Bayesian optimization of large-scale biophysical networks

The relationship between structure and function in the human brain is well established, but not yet well characterised. Large-scale biophysical models allow us to investigate this relationship, by leveraging structural information (e.g. derived from diffusion tractography) in order to couple dynamical models of local neuronal activity into networks of interacting regions distributed across the cortex. In practice however, these models are difficult to parametrise, and their simulation is often delicate and computationally expensive. This undermines the experimental aspect of scientific modelling, and stands in the way of comparing different parametrisations, network architectures, or models in general, with confidence. Here, we advocate the use of Bayesian optimisation for assessing the capabilities of biophysical network models, given a set of desired properties (e.g. band-specific functional connectivity); and in turn the use of this assessment as a principled basis for incremental modelling and model comparison. We adapt an optimisation method designed to cope with costly, high-dimensional, non-convex problems, and demonstrate its use and effectiveness. Using five parameters controlling key aspects of our model, we find that this method is able to converge to regions of high functional similarity with real MEG data, with very few samples given the number of parameters, without getting stuck in local extrema, and while building and exploiting a map of uncertainty defined smoothly across the parameter space. We compare the results obtained using different methods of structural connectivity estimation from diffusion tractography, and find that one method leads to better simulations

Addressing future food demand in The Gambia: can increased crop productivity and climate change adaptation close the supply–demand gap?

With rising demand for food and the threats posed by climate change, The Gambia faces significant challenges in ensuring sufficient and nutritious food for its population. To address these challenges, there is a need to increase domestic food production while limiting deforestation and land degradation. In this study, we modified the FABLE Calculator, a food and land-use system model, to focus on The Gambia to simulate scenarios for future food demand and increasing domestic food production. We considered the impacts of climate change on crops, the adoption of climate change adaptation techniques, as well as the potential of enhanced fertiliser use and irrigation to boost crop productivity, and assessed whether these measures would be sufficient to meet the projected increase in food demand. Our results indicate that domestic food production on existing cropland will not be sufficient to meet national food demand by 2050, leading to a significant supply–demand gap. However, investments in fertiliser availability and the development of sustainable irrigation infrastructure, coupled with climate change adaptation strategies like the adoption of climate-resilient crop varieties and optimised planting dates, could halve this gap. Addressing the remaining gap will require additional strategies, such as increasing imports, expanding cropland, or prioritising the production of domestic food crops over export crops. Given the critical role imports play in The Gambia’s food supply, it is essential to ensure a robust flow of food imports by diversifying partners and addressing regional trade barriers. Our study highlights the urgent need for sustained investment and policy support to enhance domestic food production and food imports to secure sufficient and healthy food supplies amidst growing demand and climate change challenges

Long-Term Programming of Antigen-Specific Immunity from Gene Expression Signatures in the PBMC of Rhesus Macaques Immunized with an SIV DNA Vaccine

While HIV-1-specific cellular immunity is thought to be critical for the suppression of viral replication, the correlates of protection have not yet been determined. Rhesus macaques (RM) are an important animal model for the study and development of vaccines against HIV/AIDS. Our laboratory has helped to develop and study DNA-based vaccines in which recent technological advances, including genetic optimization and in vivo electroporation (EP), have helped to dramatically boost their immunogenicity. In this study, RMs were immunized with a DNA vaccine including individual plasmids encoding SIV gag, env, and pol alone, or in combination with a molecular adjuvant, plasmid DNA expressing the chemokine ligand 5 (RANTES), followed by EP. Along with standard immunological assays, flow-based activation analysis without ex vivo restimulation and high-throughput gene expression analysis was performed. Strong cellular immunity was induced by vaccination which was supported by all assays including PBMC microarray analysis that identified the up-regulation of 563 gene sequences including those involved in interferon signaling. Furthermore, 699 gene sequences were differentially regulated in these groups at peak viremia following SIVmac251 challenge. We observed that the RANTES-adjuvanted animals were significantly better at suppressing viral replication during chronic infection and exhibited a distinct pattern of gene expression which included immune cell-trafficking and cell cycle genes. Furthermore, a greater percentage of vaccine-induced central memory CD8+ T-cells capable of an activated phenotype were detected in these animals as measured by activation analysis. Thus, co-immunization with the RANTES molecular adjuvant followed by EP led to the generation of cellular immunity that was transcriptionally distinct and had a greater protective efficacy than its DNA alone counterpart. Furthermore, activation analysis and high-throughput gene expression data may provide better insight into mechanisms of viral control than may be observed using standard immunological assays

Unusual Polymorphisms in Human Immunodeficiency Virus Type 1 Associated with Nonprogressive Infection

