Network Structure Implied by Initial Axon Outgrowth in Rodent Cortex: Empirical Measurement and Models

The developmental mechanisms by which the network organization of the adult cortex is established are incompletely understood. Here we report on empirical data on the development of connections in hamster isocortex and use these data to parameterize a network model of early cortical connectivity. Using anterograde tracers at a series of postnatal ages, we investigate the growth of connections in the early cortical sheet and systematically map initial axon extension from sites in anterior (motor), middle (somatosensory) and posterior (visual) cortex. As a general rule, developing axons extend from all sites to cover relatively large portions of the cortical field that include multiple cortical areas. From all sites, outgrowth is anisotropic, covering a greater distance along the medial/lateral axis than along the anterior/posterior axis. These observations are summarized as 2-dimensional probability distributions of axon terminal sites over the cortical sheet. Our network model consists of nodes, representing parcels of cortex, embedded in 2-dimensional space. Network nodes are connected via directed edges, representing axons, drawn according to the empirically derived anisotropic probability distribution. The networks generated are described by a number of graph theoretic measurements including graph efficiency, node betweenness centrality and average shortest path length. To determine if connectional anisotropy helps reduce the total volume occupied by axons, we define and measure a simple metric for the extra volume required by axons crossing. We investigate the impact of different levels of anisotropy on network structure and volume. The empirically observed level of anisotropy suggests a good trade-off between volume reduction and maintenance of both network efficiency and robustness. Future work will test the model's predictions for connectivity in larger cortices to gain insight into how the regulation of axonal outgrowth may have evolved to achieve efficient and economical connectivity in larger brains

The immunopathology of human schistosomiasis-III: immunoglobulin isotype profiles and response to praziquantel

Immunoglobulin (Ig) isotype (IgG, IgG1, IgG2, IgG3, IgG4, IgM, IgD and IgE) levels were investigated, both pre- and post-treatment with praziquantel (PZQ), in 43 adults and children chronically infected with Schistosoma mansoni , by means of a two-site, isotype-specific immunoenzymometric assay. The patients were classified as responders (R) or non-responders (NR) on the basis of their circumoval precipitin test (COPT) results 12 months after treatment. In comparison with controls, pre-treatment R children showed significantly higher levels of IgG, IgG1, IgG4 (p<0.001) and IgE (p<0.01), and diminished IgG2 (p<0.05), while NR children showed significantly elevated levels only of IgE (p<0.05). Twelve months after therapy, R children maintained significantly lower levels of IgG2, but showed significantly decreased levels of IgG, IgG1, IgG4, and IgE, while the Ig isotype profile of NR children was unaltered. Adult R and NR showed similar isotype profiles before chemotherapy, with the exception of significantly elevated IgM levels in R. Twelve months after therapy, R adults showed significantly decreased levels of IgG, IgG1, and IgG4, while NR adults showed only diminshed IgG4 levels. These results reveal different Ig isotype profiles in untreated adults and children chronically infected with S. mansoni. The results further show that the pre-treatment Ig isotype profile may be significantly modified after an effective R to chemotherapy, accounted for by down regulation of the IgG1 isotype in association with negative seroconversion of the COPT in R patients. The COPT reaction has been associated with the highly specific egg glycoprotein antigen w1, which shows a significant reduction in reactivity six months after treatment. IgG1 may thus play a main role in the response against the w1 antigen

Rethinking segregation and integration: contributions of whole-brain modelling

The brain regulates information flow by balancing the segregation and integration of incoming stimuli to facilitate flexible cognition and behaviour. The topological features of brain networks--in particular, network communities and hubs--support this segregation and integration but do not provide information about how external inputs are processed dynamically (that is, over time). Experiments in which the consequences of selective inputs on brain activity are controlled and traced with great precision could provide such information. However, such strategies have thus far had limited success. By contrast, recent whole-brain computational modelling approaches have enabled us to start assessing the effect of input perturbations on brain dynamics in silico.G.D. is supported by the European Research Council (ERC) Advanced grant: DYSTRUCTURE (no. 295129), by the Spanish Research Project SAF2010-16085, by the FP7-ICT BrainScales and by the Brain Network Recovery Group through the James S. McDonnell Foundation. G.T. is supported by the Paul Allen Family Foundation and by the James S. McDonnell Foundation. M.B. is supported by the Mind Science Foundation. M.L.K. is supported by the ERC Consolidator grant: CAREGIVING (no. 615539) and by the TrygFonden Charitable Foundation. The authors thank P. Maquet for agreeing to share the previously published sleep and wakefulness functional MRI data for the purposes of this article