healthy participants, aged 14–24 years. We used a novel sliding-window analysis to measure age-related changes in network attributes globally, locally and in the context of several community partitions of the network. We found that the strength of structural correlation generally decreased as a function of age. Association cortical regions demonstrated a sharp decrease in nodal degree (hubness) from 14 years, reaching a minimum at approximately 19 years, and then levelling off or even slightly increasing until 24 years. Greater and more prolonged age-related changes in degree of cortical regions within the brain network were associated with faster rates of adolescent cortical myelination and shrinkage. The brain regions that demonstrated the greatest age-related changes were concentrated within prefrontal modules. We conclude that human adolescence is associated with biologically plausible changes in structural imaging markers of brain network organization, consistent with the concept of tuning or consolidating anatomical connectivity between frontal cortex and the rest of the connectom

Houses of the Living: Domestic Architecture in England and Wales, 4000-1500 BC

This thesis explores the changes that occurred in domestic architecture in England and Wales over the course of the Neolithic until the start of the Middle Bronze Age (c.4000-1500 BC), from the possible longhouses of the Early Neolithic until the emergence of the roundhouse tradition in the Early Bronze Age. While analysis of monumental architecture has dominated studies of the built environment during this period, the study of domestic architecture has remained far more limited, despite widespread recognition of the important social roles fulfilled by domestic structures. This thesis redresses this balance by considering the ways in which domestic structures also shaped (and were shaped by) ways of living in the Neolithic to Early Bronze Age. This project provides an upto-date dataset that quantifies the number of excavated structures dating to the Neolithic to Early Bronze Age for the first time in several decades, identifying 235 structures from 138 sites across England and Wales. The ways in which these structures were built, inhabited, and abandoned is explored in depth, building a highly detailed picture of the changing architectural traditions of the Neolithic to Early Bronze Age. Possible connections to wider spheres of human life are considered, notably links to changing monumental traditions, prevailing subsistence practices and wider changes in material culture. While several key trends in construction are recorded, this study highlights the considerable diversity in the building practices of the period between 4000-1500 BC across much of England and Wales

Examining associations between second-hand smoke exposure in early childhood, respitory disease, and anxiety in adolescence

This item is only available electronically.Report (B.PsychSc(Hons)) -- University of Adelaide, School of Psychology, 202

Network Scaling Effects in Graph Analytic Studies of Human Resting-State fMRI Data

Graph analysis has become an increasingly popular tool for characterizing topological properties of brain connectivity networks. Within this approach, the brain is modeled as a graph comprising N nodes connected by M edges. In functional magnetic resonance imaging (fMRI) studies, the nodes typically represent brain regions and the edges some measure of interaction between them. These nodes are commonly defined using a variety of regional parcellation templates, which can vary both in the volume sampled by each region, and the number of regions parcellated. Here, we sought to investigate how such variations in parcellation templates affect key graph analytic measures of functional brain organization using resting-state fMRI in 30 healthy volunteers. Seven different parcellation resolutions (84, 91, 230, 438, 890, 1314, and 4320 regions) were investigated. We found that gross inferences regarding network topology, such as whether the brain is small-world or scale-free, were robust to the template used, but that both absolute values of, and individual differences in, specific parameters such as path length, clustering, small-worldness, and degree distribution descriptors varied considerably across the resolutions studied. These findings underscore the need to consider the effect that a specific parcellation approach has on graph analytic findings in human fMRI studies, and indicate that results obtained using different templates may not be directly comparable

Efficiency and Cost of Economical Brain Functional Networks

Brain anatomical networks are sparse, complex, and have economical small-world properties. We investigated the efficiency and cost of human brain functional networks measured using functional magnetic resonance imaging (fMRI) in a factorial design: two groups of healthy old (N = 11; mean age = 66.5 years) and healthy young (N = 15; mean age = 24.7 years) volunteers were each scanned twice in a no-task or “resting” state following placebo or a single dose of a dopamine receptor antagonist (sulpiride 400 mg). Functional connectivity between 90 cortical and subcortical regions was estimated by wavelet correlation analysis, in the frequency interval 0.06–0.11 Hz, and thresholded to construct undirected graphs. These brain functional networks were small-world and economical in the sense of providing high global and local efficiency of parallel information processing for low connection cost. Efficiency was reduced disproportionately to cost in older people, and the detrimental effects of age on efficiency were localised to frontal and temporal cortical and subcortical regions. Dopamine antagonism also impaired global and local efficiency of the network, but this effect was differentially localised and did not interact with the effect of age. Brain functional networks have economical small-world properties—supporting efficient parallel information transfer at relatively low cost—which are differently impaired by normal aging and pharmacological blockade of dopamine transmission

Facial emotion processing in schizophrenia : a non-specific neuropsychological deficit?