Factors accounting for long-term nonprogression may include infection with an attenuated strain of human immunodeficiency virus type 1 (HIV-1), genetic polymorphisms in the host, and virus-specific immune responses. In this study, we examined eight individuals with nonprogressing or slowly progressing HIV-1 infection, none of whom were homozygous for host-specific polymorphisms (CCR5-Δ32, CCR2-64I, and SDF-1-3\u27A) which have been associated with slower disease progression. HIV-1 was recovered from seven of the eight, and recovered virus was used for sequencing the full-length HIV-1 genome; full-length HIV-1 genome sequences from the eighth were determined following amplification of viral sequences directly from peripheral blood mononuclear cells (PBMC). Longitudinal studies of one individual with HIV-1 that consistently exhibited a slow/low growth phenotype revealed a single amino acid deletion in a conserved region of the gp41 transmembrane protein that was not seen in any of 131 envelope sequences in the Los Alamos HIV-1 sequence database. Genetic analysis also revealed that five of the eight individuals harbored HIV-1 with unusual 1- or 2-amino-acid deletions in the Gag sequence compared to subgroup B Gag consensus sequences. These deletions in Gag have either never been observed previously or are extremely rare in the database. Three individuals had deletions in Nef, and one had a 4-amino-acid insertion in Vpu. The unusual polymorphisms in Gag, Env, and Nef described here were also found in stored PBMC samples taken 3 to 11 years prior to, or in one case 4 years subsequent to, the time of sampling for the original sequencing. In all, seven of the eight individuals exhibited one or more unusual polymorphisms; a total of 13 unusual polymorphisms were documented in these seven individuals. These polymorphisms may have been present from the time of initial infection or may have appeared in response to immune surveillance or other selective pressures. Our results indicate that unusual, difficult-to-revert polymorphisms in HIV-1 can be found associated with slow progression or nonprogression in a majority of such cases

A biophysical model of dynamic balancing of excitation and inhibition in fast oscillatory large-scale networks

Over long timescales, neuronal dynamics can be robust to quite large perturbations, such as changes in white matter connectivity and grey matter structure through processes including learning, aging, development and certain disease processes. One possible explanation is that robust dynamics are facilitated by homeostatic mechanisms that can dynamically rebalance brain networks. In this study, we simulate a cortical brain network using the Wilson-Cowan neural mass model with conduction delays and noise, and use inhibitory synaptic plasticity (ISP) to dynamically achieve a spatially local balance between excitation and inhibition. Using MEG data from 55 subjects we find that ISP enables us to simultaneously achieve high correlation with multiple measures of functional connectivity, including amplitude envelope correlation and phase locking. Further, we find that ISP successfully achieves local E/I balance, and can consistently predict the functional connectivity computed from real MEG data, for a much wider range of model parameters than is possible with a model without ISP

Leveraging analytics to produce compelling and profitable film content

Producing compelling film content profitably is a top priority to the long-term prosperity of the film industry. Advances in digital technologies, increasing availabilities of granular big data, rapid diffusion of analytic techniques, and intensified competition from user generated content and original content produced by Subscription Video on Demand (SVOD) platforms have created unparalleled needs and opportunities for film producers to leverage analytics in content production. Built upon the theories of value creation and film production, this article proposes a conceptual framework of key analytic techniques that film producers may engage throughout the production process, such as script analytics, talent analytics, and audience analytics. The article further synthesizes the state-of-the-art research on and applications of these analytics, discuss the prospect of leveraging analytics in film production, and suggest fruitful avenues for future research with important managerial implications

Examining the generalizability of research findings from archival data

This initiative examined systematically the extent to which a large set of archival research findings generalizes across contexts. We repeated the key analyses for 29 original strategic management effects in the same context (direct reproduction) as well as in 52 novel time periods and geographies; 45% of the reproductions returned results matching the original reports together with 55% of tests in different spans of years and 40% of tests in novel geographies. Some original findings were associated with multiple new tests. Reproducibility was the best predictor of generalizability-for the findings that proved directly reproducible, 84% emerged in other available time periods and 57% emerged in other geographies. Overall, only limited empirical evidence emerged for context sensitivity. In a forecasting survey, independent scientists were able to anticipate which effects would find support in tests in new samples

The effects of having more than one good reputation on distributor investments in the film industry

Reputations of organizations and its individual members are valuable resources that help new organizations to get access to investment capital. Reputations, however, can have different dimensions. In this paper, we argue that an individual’s reputation along a particular dimension will have a positive effect on the behavior of investors when it is role congruent. In addition, we argue that also scoring favorably on the role-incongruent dimension at the same time—or, in other words, engaging in reputational category spanning—will weaken the positive effect of the role-congruent reputation. Our empirical setting is the film industry where we study the effect of the two main dimensions of reputation in cultural industries, artistic and commercial, of both directors and producers on the size of the investment by distributors. In this study, artistic reputation is based on professional critics’ reviews and commercial reputation on box office performance of the films in which individuals were involved in the past. We find that the commercial reputation of a film producer based on past box office performance has a positive effect on the size of the investment by film distributors. In addition, we find that directors who at the same time combine both a favorable commercial as well as an artistic reputation actually receive a lower investment from film distributors

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)