Scalar connectivity measures from fast-marching tractography reveal heritability of white matter architecture

Recent advances in diffusion-weighted MRI (DWI) have enabled studies of complex white matter tissue architecture in vivo. To date, the underlying influence of genetic and environmental factors in determining central nervous system connectivity has not been widely studied. In this work, we introduce new scalar connectivity measures based on a computationally-efficient fast-marching algorithm for quantitative tractography. We then calculate connectivity maps for a DTI dataset from 92 healthy adult twins and decompose the genetic and environmental contributions to the variance in these metrics using structural equation models. By combining these techniques, we generate the first maps to directly examine genetic and environmental contributions to brain connectivity in humans. Our approach is capable of extracting statistically significant measures of genetic and environmental contributions to neural connectivity.

Investigating brain connectivity heritability in a twin study using diffusion imaging data

Heritability of brain anatomical connectivity has been studied with diffusion-weighted imaging (DWI) mainly by modeling each voxel's diffusion pattern as a tensor (e.g., to compute fractional anisotropy), but this method cannot accurately represent the many crossing connections present in the brain. We hypothesized that different brain networks (i.e., their component fibers) might have different heritability and we investigated brain connectivity using High Angular Resolution Diffusion Imaging (HARDI) in a cohort of twins comprising 328 subjects that included 70 pairs of monozygotic and 91 pairs of dizygotic twins. Water diffusion was modeled in each voxel with a Fiber Orientation Distribution (FOD) function to study heritability for multiple fiber orientations in each voxel. Precision was estimated in a test-retest experiment on a sub-cohort of 39 subjects. This was taken into account when computing heritability of FOD peaks using an ACE model on the monozygotic and dizygotic twins. Our results confirmed the overall heritability of the major white matter tracts but also identified differences in heritability between connectivity networks. Inter-hemispheric connections tended to be more heritable than intra-hemispheric and cortico-spinal connections. The highly heritable tracts were found to connect particular cortical regions, such as medial frontal cortices, postcentral, paracentral gyri, and the right hippocampus.

A functional MRI study of the relationship between naming treatment outcomes and resting state functional connectivity in post-stroke aphasia

Background: The majority of studies investigating the neural mechanisms underlying treatment in people with aphasia have examined task-based brain activity. However, the use of resting-state fMRI may provide another method of examining the brain mechanisms responsible for treatment-induced recovery, and allows for investigation into connectivity within complex functional networks Methods: Eight people with aphasia underwent 12 treatment sessions that aimed to improve object naming. Half the sessions employed a phonologically-based task, and half the sessions employed a semantic-based task, with resting-state fMRI conducted pre- and post-treatment. Brain regions in which the amplitude of low frequency fluctuations (ALFF) correlated with treatment outcomes were used as seeds for functional connectivity (FC) analysis. FC maps were compared from pre- to post-treatment, as well as with a group of 12 healthy older controls Results: Pre-treatment ALFF in the right middle temporal gyrus (MTG) correlated with greater outcomes for the phonological treatment, with a shift to the left MTG and supramarginal gyrus, as well as the right inferior frontal gyrus, post-treatment. When compared to controls, participants with aphasia showed both normalization and up-regulation of connectivity within language networks post-treatment, predominantly in the left hemisphere Conclusions: The results provide preliminary evidence that treatments for naming impairments affect the FC of language networks, and may aid in understanding the neural mechanisms underlying the rehabilitation of language post-stroke.

