Journal article
Empirical mode decomposition of field potentials from macaque V4 in visual spatial attention
Biological cybernetics, v 92(6), pp 380-392
Jun 2005
PMID: 15906081
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.
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Details
- Title
- Empirical mode decomposition of field potentials from macaque V4 in visual spatial attention
- Creators
- Hualou Liang - School of Health Information Sciences, University of Texas Health Science Center at Houston, 7000 Fannin, Suite 600 Houston, TX 77030, USA. hualou.liang@uth.tmc.eduSteven L BresslerElizabeth A BuffaloRobert DesimonePascal Fries
- Publication Details
- Biological cybernetics, v 92(6), pp 380-392
- Publisher
- Springer Nature; Germany
- Grant note
- 67776 / PHS HHS 64204 / PHS HHS
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000229972300005
- Scopus ID
- 2-s2.0-20644453750
- Other Identifier
- 991014878576404721
InCites Highlights
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- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Computer Science, Cybernetics
- Neurosciences