Quantifying evoked responses through information-theoretical measures

Julian Fuhrer; Kyrre Glette; Anaïs Llorens; Tor Endestad; Anne-Kristin Solbakk; Alejandro Omar Blenkmann

doi:10.3389/fninf.2023.1128866

Quantifying evoked responses through information-theoretical measures

Front Neuroinform. 2023 May 23:17:1128866. doi: 10.3389/fninf.2023.1128866. eCollection 2023.

Authors

Julian Fuhrer^{1

2}, Kyrre Glette^{1

2}, Anaïs Llorens³, Tor Endestad^{1

4

5}, Anne-Kristin Solbakk^{1

4

5

6}, Alejandro Omar Blenkmann^{1

4}

Affiliations

¹ RITMO Centre for Interdisciplinary Studies in Rhythm, Time and Motion, University of Oslo, Oslo, Norway.
² Department of Informatics, University of Oslo, Oslo, Norway.
³ Helen Wills Neuroscience Institute and Department of Psychology, University of California, Berkeley, Berkeley, CA, United States.
⁴ Department of Psychology, University of Oslo, Oslo, Norway.
⁵ Department of Neurosurgery, Oslo University Hospital, Rikshospitalet, Oslo, Norway.
⁶ Department of Neuropsychology, Helgeland Hospital, Mosjøen, Norway.

Abstract

Information theory is a viable candidate to advance our understanding of how the brain processes information generated in the internal or external environment. With its universal applicability, information theory enables the analysis of complex data sets, is free of requirements about the data structure, and can help infer the underlying brain mechanisms. Information-theoretical metrics such as Entropy or Mutual Information have been highly beneficial for analyzing neurophysiological recordings. However, a direct comparison of the performance of these methods with well-established metrics, such as the t-test, is rare. Here, such a comparison is carried out by evaluating the novel method of Encoded Information with Mutual Information, Gaussian Copula Mutual Information, Neural Frequency Tagging, and t-test. We do so by applying each method to event-related potentials and event-related activity in different frequency bands originating from intracranial electroencephalography recordings of humans and marmoset monkeys. Encoded Information is a novel procedure that assesses the similarity of brain responses across experimental conditions by compressing the respective signals. Such an information-based encoding is attractive whenever one is interested in detecting where in the brain condition effects are present.

Keywords: ECoG; EEG; algorithmic complexity; frequency tagging; information content; t-test.

Grants and funding

This work was partly supported by the Research Council of Norway (RCN) through its Centers of Excellence scheme project number 262762, RCN project number 240389, and RCN project number 314925.