Power and phase properties of oscillatory neural responses in the presence of background activity

  • Authors:
  • Nai Ding;Jonathan Z. Simon

  • Affiliations:
  • Department of Electrical and Computer Engineering, University of Maryland, College Park, USA 20742;Department of Electrical and Computer Engineering, University of Maryland, College Park, USA 20742 and Department of Biology, University of Maryland, College Park, USA 20742

  • Venue:
  • Journal of Computational Neuroscience
  • Year:
  • 2013

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Abstract

Natural sensory inputs, such as speech and music, are often rhythmic. Recent studies have consistently demonstrated that these rhythmic stimuli cause the phase of oscillatory, i.e. rhythmic, neural activity, recorded as local field potential (LFP), electroencephalography (EEG) or magnetoencephalography (MEG), to synchronize with the stimulus. This phase synchronization, when not accompanied by any increase of response power, has been hypothesized to be the result of phase resetting of ongoing, spontaneous, neural oscillations measurable by LFP, EEG, or MEG. In this article, however, we argue that this same phenomenon can be easily explained without any phase resetting, and where the stimulus-synchronized activity is generated independently of background neural oscillations. It is demonstrated with a simple (but general) stochastic model that, purely due to statistical properties, phase synchronization, as measured by `inter-trial phase coherence', is much more sensitive to stimulus-synchronized neural activity than is power. These results question the usefulness of analyzing the power and phase of stimulus-synchronized activity as separate and complementary measures; particularly in the case of attempting to demonstrate whether stimulus-synchronized neural activity is generated by phase resetting of ongoing neural oscillations.