Original article can be found at : http://journals.cambridge.org/ Copyright Cambridge University PressBackground: Identification of facial emotions has been found to be impaired in schizophrenia but there are uncertainties about the neuropsychological specificity of the finding. Method: Twenty-two patients with schizophrenia and 20 healthy controls were given tests requiring identification of facial emotion, judgement of the intensity of emotional expressions without identification, familiar face recognition and the Benton Facial Recognition Test (BFRT). The schizophrenia patients were selected to be relatively intellectually preserved. Results: The patients with schizophrenia showed no deficit in identifying facial emotion, although they were slower than the controls. They were, however, impaired on judging the intensity of emotional expression without identification. They showed impairment in recognizing familiar faces but not on the BFRT. Conclusions: When steps are taken to reduce the effects of general intellectual impairment, there is no deficit in identifying facial emotions in schizophrenia. There may, however, be a deficit in judging emotional intensity. The impairment found in naming familiar faces is consistent with other evidence of semantic memory impairment in the disorder.Peer reviewe

Change detection in children with autism: an auditory event-related fMRI study

Autism involves impairments in communication and social interaction, as well as high levels of repetitive, stereotypic and ritualistic behaviours, and extreme resistance to change. This latter dimension, whilst required for a diagnosis, has received less research attention. We hypothesise that this extreme resistance to change in autism is rooted in atypical processing of unexpected stimuli. We tested this using auditory event-related fMRI to determine regional brain activity associated with passive detection of infrequently occurring frequency-deviant and complex novel sounds in a no-task condition. Participants were twelve 10 to 15-year-old children with autism, and a group of 12 age- and sex-matched healthy controls

Statistical Analysis of Tract-Tracing Experiments Demonstrates a Dense, Complex Cortical Network in the Mouse.

Anatomical tract tracing methods are the gold standard for estimating the weight of axonal connectivity between a pair of pre-defined brain regions. Large studies, comprising hundreds of experiments, have become feasible by automated methods. However, this comes at the cost of positive-mean noise making it difficult to detect weak connections, which are of particular interest as recent high resolution tract-tracing studies of the macaque have identified many more weak connections, adding up to greater connection density of cortical networks, than previously recognized. We propose a statistical framework that estimates connectivity weights and credibility intervals from multiple tract-tracing experiments. We model the observed signal as a log-normal distribution generated by a combination of tracer fluorescence and positive-mean noise, also accounting for injections into multiple regions. Using anterograde viral tract-tracing data provided by the Allen Institute for Brain Sciences, we estimate the connection density of the mouse intra-hemispheric cortical network to be 73% (95% credibility interval (CI): 71%, 75%); higher than previous estimates (40%). Inter-hemispheric density was estimated to be 59% (95% CI: 54%, 62%). The weakest estimable connections (about 6 orders of magnitude weaker than the strongest connections) are likely to represent only one or a few axons. These extremely weak connections are topologically more random and longer distance than the strongest connections, which are topologically more clustered and shorter distance (spatially clustered). Weak links do not substantially contribute to the global topology of a weighted brain graph, but incrementally increased topological integration of a binary graph. The topology of weak anatomical connections in the mouse brain, rigorously estimable down to the biological limit of a single axon between cortical areas in these data, suggests that they might confer functional advantages for integrative information processing and/or they might represent a stochastic factor in the development of the mouse connectome.Netherlands Organisation for Scientific Research (Rubicon Fellowship), National Institute of Health Research (NIHR) Cambridge Biomedical Research CentreThis is the final version of the article. It first appeared from the Public Library of Science via http://dx.doi.org/10.1371/journal.pcbi.100510

Small-World Brain Networks Revisited.

It is nearly 20 years since the concept of a small-world network was first quantitatively defined, by a combination of high clustering and short path length; and about 10 years since this metric of complex network topology began to be widely applied to analysis of neuroimaging and other neuroscience data as part of the rapid growth of the new field of connectomics. Here, we review briefly the foundational concepts of graph theoretical estimation and generation of small-world networks. We take stock of some of the key developments in the field in the past decade and we consider in some detail the implications of recent studies using high-resolution tract-tracing methods to map the anatomical networks of the macaque and the mouse. In doing so, we draw attention to the important methodological distinction between topological analysis of binary or unweighted graphs, which have provided a popular but simple approach to brain network analysis in the past, and the topology of weighted graphs, which retain more biologically relevant information and are more appropriate to the increasingly sophisticated data on brain connectivity emerging from contemporary tract-tracing and other imaging studies. We conclude by highlighting some possible future trends in the further development of weighted small-worldness as part of a deeper and broader understanding of the topology and the functional value of the strong and weak links between areas of mammalian cortex.DSB acknowledges support from the John D. and Catherine T. MacArthur Foundation, the Alfred P. Sloan Foundation, the Army Research Laboratory and the Army Research Office through contract numbers W911NF-10-2-0022 and W911NF-14-1-0679, the National Institute of Health (2-R01-DC-009209-11, 1R01HD086888-01, R01-MH107235, R01-MH107703, and R21-M MH-106799), the Office of Naval Research, and the National Science Foundation (BCS-1441502, CAREER PHY-1554488, and BCS-1631550).This is the final version of the article. It first appeared from Sage at http://dx.doi.org/10.1177/1073858416667720