Changes in white matter connectivity following therapy for anomia post stroke

Background. The majority of studies investigating the neural mechanisms underlying treatment-induced recovery in aphasia have focused on the cortical regions associated with language processing. However, the integrity of the white matter connecting these regions may also be crucial to understanding treatment mechanisms. Objective. This study investigated the integrity of the arcuate fasciculus (AF) and uncinate fasciculus (UF) before and after treatment for anomia in people with aphasia. Method. Eight people with aphasia received 12 treatment sessions to improve naming; alternating between phonologically-based and semantic-based tasks, with high angular resolution diffusion imaging conducted pre and post treatment. The mean generalized fractional anisotropy (GFA), a measure of fiber integrity, and number of fibers in the AF and UF were compared pre and post treatment, as well as with a group of 14 healthy older controls. Results. Pre treatment, participants with aphasia had significantly fewer fibers and lower mean GFA in the left AF compared with controls. Post treatment, mean GFA increased in the left AF to be statistically equivalent to controls. Additionally, mean GFA in the left AF pre and post treatment positively correlated with maintenance of the phonologically based treatment. No differences were found in the right AF, or the UF in either hemisphere, between participants with aphasia and controls, and no changes were observed in these tracts following treatment. Conclusions. Anomia treatments may improve the integrity of the white matter connecting cortical language regions. These preliminary results add to the understanding of the mechanisms underlying treatment outcomes in people with aphasia post stroke.

High connectivity in rastrelliger kanagurta: Influence of historical signatures and migratory behaviour inferred from mtDNA Cytochrome b

Phylogeographic patterns and population structure of the pelagic Indian mackerel, Rastrelliger kanagurta were examined in 23 populations collected from the Indonesian-Malaysian Archipelago (IMA) and the West Indian Ocean (WIO). Despite the vast expanse of the IMA and neighbouring seas, no evidence for geographical structure was evident. An indication that R. kanagurta populations across this region are essentially panmictic. This study also revealed that historical isolation was insufficient for R. kanagurta to attain migration drift equilibrium. Two distinct subpopulations were detected between the WIO and the IMA (and adjacent populations); interpopulation genetic variation was high. A plausible explanation for the genetic differentiation observed between the IMA and WIO regions suggest historical isolation as a result of fluctuations in sea levels during the late Pleistocene. This occurrence resulted in the evolution of a phylogeographic break for this species to the north of the Andaman Sea.

Spatial variation in life history reveals insight into connectivity and geographic population structure of a tropical estuarine teleost: king threadfin, Polydactylus macrochir

Understanding the life history of exploited fish species is not only critical in developing stock assessments and productivity models, but has a dual function in the delineation of connectivity and geographical population structure. In this study, patterns in growth and length and age at sex change of Polydactylus macrochir, an ecologically and economically important protandrous estuarine teleost, were examined to provide preliminary information on the species' connectivity and geographic structure across northern Australia. Considerable variation in life history parameters was observed among the 18 locations sampled. Both unconstrained and constrained (t(0) = 0) estimates of von Bertalanffy growth function parameters differed significantly among all neighbouring locations with the exception of two locations in Queensland's east coast and two in Queensland's Gulf of Carpentaria waters, respectively. Comparisons of back-calculated length-at-age 2 provided additional evidence for growth differences among some locations, but were not significantly different among locations in the south-eastern Gulf of Carpentaria or on Queensland's east coast. The length and age at sex change differed markedly among locations, with fish from the east coast of Australia changing sex from males to females at significantly greater lengths and ages than elsewhere. Sex change occurred earliest at locations within Queensland's Gulf of Carpentaria, where a large proportion of small, young females were recorded. The observed differences suggest that P. macrochir likely form a number of geographically and/or reproductively distinct groups in Australian waters and suggest that future studies examining connectivity and geographic population structure of estuarine fishes will likely benefit from the inclusion of comparisons of life history parameters. (C) 2012 Elsevier B.V. All rights reserved.

Parasites as indicators of movement and population connectivity of a non-diadromous, tropical estuarine teleost: king threadfin Polydactylus macrochir

