Structural subnetwork evolution across the life-span: rich-club, feeder, seeder

The impact of developmental and aging processes on brain connectivity and the connectome has been widely studied. Network theoretical measures and certain topological principles are computed from the entire brain, however there is a need to separate and understand the underlying subnetworks which contribute towards these observed holistic connectomic alterations. One organizational principle is the rich-club - a core subnetwork of brain regions that are strongly connected, forming a high-cost, high-capacity backbone that is critical for effective communication in the network. Investigations primarily focus on its alterations with disease and age. Here, we present a systematic analysis of not only the rich-club, but also other subnetworks derived from this backbone - namely feeder and seeder subnetworks. Our analysis is applied to structural connectomes in a normal cohort from a large, publicly available lifespan study. We demonstrate changes in rich-club membership with age alongside a shift in importance from 'peripheral' seeder to feeder subnetworks. Our results show a refinement within the rich-club structure (increase in transitivity and betweenness centrality), as well as increased efficiency in the feeder subnetwork and decreased measures of network integration and segregation in the seeder subnetwork. These results demonstrate the different developmental patterns when analyzing the connectome stratified according to its rich-club and the potential of utilizing this subnetwork analysis to reveal the evolution of brain architectural alterations across the life-span

A geometric network model of intrinsic grey-matter connectivity of the human brain

Network science provides a general framework for analysing the large-scale brain networks that naturally arise from modern neuroimaging studies, and a key goal in theoretical neuro- science is to understand the extent to which these neural architectures influence the dynamical processes they sustain. To date, brain network modelling has largely been conducted at the macroscale level (i.e. white-matter tracts), despite growing evidence of the role that local grey matter architecture plays in a variety of brain disorders. Here, we present a new model of intrinsic grey matter connectivity of the human connectome. Importantly, the new model incorporates detailed information on cortical geometry to construct ‘shortcuts’ through the thickness of the cortex, thus enabling spatially distant brain regions, as measured along the cortical surface, to communicate. Our study indicates that structures based on human brain surface information differ significantly, both in terms of their topological network characteristics and activity propagation properties, when compared against a variety of alternative geometries and generative algorithms. In particular, this might help explain histological patterns of grey matter connectivity, highlighting that observed connection distances may have arisen to maximise information processing ability, and that such gains are consistent with (and enhanced by) the presence of short-cut connections

Acquisition of a Unique Onshore/Offshore Geophysical and Geochemical Dataset in the Northern Malawi (Nyasa) Rift

The Study of Extension and maGmatism in Malawi aNd Tanzania (SEGMeNT) project acquired a comprehensive suite of geophysical and geochemical datasets across the northern Malawi (Nyasa) rift in the East Africa rift system. Onshore/offshore active and passive seismic data, long‐period and wideband magnetotelluric data, continuous Global Positioning System data, and geochemical samples were acquired between 2012 and 2016. This combination of data is intended to elucidate the sedimentary, crustal, and upper‐mantle architecture of the rift, patterns of active deformation, and the origin and age of rift‐related magmatism. A unique component of our program was the acquisition of seismic data in Lake Malawi, including seismic reflection, onshore/offshore wide‐angle seismic reflection/refraction, and broadband seismic data from lake‐bottom seismometers, a towed streamer, and a large towed air‐gun source

Coupled Growth and Division of Model Protocell Membranes

The generation of synthetic forms of cellular life requires solutions to the problem of how biological processes such as cyclic growth and division could emerge from purely physical and chemical systems. Small unilamellar fatty acid vesicles grow when fed with fatty acid micelles and can be forced to divide by extrusion, but this artificial division process results in significant loss of protocell contents during each division cycle. Here we describe a simple and efficient pathway for model protocell membrane growth and division. The growth of large multilamellar fatty acid vesicles fed with fatty acid micelles, in a solution where solute permeation across the membranes is slow, results in the transformation of initially spherical vesicles into long thread-like vesicles, a process driven by the transient imbalance between surface area and volume growth. Modest shear forces are then sufficient to cause the thread-like vesicles to divide into multiple daughter vesicles without loss of internal contents. In an environment of gentle shear, protocell growth and division are thus coupled processes. We show that model protocells can proceed through multiple cycles of reproduction. Encapsulated RNA molecules, representing a primitive genome, are distributed to the daughter vesicles. Our observations bring us closer to the laboratory synthesis of a complete protocell consisting of a self-replicating genome and a self-replicating membrane compartment. In addition, the robustness and simplicity of this pathway suggests that similar processes might have occurred under the prebiotic conditions of the early Earth.Exobiology Program (U.S.) (Grant EXB02- 0031-0018)United States. National Aeronautics and Space Administration (Exobiology Program) (Grant EXB02-0031-0018)Howard Hughes Medical Institute (Investigator

The Dynamics of Functional Brain Networks:Integrated Network States during Cognitive Task Performance

Higher brain function relies upon the ability to flexibly integrate information across specialized communities of brain regions, however it is unclear how this mechanism manifests over time. In this study, we use time-resolved network analysis of functional magnetic resonance imaging data to demonstrate that the human brain traverses between two functional states that maximize either segregation into tight-knit communities or integration across otherwise disparate neural regions. The integrated state enables faster and more accurate performance on a cognitive task, and is associated with dilations in pupil diameter, suggesting that ascending neuromodulatory systems may govern the transition between these alternative modes of brain function. Our data confirm a direct link between cognitive performance and the dynamic reorganization of the network structure of the brain.Comment: 38 pages, 4 figure

A latent class analysis of trauma based on a nationally representative sample of US adolescents

Purpose Traumatic events in adolescence rarely occur in isolation. Multiple traumatic experiences are prevalent, diverse and a well-established risk factor for mental health disorders. The aim of this study was to explore and explain the heterogeneity in trauma profiles in a nationally representative sample of US adolescents. Method Using latent class analysis, data on 10,123 adolescents aged between 13 and 18 from the National Comorbidity Survey Adolescent Supplement were examined. In addition, the relationships between the emergent classes and demographic and clinical variables were explored. Results A four-class solution was the best fit of adolescent trauma patterns, with classes labelled as low risk, sexual assault risk, non-sexual risk and high risk. When compared to the low risk class, those in the other classes were significantly more likely not to live with either biological parent, display symptoms indicative of mood and anxiety disorders, and to have higher rates of disorder comorbidity. Conclusions This provides evidence of four distinct groups of adolescents who have experienced a variety of traumas. Evidence demonstrates the increased risk of adolescents with a history of trauma meeting the diagnostic criteria for not only individual disorders but also comorbidity across disorde