Abstract
Transient sensory, motor or cognitive event elicit not only phase-locked event-related potentials (ERPs) in the ongoing electroencephalogram (EEG), but also induce non-phase-locked modulations of ongoing EEG oscillations. These modulations can be detected when single-trial waveforms are analysed in the time-frequency domain, and consist in stimulus-induced decreases (event-related desynchronization, ERD) or increases (event-related synchronization, ERS) of synchrony in the activity of the underlying neuronal populations. ERD and ERS reflect changes in the parameters that control oscillations in neuronal networks and, depending on the frequency at which they occur, represent neuronal mechanisms involved in cortical activation, inhibition and binding. ERD and ERS are commonly estimated by averaging the time-frequency decomposition of single trials. However, their trial-to-trial variability that can reflect physiologically-important information is lost by across-trial averaging. Here, we aim to (1) develop novel approaches to explore single-trial parameters (including latency, frequency and magnitude) of ERP/ERD/ERS; (2) disclose the relationship between estimated single-trial parameters and other experimental factors (e.g., perceived intensity). We found that (1) stimulus-elicited ERP/ERD/ERS can be correctly separated using principal component analysis (PCA) decomposition with Varimax rotation on the single-trial time-frequency distributions; (2) time-frequency multiple linear regression with dispersion term (TF-MLRd) enhances the signal-to-noise ratio of ERP/ERD/ERS in single trials, and provides an unbiased estimation of their latency, frequency, and magnitude at single-trial level; (3) these estimates can be meaningfully correlated with each other and with other experimental factors at single-trial level (e.g., perceived stimulus intensity and ERP magnitude). The methods described in this article allow exploring fully non-phase-locked stimulus-induced cortical oscillations, obtaining single-trial estimate of response latency, frequency, and magnitude. This permits within-subject statistical comparisons, correlation with pre-stimulus features, and integration of simultaneously-recorded EEG and fMRI.
Highlights
The human electroencephalogram (EEG) and magnetoencephalogram (MEG) largely reflect synchronous changes of slow postsynaptic potentials occurring within a large number of oriented cortical pyramidal neurons (Nunez and Srinivasan, 2006)
The group-level phaselocking value (PLV) indicated that only the event-related potentials (ERPs) response was phase-locked to stimulus onset, while the other time-frequency distribution (TFD) responses (ERD and ERS) were not (Fig. 1, left panel)
The present study shows that different features (i.e., ERP, estimated using TF-MLR and TF-MLRd (ERD), and ERS) of the time-frequency EEG response elicited by transient sensory stimuli can be (1) isolated and characterized using principal component analysis (PCA) with Varimax rotation, and (2) reliably estimated at single-trial level using multiple linear regression approaches (TF-MLR and TF-MLRd)
Summary
The human electroencephalogram (EEG) and magnetoencephalogram (MEG) largely reflect synchronous changes of slow postsynaptic potentials occurring within a large number of oriented cortical pyramidal neurons (Nunez and Srinivasan, 2006). Motor or cognitive events can elicit transient changes in the ongoing EEG activity. Such changes are commonly detected as event-related potentials (ERPs) that are both time-locked and phase-locked to the stimulus. Key Laboratory of Cognition and Personality (Ministry of Education), Faculty of Psychology, Southwest University, Chongqing, China.
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