Connectivity within network processes and coupling with global flows

The brain structure and function are naturally modelled as networks with cytoarchitectonic areas and deep brain nuclei represented as nodes and the white matter or some measure of functional connectivity as edges in a graph.  This project will add to the increasingly popular network model of the brain the coupling to the global electrical current flow generated by the collective neuronal activity.  This model will be tested using Magnetoencephalography (MEG) and electroencephalography (EEG) data.  The ESR will test two hypotheses:

  1. passive flow of electrical current interacts with the processing based on the network of white matter connections
  2. this interaction has consequences for normal activity in awake state and sleep and possibly in pathology. The transferability of connectivity techniques and ideas will utilise results of other projects where the interaction between global flow and network activity is evident, e.g. ecogeomorphology of dryland and/or fluvial environments.

Objectives

  1. To model network-based and continuous flows and their interactions so that the influence of each component in specific and possibly diverse applications can be estimated quantitatively and in terms of meaningful visualizations and time-dependent connectivity.
  2. To describe spatiotemporal brain network activity, using MEG and EEG data.
  3. Document similarities between processes in the brain and in other fields and explore how these can be generalized so they can be applied to other disciplines.
  4. Review trends in connectivity-based biomarker development with few channel EEG and related IPR issues and relevance to results of the project.

Expected Results

  1. Understanding the universality of changes in network topology driven by time-ordered events leading to
  2. unifying the methodology for quantitatively describing network and global properties, dynamics and transitions generated by internal and external influences of finite duration and
  3. through this analysis showing how the relevant parts of a network are “seen” from the point of view of one of the components of the system (node or edge), or
  4. from the point of view of transferability of concepts and approaches between apparently unrelated disciplines sharing some common graph theoretical description.
  5. The ESR will prepare a report and a training material for other ESRs on current efforts of developing connectivity based biomarkers with emphasis on the use of few channel EEG and related IPR issues.

Secondments

Host Months Aim

European University Cyprus (Vicky Papadopoulou-Lesta)

13, 20, 33 - 35

The ESR will receive formal training in computer programming (if needed) graph theory and other computational and mathematical skills, including techniques for High Performance Computing.

University of Durham ((Laura Turnbull, John Wainwright, Rebecca Hodge)

26 - 28

Time ordered events in network activity and continuous flows in ecogeomorphology of dryland and fluvial environments

Jacobs University (Marc Huett)

16, 22

To provide (i) training on non-linear time series analysis and (ii) discussion of these techniques can best be utilized in the specific task(s) this ESR will be tackling.

Other Positions in Structures and Properties

ESR 11

AAISCS (Cyprus)

Connectivity within network processes and coupling with global flows

ESR 14

University of Groningen (Netherlands)

Understanding the emergence of connectivity science in practice: a network of network colleagues

ESR 15

Durham University (United Kingdom)

Use connectivity science to determine the fate (source-pathway-interceptors) of specific diffuse chemicals and pathogens in the water supply chain

ESR 6

Durham University (United Kingdom)

Scaling connectivity science in fluvial systems