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Weighted Stochastic Block Models of the Human Connectome across the Life Span.

ABSTRACT: The human brain can be described as a complex network of anatomical connections between distinct areas, referred to as the human connectome. Fundamental characteristics of connectome organization can be revealed using the tools of network science and graph theory. Of particular interest is the network's community structure, commonly identified by modularity maximization, where communities are conceptualized as densely intra-connected and sparsely inter-connected. Here we adopt a generative modeling approach called weighted stochastic block models (WSBM) that can describe a wider range of community structure topologies by explicitly considering patterned interactions between communities. We apply this method to the study of changes in the human connectome that occur across the life span (between 6-85 years old). We find that WSBM communities exhibit greater hemispheric symmetry and are spatially less compact than those derived from modularity maximization. We identify several network blocks that exhibit significant linear and non-linear changes across age, with the most significant changes involving subregions of prefrontal cortex. Overall, we show that the WSBM generative modeling approach can be an effective tool for describing types of community structure in brain networks that go beyond modularity.

SUBMITTER: Faskowitz J

PROVIDER: S-EPMC6115421 | biostudies-literature | 2018 Aug

REPOSITORIES: biostudies-literature

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Weighted Stochastic Block Models of the Human Connectome across the Life Span.

Faskowitz Joshua J Yan Xiaoran X Zuo Xi-Nian XN Sporns Olaf O

Scientific reports 20180829 1

The human brain can be described as a complex network of anatomical connections between distinct areas, referred to as the human connectome. Fundamental characteristics of connectome organization can be revealed using the tools of network science and graph theory. Of particular interest is the network's community structure, commonly identified by modularity maximization, where communities are conceptualized as densely intra-connected and sparsely inter-connected. Here we adopt a generative model ...[more]

PMID: 30158553

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Project description:ABSTRACT MAGWIRE, MICHAEL MAHLON. Mutations Increasing Drosophila melanogaster Life Span. (Under the direction of Trudy F. C. Mackay.) Better living conditions and advances in medicine have made it possible for humans to live considerably longer than before. This has uncovered many health problems associated with age. By identifying genes involved in the limitation of life span, we may better understand the processes that lead to aging. In model organisms, we can use mutagenesis to discover mutations that increase life span, and hence infer that the wild-type allele limits life span by some means. We have assessed longevity in a collection of 1332 co-isogenic gene-trap P-element insertion lines and determined changes in life span of each insert line relative to the corresponding control line. Significant lines were determined via two different methods of analysis: A 95% confidence interval was established based on deviations of the mutant life spans from the controls and Dunnett’s two tailed t-tests were used to examine differences between mutant and control in each individual block. Based on the 95% confidence interval, 139 inserts displayed an increase in life span and 194 inserts a decrease. Using Dunnett’s, 70 lines increased in life span, while 270 decreased in life span. An additional 48 increased longevity lines were close enough to meeting Dunnett’s criteria to be considered for additional investigation. Combining these two analyses, we chose 83 inserts associated with increased life span for a secondary screen using an additional twelve replicates. 58 of these lines remained significant. We have determined the P-element insertion site for 50 of these lines. Starvation resistance, chill coma recovery time and climbing activity were measured on the lines remaining significant after the the secondary screen to identify pleiotropic effects. A positive correlation was found for males between life span and starvation resistance as well as between life span and chill coma recovery. Females only displayed a correlation between life span and chill coma recovery, which was negative. None of the lines indicated increased fitness for all phenotypes, indicating there may be some type of trade-off. There also appears to be a lot of pleiotropic variation depending on background and sex. Ten of the lines, all with the same parental background, were chosen for a half-diallel cross to identify epistasis between the mutants. There were substantial epistatic interactions between all ten lines. Furthermore, males and females displayed vastly different patterns of epistasis, again indicating major differences in life span regulation between the sexes. Finally, a subset of seven of the lines used in the epistatic study, in addition to the corresponding parental control, were chosen for microarray analysis to look for possible pathways and novel genes involved in increasing life span. 1,996 probe sets were significant at a false discovery rate q-value threshold of q < 0.0001. Tukeys tests were carried out for these probe sets to determine how each of the seven mutant backgrounds differed compared to the control and each other. In addition, each mutant background was compared individually with the control to identify any changes in expression. Gene ontologies were determined for each of the lines to identify over-represented biological functions which would indicate possible longevity pathways. Dozens of pathways were suggested, including several novel pathways. Keywords: Genetic (P-element insertion) modification and comparison to control line

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Weighted Stochastic Block Models of the Human Connectome across the Life Span.

Publications

Weighted Stochastic Block Models of the Human Connectome across the Life Span.

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