Role of Neuronal Synchrony in the Generation of Evoked EEG/MEG Responses

Dept. of Neurology, Charité-Universitätsmedizin, Hindenburgdamm 30, 12203 Berlin, Germany.
Journal of Neurophysiology (Impact Factor: 2.89). 10/2010; 104(6):3557-67. DOI: 10.1152/jn.00138.2010
Source: PubMed


Evoked EEG/MEG responses are a primary real-time measure of perceptual and cognitive activity in the human brain, but their neuronal generator mechanisms are not yet fully understood. Arguments have been put forward in favor of either "phase-reset" of ongoing oscillations or "added-energy" models. Instead of advocating for one or the other model, here we show theoretically that the differentiation between these two generation mechanisms might not be possible if based solely on macroscopic EEG/MEG recordings. Using mathematical modeling, we show that a simultaneous phase reset of multiple oscillating neuronal (microscopic) sources contributing to EEG/MEG can produce evoked responses in agreement with both, the "added-energy" and the "phase-reset" model. We observe a smooth transition between the two models by just varying the strength of synchronization between the multiple microscopic sources. Consequently, because precise knowledge about the strength of microscopic ensemble synchronization is commonly not available in noninvasive EEG/MEG studies, they cannot, in principle, differentiate between the two mechanisms for macroscopic-evoked responses.

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Available from: Bartosz Telenczuk,
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    • "Previous studies argued that such phase modulations could be either related to additive evoked responses or phase resetting (Sauseng et al., 2007; Becker et al., 2008). Moreover, it is not clear whether the macroscopic phase resetting of EEG oscillations reflects the microscopic phase resetting or additive evoked responses at the single neuron level (Telenczuk et al., 2010). Therefore, it is necessary to examine the issues by combining experimental data at different spatial scales using several indices and mathematical modeling. "
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    ABSTRACT: Electroencephalogram (EEG) phase synchronization analyses can reveal large-scale communication between distant brain areas. However, it is not possible to identify the directional information flow between distant areas using conventional phase synchronization analyses. In the present study, we applied transcranial magnetic stimulation (TMS) to the occipital area in subjects who were resting with their eyes closed, and analyzed the spatial propagation of transient TMS-induced phase resetting by using the transfer entropy (TE), to quantify the causal and directional flow of information. The time-frequency EEG analysis indicated that the theta (5 Hz) phase locking factor (PLF) reached its highest value at the distant area (the motor area in this study), with a time lag that followed the peak of the transient PLF enhancements of the TMS-targeted area at the TMS onset. Phase-preservation index (PPI) analyses demonstrated significant phase resetting at the TMS-targeted area and distant area. Moreover, the TE from the TMS-targeted area to the distant area increased clearly during the delay that followed TMS onset. Interestingly, the time lags were almost coincident between the PLF and TE results (152 vs. 165 ms), which provides strong evidence that the emergence of the delayed PLF reflects the causal information flow. Such tendencies were observed only in the higher-intensity TMS condition, and not in the lower-intensity or sham TMS conditions. Thus, TMS may manipulate large-scale causal relationships between brain areas in an intensity-dependent manner. We demonstrated that single-pulse TMS modulated global phase dynamics and directional information flow among synchronized brain networks. Therefore, our results suggest that single-pulse TMS can manipulate both incoming and outgoing information in the TMS-targeted area associated with functional changes.
    Frontiers in Human Neuroscience 03/2014; 8:173. DOI:10.3389/fnhum.2014.00173 · 3.63 Impact Factor
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    • "The investigation of both possibilities remains subject of follow-up studies. It has been recently argued that the detection of added-activity in single-trials of EEG does not determine the mechanisms of evoked response generation at the microscopic neuronal level (Telenczuk et al., 2010). However, in accordance with the conclusion of the present non-invasive study, invasive measures in the barrel cortex of rats (Barth, 2003) and the primary somatosensory cortex of non-human primates (Baker et al., 2003) have shown that macroscopic evoked hfSEP are related to increased activity at both, single-cell and population level. "
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    ABSTRACT: Median nerve somatosensory evoked potentials (SEP) contain a brief oscillatory wavelet burst at about 600Hz (σ-burst) superimposed on the initial cortical component (N20). While invasive single-cell recordings suggested that this burst is generated by increased neuronal spiking activity in area 3b, recent non-invasive scalp recordings could not reveal concomitant single-trial added-activity, suggesting that the SEP burst might instead be generated by phase-reset of ongoing high-frequency EEG. Here, a statistical model and exemplary data are presented reconciling these seemingly contradictory results. A statistical model defined the conditions required to detect added-activity in a set of single-trial SEP. Its predictions were tested by analyzing human single-trial scalp SEP recorded with custom-made low-noise amplifiers. The noise level in previous studies did not allow to detect single-trial added-activity in the period concomitant with the trial-averaged σ-burst. In contrast, optimized low-noise recordings do reveal added-activity in a set of single-trials. The experimental noise level is the decisive factor determining the detectability of added-activity in single-trials. A low-noise experiment provided direct evidence that the SEP σ-burst is at least partly generated by added-activity matching earlier invasive single-cell recordings. Quantitative criteria are provided for the feasibility of single-trial detectability of band-limited added-activity.
    Clinical neurophysiology: official journal of the International Federation of Clinical Neurophysiology 05/2012; 123(10):2064-73. DOI:10.1016/j.clinph.2012.03.013 · 3.10 Impact Factor
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