Temporal and spatial patterns in parasite assemblages were examined to evaluate the degree of movement and connectivity of post-recruitment life-history stages of a large, non-diadromous tropical estuarine teleost, king threadfin Polydactylus macrochir, collected from 18 locations across northern Australia. Ten parasites types (juvenile stages of two nematodes and seven cestodes, and adults of an acanthocephalan) were deemed to be suitable for use as biological tags, in that they were considered to have a long residence time in the fish, were relatively easy to find and were morphologically very different to each other which aided discrimination. Univariate and discriminant function analysis of these parasites revealed little difference in temporal replicates collected from five locations, suggesting that the parasite communities were stable over the timeframes explored. Univariate, discriminant function, and BrayCurtis similarity analyses indicated significant spatial heterogeneity, with BrayCurtis classification accuracies ranging from 55 to 100% for locations in north-western and northern Australia, 24 to 88% in the Gulf of Carpentaria, and 39 to 88% on the east coast of Queensland. Few differences were observed among locations separated by <200 km. The observed patterns of parasite infection are in agreement with concurrent studies of movement and connectivity of P. macrochir in that they indicate a complex population structure across northern Australia. These results should be considered when reviewing the management arrangements for this species.

Fish mediate high food web connectivity in the lower reaches of a tropical floodplain river

High levels of hydrological connectivity during seasonal flooding provide significant opportunities for movements of fish between rivers and their floodplains, estuaries and the sea, possibly mediating food web subsidies among habitats. To determine the degree of utilisation of food sources from different habitats in a tropical river with a short floodplain inundation duration (similar to 2 months), stable isotope ratios in fishes and their available food were measured from three habitats (inundated floodplain, dry season freshwater, coastal marine) in the lower reaches of the Mitchell River, Queensland (Australia). Floodplain food sources constituted the majority of the diet of large-bodied fishes (barramundi Lates calcarifer, catfish Neoarius graeffei) captured on the floodplain in the wet season and for gonadal tissues of a common herbivorous fish (gizzard shad Nematalosa come), the latter suggesting that critical reproductive phases are fuelled by floodplain production. Floodplain food sources also subsidised barramundi from the recreational fishery in adjacent coastal and estuarine areas, and the broader fish community from a freshwater lagoon. These findings highlight the importance of the floodplain in supporting the production of large fishes in spite of the episodic nature and relatively short duration of inundation compared to large river floodplains of humid tropical regions. They also illustrate the high degree of food web connectivity mediated by mobile fish in this system in the absence of human modification, and point to the potential consequences of water resource development that may reduce or eliminate hydrological connectivity between the river and its floodplain.

Crinkles in connectivity: combining genetics and other types of biological data to estimate movement and interbreeding between populations

Marine species generally have large population sizes, continuous distributions and high dispersal capacity. Despite this, they are often subdivided into separate populations, which are the basic units of fisheries management. For example, populations of some fisheries species across the deep water of the Timor Trench are genetically different, inferring minimal movement and interbreeding. When connectivity is higher than the Timor Trench example, but not so high that the populations become one, connectivity between populations is crinkled. Crinkled connectivity occurs when migration is above the threshold required to link populations genetically, but below the threshold for demographic links. In future, genetic estimates of connectivity over crinkled links could be uniquely combined with other data, such as estimates of population size and tagging and tracking data, to quantify demographic connectedness between these types of populations. Elasmobranch species may be ideal targets for this research because connectivity between populations is more likely to be crinkled than for finfish species. Fisheries stock-assessment models could be strengthened with estimates of connectivity to improve the strategic and sustainable harvesting of biological resources.

Inferring neuronal network connectivity from spike data: A temporal data mining approach

Understanding the functioning of a neural system in terms of its underlying circuitry is an important problem in neuroscience. Recent d evelopments in electrophysiology and imaging allow one to simultaneously record activities of hundreds of neurons. Inferring the underlying neuronal connectivity patterns from such multi-neuronal spike train data streams is a challenging statistical and computational problem. This task involves finding significant temporal patterns from vast amounts of symbolic time series data. In this paper we show that the frequent episode mining methods from the field of temporal data mining can be very useful in this context. In the frequent episode discovery framework, the data is viewed as a sequence of events, each of which is characterized by an event type and its time of occurrence and episodes are certain types of temporal patterns in such data. Here we show that, using the set of discovered frequent episodes from multi-neuronal data, one can infer different types of connectivity patterns in the neural system that generated it. For this purpose, we introduce the notion of mining for frequent episodes under certain temporal constraints; the structure of these temporal constraints is motivated by the application. We present algorithms for discovering serial and parallel episodes under these temporal constraints. Through extensive simulation studies we demonstrate that these methods are useful for unearthing patterns of neuronal network connectivity.

