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Graph Theory for Brain Signal Processing

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Handbook of Neuroengineering

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Abstract

This chapter introduces the use of graph-theoretic concepts in analyzing brain signals. For didactic purposes, it has been split into three parts: “theory,” “demonstration,” and “examples.” In the first part, we commence by introducing some basic elements from graph theory and stemming algorithmic tools, which can be employed for data-analytic purposes. Next, we describe how these concepts are adapted for handling evolving connectivity and gaining insights into network reorganization. Finally, the notion of signals residing on a given graph is introduced, and elements from the emerging field of graph signal processing (GSP) are provided. The second part serves as a pragmatic demonstration of the tools and techniques described earlier. It is based on analyzing a multi-trial dataset containing single-trial responses from a visual event-related potential (ERP) paradigm. The third part includes examples from the related literature. This chapter ends with a brief outline of the most recent trends in graph theory that are about to shape brain signal processing in the near future and a more general discussion on the relevance of graph-theoretic methodologies for neural recordings.

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Authors and Affiliations

  1. Department of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece

    Nikolaos Laskaris

  2. Department of Computing, Imperial College London, London, UK

    Dimitrios Adamos

  3. Department of Medicine, University of Patras, Patras, Greece

    Anastasios Bezerianos

  4. Hellenic Institute of Transport, Center for Research and Technology Hellas, Thermi, Thessaloniki, Greece

    Anastasios Bezerianos

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  1. Nikolaos Laskaris
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  2. Dimitrios Adamos
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  3. Anastasios Bezerianos
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Correspondence to Dimitrios Adamos .

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  1. Singapore Institute for Neurotechnology, National University of Singapore, Singapore, Singapore

    Nitish V. Thakor

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  1. National University of Singapore, Singapore, Singapore

    Andrei Dragomir

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Laskaris, N., Adamos, D., Bezerianos, A. (2021). Graph Theory for Brain Signal Processing. In: Thakor, N.V. (eds) Handbook of Neuroengineering. Springer, Singapore. https://doi.org/10.1007/978-981-15-2848-4_66-2

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