Explorative data analysis for changes in neural activity

Duncan A J Blythe, Frank C. Meinecke, Paul Von Bünau, Klaus Muller

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

Neural recordings are non-stationary time series, i.e. their properties typically change over time. Identifying specific changes, e.g., those induced by a learning task, can shed light on the underlying neural processes. However, such changes of interest are often masked by strong unrelated changes, which can be of physiological origin or due to measurement artifacts. We propose a novel algorithm for disentangling such different causes of non-stationarity and in this manner enable better neurophysiological interpretation for a wider set of experimental paradigms. A key ingredient is the repeated application of Stationary Subspace Analysis (SSA) using different temporal scales. The usefulness of our explorative approach is demonstrated in simulations, theory and EEG experiments with 80 brain-computer interfacing subjects.

Original languageEnglish
Article number026018
JournalJournal of Neural Engineering
Volume10
Issue number2
DOIs
Publication statusPublished - 2013 Apr 1

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

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  • Cite this

    Blythe, D. A. J., Meinecke, F. C., Von Bünau, P., & Muller, K. (2013). Explorative data analysis for changes in neural activity. Journal of Neural Engineering, 10(2), [026018]. https://doi.org/10.1088/1741-2560/10/2/026018