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See detailFastField: An Open-Source Toolbox for Efficient Approximation of Deep Brain Stimulation Electric Fields
Baniasadi, Mehri UL; Proverbio, Daniele UL; Goncalves, Jorge UL et al

in NeuroImage (2020)

Deep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of certain brain disorders by electrically modulating neural tissues. Computational models predicting electric fields and volumes ... [more ▼]

Deep brain stimulation (DBS) is a surgical therapy to alleviate symptoms of certain brain disorders by electrically modulating neural tissues. Computational models predicting electric fields and volumes of tissue activated are key for efficient parameter tuning and network analysis. Currently, we lack efficient and flexible software implementations supporting complex electrode geometries and stimulation settings. Available tools are either too slow (e.g. finite element method–FEM), or too simple, with limited applicability to basic use-cases. This paper introduces FastField, an efficient open-source toolbox for DBS electric field and VTA approximations. It computes scalable e-field approximations based on the principle of superposition, and VTA activation models from pulse width and axon diameter. In benchmarks and case studies, FastField is solved in about 0.2s, ~ 1000 times faster than using FEM. Moreover, it is almost as accurate as using FEM: average Dice overlap of 92%, which is around typical noise levels found in clinical data. Hence, FastField has the potential to foster efficient optimization studies and to support clinical applications [less ▲]

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See detailAssessing suppression strategies against epidemicoutbreaks like COVID-19: the SPQEIR model
Proverbio, Daniele UL; Kemp, Francoise UL; Magni, Stefano UL et al

E-print/Working paper (2020)

The current COVID-19 outbreak represents a most serious challenge for societies worldwide. It isendangering the health of millions of people, and resulting in severe socioeconomic challenges dueto lock ... [more ▼]

The current COVID-19 outbreak represents a most serious challenge for societies worldwide. It isendangering the health of millions of people, and resulting in severe socioeconomic challenges dueto lock-down measures. Governments worldwide aim to devise exit strategies to revive the economywhile keeping the pandemic under control. The problem is that the effects of distinct measures arenot well quantified. This paper compares several suppression approaches and potential exit strategiesusing a new extended epidemic SEIR model. It concludes that while rapid and strong lock-down isan effective pandemic suppression measure, a combination of other strategies such as social distanc-ing, active protection and removal can achieve similar suppression synergistically. This quantitativeunderstanding will support the establishment of mid- and long-term interventions. Finally, the paperprovides an online tool that allows researchers and decision makers to interactively simulate diversescenarios with our model. [less ▲]

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See detailA Multi-agent approach for in silico simulations of micro-biological systems
Proverbio, Daniele UL; Gallo, Luca; Passalacqua, Barbara et al

E-print/Working paper (2019)

A Multi-agent approach forin silicosimulations ofmicro-biological systemsProverbio D., Gallo L., Passalacqua B., Pellegrino J., Maggiora M.AbstractUsing a Multi-agent systems paradigm, the present project ... [more ▼]

A Multi-agent approach forin silicosimulations ofmicro-biological systemsProverbio D., Gallo L., Passalacqua B., Pellegrino J., Maggiora M.AbstractUsing a Multi-agent systems paradigm, the present project develops, validates and exploits a computa-tionaltestbedthat simulates micro-biological complex systems, namely the aggregation patterns of thesocial amoebaDyctiostelium discoideum. We propose a new design and implementation for managingdiscrete simulations with autonomous agents on a microscopic scale, thus focusing on their social be-havior and mutual interactions. Then, the dependence on the main physical variables is tested, namelydensity and number of amoebas; in addition, we analyze the robustness of the dynamics against var-ious noise sources. Along with these results, we suggest a methodology for further studies that makeuse of our validated model. [less ▲]

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See detailApproXON: Heuristic Approximation to the E-Field-Threshold for Deep Brain Stimulation Volume-of-Tissue-Activated Estimation
Proverbio, Daniele UL; Husch, Andreas UL

E-print/Working paper (2019)

This paper introduces a heuristic approximation of the e-field threshold used for volume-of-tissue activated computation in deep brain stimulation. Pulse width and axon diameter are used as predictors. An ... [more ▼]

This paper introduces a heuristic approximation of the e-field threshold used for volume-of-tissue activated computation in deep brain stimulation. Pulse width and axon diameter are used as predictors. An open source implementation in MATLAB is provided together with an integration in the open LeadDBS deep brain stimulation research toolbox. [less ▲]

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See detailDynamical strategies for obstacle avoidance during Dictyostelium discoideum aggregation: a Multi-agent system model
Proverbio, Daniele UL; Maggiora, Marco

E-print/Working paper (2019)

Chemotaxis, the movement of an organism in response to a chemical stimulus, is a typical feature of many microbiological systems. In particular, the social amoeba Disctyostelium discoideum is widely used ... [more ▼]

Chemotaxis, the movement of an organism in response to a chemical stimulus, is a typical feature of many microbiological systems. In particular, the social amoeba Disctyostelium discoideum is widely used as a model organism, but it is not still clear how it behaves in heterogeneous environments. A few models focused on mechanical features have already addressed the question; however, we propose that phenomenological models focusing on the dynamics may provide new meaningful data. Consequently, by means of a specific Multi-agent system model, we studied the dynamical features emerging from complex social interactions among individuals belonging to amoeboids colonies. After defining an appropriate metric to perform meaningful measurements, we found that: a) obstacles play the role of local topological perturbation, as they alter the flux of chemical signals; b) that obstacle that physically block the cellular motion as well as the chemicals elicit dynamical evolutions that are not statistically distinguishable from the case where obstacles that do not interfere physically with said motion; c) that fluctuations of the dynamics can lead to better exploration of the physical space, thus preventing multiple stable aggregates. From previous results, we may speculate about the fact that chemotactic cells, in many cases, can avoid obstacles by simply following the altered chemical gradient: social interactions seem to be sufficient to guarantee the aggregation of the whole colony past numerous obstacles. It is then unlikely that cells have developed special mechanisms to cope with the presence of topological perturbation sources. Nevertheless, we suggest that further studies can provide better understanding and that, in order to gain deeper knowledge, mechanical models should be coupled with phenomenological, system-oriented ones. [less ▲]

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