Empirical mode decomposition of field potentials from macaque V4 in visual spatial attention

Authors:
H. Liang;S. L. Bressler;E. A. Buffalo;R. Desimone;P. Fries
Affiliations:
School of Health Information Sciences, University of Texas Health Science Center at Houston, 7000 Fannin, 77030, Suite 600 Houston, TX, USA;Center for Complex Systems and Brain Sciences, Florida Atlantic University, 7000 Fannin, 33431, Boca Raton, FL, USA;Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, 7000 Fannin, 20892, Bethesda, MD, USA;Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, 7000 Fannin, 20892, Bethesda, MD, USA and Mc Govern Institute for Brain Research at Massachusetts ...;F.C. Donders Centre for Cognitive Neuroimaging, University of Nijmegen, 7000 Fannin, 6525 EK, Nijmegen, MD, The Netherlands
Venue:
Biological Cybernetics
Year:
2005

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Abstract

Empirical mode decomposition (EMD) has recently been introduced as a local and fully data-driven technique for the analysis of non-stationary time-series. It allows the frequency and amplitude of a time-series to be evaluated with excellent time resolution. In this article we consider the application of EMD to the analysis of neuronal activity in visual cortical area V4 of a macaque monkey performing a visual spatial attention task. We show that, by virtue of EMD, field potentials can be resolved into a sum of intrinsic components with different degrees of oscillatory content. Low-frequency components in single-trial recordings contribute to the average visual evoked potential (AVEP), whereas high-frequency components do not, but are identified as gamma-band (30–90 Hz) oscillations. The magnitude of time-varying gamma activity is shown to be enhanced when the monkey attends to a visual stimulus as compared to when it is not attending to the same stimulus. Comparison with Fourier analysis shows that EMD may offer better temporal and frequency resolution. These results support the idea that the magnitude of gamma activity reflects the modulation of V4 neurons by visual spatial attention. EMD, coupled with instantaneous frequency analysis, is demonstrated to be a useful technique for the analysis of neurobiological time-series.