Sander van Bree

sandervanbree@gmail.com


Curriculum vitae


Postdoc

JLU Giessen
MPI Leipzig
University of Glasgow



The Brain Time Toolbox, a software library to retune electrophysiology data to brain dynamics


Journal article


Sander van Bree, M. Melcón, L. Kolibius, Casper Kerrén, M. Wimber, S. Hanslmayr
Nature Human Behaviour, 2022

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Cite

APA   Click to copy
van Bree, S., Melcón, M., Kolibius, L., Kerrén, C., Wimber, M., & Hanslmayr, S. (2022). The Brain Time Toolbox, a software library to retune electrophysiology data to brain dynamics. Nature Human Behaviour.


Chicago/Turabian   Click to copy
Bree, Sander van, M. Melcón, L. Kolibius, Casper Kerrén, M. Wimber, and S. Hanslmayr. “The Brain Time Toolbox, a Software Library to Retune Electrophysiology Data to Brain Dynamics.” Nature Human Behaviour (2022).


MLA   Click to copy
van Bree, Sander, et al. “The Brain Time Toolbox, a Software Library to Retune Electrophysiology Data to Brain Dynamics.” Nature Human Behaviour, 2022.


BibTeX   Click to copy

@article{sander2022a,
  title = {The Brain Time Toolbox, a software library to retune electrophysiology data to brain dynamics},
  year = {2022},
  journal = {Nature Human Behaviour},
  author = {van Bree, Sander and Melcón, M. and Kolibius, L. and Kerrén, Casper and Wimber, M. and Hanslmayr, S.}
}

Abstract

Human thought is highly flexible, achieved by evolving patterns of brain activity across groups of cells. Neuroscience aims to understand cognition in the brain by analysing these intricate patterns. We argue this goal is impeded by the time format of our data – clock time. The brain is a system with its own dynamics and regime of time, with no intrinsic concern for the human-invented second. Here, we present the Brain Time Toolbox, a software library that retunes electrophysiology data in line with oscillations that orchestrate neural patterns of cognition. These oscillations continually slow down, speed up, and undergo abrupt changes, introducing a disharmony between the brain’s internal regime and clock time. The toolbox overcomes this disharmony by warping the data to the dynamics of coordinating oscillations, setting oscillatory cycles as the data’s new time axis. This enables the study of neural patterns as they unfold in the brain, aiding neuroscientific inquiry into dynamic cognition. In support of this, we demonstrate that the toolbox can reveal results that are absent in a default clock time format.


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