Functional Near-Infrared Spectroscopy and Electroencephalography: A Multimodal Imaging Approach

  • Authors:

  • Anna C. Merzagora;Meltem Izzetoglu;Robi Polikar;Valerie Weisser;Banu Onaral;Maria T. Schultheis

  • Affiliations:

  • School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, U.S.A. PA 19104;School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, U.S.A. PA 19104;School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, U.S.A. PA 19104 and Department of Electrical and Computer Engineering, Rowan University, Glassboro, U ...;Department of Psychology, Drexel University, Philadelphia, U.S.A. PA 19104;School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, U.S.A. PA 19104;School of Biomedical Engineering, Science and Health Systems, Drexel University, Philadelphia, U.S.A. PA 19104 and Department of Psychology, Drexel University, Philadelphia, U.S.A. PA 19104

  • Venue:
  • FAC '09 Proceedings of the 5th International Conference on Foundations of Augmented Cognition. Neuroergonomics and Operational Neuroscience: Held as Part of HCI International 2009
  • Year:
  • 2009

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Abstract

Although neuroimaging has greatly expanded our knowledge about the brain-behavior relation, combining multiple neuroimaging modalities with complementing strengths can overcome some limitations encountered when using a single modality. Valuable candidates for a multimodal approach are functional near-infrared spectroscopy (fNIRS) and electroencephalography (EEG). fNIRS is an imaging technology that localizes hemodynamic changes within the cortex. However, hemodynamic activation is an intrinsically slow process. On the other hand, EEG has excellent time resolution by directly measuring the manifestation of the brain electrical activity at the scalp. Based on their complementary strengths, the integration of fNIRS and EEG may provide higher spatiotemporal resolution than either method alone. In this effort, we integrate fNIRS and EEG to evaluate the behavioral performance of six healthy adults in a working memory task. To this end, features extracted from fNIRS and EEG were used separately, as well as in combination, and their performances were compared against each other.