Heritability of the network architecture of intrinsic brain functional connectivity

The brain's functional network exhibits many features facilitating functional specialization, integration, and robustness to attack. Using graph theory to characterize brain networks, studies demonstrate their small-world, modular, and "rich-club" properties, with deviations reported in many common neuropathological conditions. Here we estimate the heritability of five widely used graph theoretical metrics (mean clustering coefficient (γ), modularity (Q), rich-club coefficient (ϕnorm), global efficiency (λ), small-worldness (σ)) over a range of connection densities (k=5-25%) in a large cohort of twins (N=592, 84 MZ and 89 DZ twin pairs, 246 single twins, age 23±2.5). We also considered the effects of global signal regression (GSR). We found that the graph metrics were moderately influenced by genetic factors h2 (γ=47-59%, Q=38-59%, ϕnorm=0-29%, λ=52-64%, σ=51-59%) at lower connection densities (≤15%), and when global signal regression was implemented, heritability estimates decreased substantially h2 (γ=0-26%, Q=0-28%, ϕnorm=0%, λ=23-30%, σ=0-27%). Distinct network features were phenotypically correlated (|r|=0.15-0.81), and γ, Q, and λ were found to be influenced by overlapping genetic factors. Our findings suggest that these metrics may be potential endophenotypes for psychiatric disease and suitable for genetic association studies, but that genetic effects must be interpreted with respect to methodological choices.

Genetic analysis of structural brain connectivity using DICCCOL models of diffusion MRI in 522 twins

Genetic and environmental factors affect white matter connectivity in the normal brain, and they also influence diseases in which brain connectivity is altered. Little is known about genetic influences on brain connectivity, despite wide variations in the brain's neural pathways. Here we applied the 'DICCCOL' framework to analyze structural connectivity, in 261 twin pairs (522 participants, mean age: 21.8 y ± 2.7SD). We encoded connectivity patterns by projecting the white matter (WM) bundles of all 'DICCCOLs' as a tracemap (TM). Next we fitted an A/C/E structural equation model to estimate additive genetic (A), common environmental (C), and unique environmental/error (E) components of the observed variations in brain connectivity. We found 44 'heritable DICCCOLs' whose connectivity was genetically influenced (α2>1%); half of them showed significant heritability (α2>20%). Our analysis of genetic influences on WM structural connectivity suggests high heritability for some WM projection patterns, yielding new targets for genome-wide association studies.

Understanding Connectivity between Groundwater Chemistry Data and Geological Stratigraphy via 3D Sub-surface Visualization and Analysis

This paper describes the 3D Water Chemistry Atlas - an open source, Web-based system that enables the three-dimensional (3D) sub-surface visualization of ground water monitoring data, overlaid on the local geological model. Following a review of existing technologies, the system adopts Cesium (an open source Web-based 3D mapping and visualization interface) together with a PostGreSQL/PostGIS database, for the technical architecture. In addition a range of the search, filtering, browse and analysis tools were developed that enable users to interactively explore the groundwater monitoring data and interpret it spatially and temporally relative to the local geological formations and aquifers via the Cesium interface. The result is an integrated 3D visualization system that enables environmental managers and regulators to assess groundwater conditions, identify inconsistencies in the data, manage impacts and risks and make more informed decisions about activities such as coal seam gas extraction, waste water extraction and re-use.

Analysis of connectivity map: Control to glutamate injured and phenobarbital treated neuronal network

We study the responses of a cultured neural network when it is exposed to epileptogenesis glutamate injury causing epilepsy and subsequent treatment with phenobarbital by constructing connectivity map of neurons using correlation matrix. This study is particularly useful in understanding the pharmaceutical drug induced changes in the neuronal network properties with insights into changes at the systems biology level. (C) 2010 American Institute of Physics. [doi:10.1063/1.3398025]