Visualization of brain connectomics data

Researcher: Chengtao Ji, MSc (PhD student)

Expected thesis defense: 2018

First promotor: Prof. Jos Roerdink, PhD (Computer Sciences, RuG)

Collaborators: Jasper van de Gronde, PhD

Funding: CSC

An electroencephalography (EEG) coherence network is a representation of functional brain connectivity, and is constructed by calculating the coherence between pairs of electrode signals as a function of frequency. Visualization of coherence networks can provide insight into unexpected patterns of cognitive processing and help neuroscientists understand brain mechanisms. However, most studies have been limited to static EEG coherence networks or were focused on individual network nodes. In this project, we develop new methods for visualizing the evolution of networks to gain a more complete understanding of EEG coherence and other brain connectivity networks.


  • Visualization of Multichannel EEG Coherence Networks Based on Community Structure C. Ji, N.M. Maurits, J.B.T.M. Roerdink
    In: C. Cherifi et al. (eds.), Complex Networks & Their Applications VI, Studies in Computational Intelligence 689,, Springer International Publishing AG 2018
  • Visualizing and Exploring Dynamic Multichannel EEG Coherence Networks. Chengtao Ji, Jasper van de Gronde, Natasha Maurits, Jos Roerdink. Eurographics Workshop on Visual Computing for Biology and Medicine (2017), S. Bruckner, A. Hennemuth, and B. Kainz (Editors), DOI: 10.2312/vcbm.20171238,
  • Chengtao Ji, Jasper J. van de Gronde, Natasha M. Maurits, and Jos B. T. M. Roerdink. Tracking and Visualizing Dynamic Structures in Multichannel EEG Coherence Networks. In EuroVis Poster. 2016.