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H2020

COSMOS Report Summary

Project ID: 642563
Funded under: H2020-EU.1.3.1.

Periodic Reporting for period 1 - COSMOS (Complex Oscillatory Systems: Modeling and Analysis)

Reporting period: 2015-01-01 to 2016-12-31

Summary of the context and overall objectives of the project

Complex oscillatory systems are abundant in nature, physical and engineering devices, and life sciences. The overarching aim of COSMOS is to understand the behavior of such large and complex systems, specifically those composed of multiple interrelated subunits, many of which operate on different time scales. The novel interdisciplinary approach of COSMOS is to combine theoretical techniques with data-analysis procedures, to allow the development and validation of original analysis methods for complex systems.
COSMOS is pursuing three main objectives:
• The development of methods for the identification of the relevant variables describing collective dynamics of coupled oscillators (top-down)
• The extraction of relevant information from multivariate-data recorded in complex oscillatory systems (bottom-up)
• Integration of the two approaches for cross validation and refinement; implementation of the findings in software toolboxes for the use of unskilled users

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

For objective 1, the main achievements are:
• The characterisation of networks of coupled rotators, where multi-cluster and chimera-like states were observed
• Proven the universality of self-consistent partial synchrony and also optimal immunizations against epidemics on large networks
• Developed an understanding of single cell voltage dynamics of human T-lymphocytes obtained from free-running voltage and whole-cell patch clamp tests
• Developed an understanding of the effects of endogenous noise on networks of neural oscillators
• Addressed the question of how two, very different microscopic dynamics can lead to the same macroscopic phenomena
• Established and verified the topological equivalence between networks with bimodal frequency distributions and two symmetrically coupled networks, extending this to the multimodal case
• Demonstrated the validity of the Ott-Antonsen ansatz for parameter-dependent systems to a variety of bio-physically plausible models

For objective 2, the main achievements are:
• Developed a robust approach to recover the connectivity of a network of pulse-coupled integrate-and-fire oscillators
• Studied the emergence of non-trivial collective behavior and non-equilibrium phase transitions in complex systems
• Developed a method for the inverse problem of correctly inferring the network topology from data
• Developed an understanding of chronotaxic systems and non-autonomous systems in both the theoretical and the inverse approach
• Made improvements to three spike train measures and have developed a new directional spike train analysis method
• Studied methods for the detection of unidirectional couplings between neurons from spike trains, and the influence of other parameters of the measure
• Integrated widely used machine learning techniques for supervised learning and regression modeling into the framework of the network reconstruction
• Development of nonlinear-dynamics-based tools for novel methods of analysing the heart rate variability, with potentially promising clinical applications

Objective 3 will be fully addressed in the second reporting period, however, some initial steps have been made towards this with two ESRs publically releasing their code.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Given the broad ranging scope of the COSMOS consortium, we expect the ideas and tools developed as part of this project to have a prominent impact on a wide-range of communities, from fundamental theory through to industry. Many of the results of the projects are applicable in fields such as climate research, neuroscience and power networks. The work of the project has already started to influence the wider scientific community and has led to the attraction of three new industrial partners and the formation of two new research collaborations.
Our work is developing beyond the state of the art as demonstrated by four ESR first author publications and three ESR first author publications in submission as of the end of the first reporting period.
The developments of the work are to be focused on the refinement of already developed models and theories to expand and extend their scope, with the eventual aim that the two approaches, top-down and bottom-up might ‘meet’.

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