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FiNN: A toolbox for neurophysiological network analysis.

Maximilian Scherer1,2, Tianlu Wang1, Robert Guggenberger1

  • 1Institute for Neuromodulation and Neurotechnology, University Hospital and University of Tübingen, Tübingen, Germany.

Network Neuroscience (Cambridge, Mass.)
|May 27, 2024
PubMed
Summary

Introducing FiNN, a new toolbox for analyzing brain networks. This open-source software efficiently processes neurophysiological data for functional and effective connectivity, aiding neuroscience research.

Keywords:
ConnectivityCross-frequency couplingNeural oscillationsPhase-amplitude coupling

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Area of Science:

  • Neuroscience
  • Computational Neuroscience
  • Network Science

Background:

  • Neuroscience research is shifting from local brain function analysis to network-wide investigations.
  • Understanding neural communication requires analyzing neurophysiological signals across various scales.
  • Network-wide brain dynamics present methodological challenges due to large, high-dimensional data.

Purpose of the Study:

  • To introduce FiNN (Find Neurophysiological Networks), a novel toolbox for analyzing neurophysiological data.
  • To provide tools for assessing functional and effective connectivity in brain networks.
  • To offer an efficient, accessible, and modifiable open-source solution for neuroscientific research.

Main Methods:

  • FiNN offers a comprehensive suite of data processing, statistical, and visualization tools.
  • The toolbox focuses on estimating functional and effective connectivity.
  • FiNN was evaluated against established frameworks on conceptual and implementation levels.

Main Results:

  • FiNN demonstrated significantly reduced processing time and memory requirements compared to existing toolboxes.
  • The software is designed for easy access and modification.
  • FiNN provides efficient implementations for data processing.

Conclusions:

  • FiNN is a valuable open-source resource for the neuroscientific community.
  • The toolbox facilitates the investigation of network-level neural dynamics.
  • FiNN's efficiency and accessibility support the growing interest in brain network analysis.