Very high frequency oscillations (VHFO) as a predictor of movement intentions

Gonzalez, Sara; Peralta, Rolando Grave de; Thut, Gregor; Millán, José del R.; Morier, Patrice; Landis, Théodor

doi:10.1016/j.neuroimage.2006.02.041

Cited by 53 publications

(41 citation statements)

References 36 publications

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“…Among these are the application of clustering algorithms to single-subject and single-trial data [5,17] and the direct analysis of single-subject and single-trial source estimations [16,19], including within the time-frequency domain [18,35].…”

Section: Conclusion Future Directions and Outlookmentioning

confidence: 99%

Topographic ERP Analyses: A Step-by-Step Tutorial Review

2008

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In this tutorial review, we detail both the rationale for as well as the implementation of a set of analyses of surface-recorded event-related potentials (ERPs) that uses the reference-free spatial (i.e. topographic) information available from high-density electrode montages to render statistical information concerning modulations in response strength, latency, and topography both between and within experimental conditions. In these and other ways these topographic analysis methods allow the experimenter to glean additional information and neurophysiologic interpretability beyond what is available from canonical waveform analyses. In this tutorial we present the example of somatosensory evoked potentials (SEPs) in response to stimulation of each hand to illustrate these points. For each step of these analyses, we provide the reader with both a conceptual and mathematical description of how the analysis is carried out, what it yields, and how to interpret its statistical outcome. We show that these topographic analysis methods are intuitive and easy-to-use approaches that can remove much of the guesswork often confronting ERP researchers and also assist in identifying the information contained within highdensity ERP datasets.

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Section: Conclusion Future Directions and Outlookmentioning

confidence: 99%

Topographic ERP Analyses: A Step-by-Step Tutorial Review

2008

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“…The estimation of LFPs required the solution of the so-called bio-electromagnetic inverse problem, which is ill-posed due to its lack of a unique solution and will therefore vary in quality as a function of the a priori constraints one applies to obtain a unique solution. In our particular case, we used biophysically based constraints that differ considerably from purely mathematically based constraints and furthermore have several computational and empirical benefits (detailed in Grave de Peralta Menendez et al 2004; see also Gonzalez Andino et al 2005b;Gonzalez et al 2006). Prior studies from our group evaluated the reliability of such an inverse solution in two manners.…”

Section: Experimental Datamentioning

confidence: 99%

“…In humans, VHFOs have been recorded noninvasively in response to somatosensory (Curio 2000;Miller et al 2007) as well as visual stimuli (Gonzalez et al 2006). The noninvasive study of VHFOs has typically been limited (and often obfuscated) by their small amplitude on the scalp, often below the noise level.…”

Section: Experimental Datamentioning

confidence: 99%

“…Thus the role of MUA cannot be entirely discounted. Additionally, very high-frequency oscillations (VHFOs) within the LFP appear to be more tightly linked to MUA than to LFP oscillations in lower frequency bands (Kreiman et al 2006), raising the possibility that VHFOs in surface-recorded EEG in humans might provide insights into a wider range of neuronal activity (e.g., Gonzalez et al 2006). To date, noninvasive studies in humans have assessed the spatial correspondence between BOLD responses and source estimations from surface-recorded event-related potentials (ERPs) (e.g., Dale and Halgren 2001) and steady-state visual evoked potentials (SSVEPs) (Di Russo et al 2007), although these assessments were always qualitative rather than quantitative in nature.…”

Section: Introductionmentioning

confidence: 99%

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Methods for Determining Frequency- and Region-Dependent Relationships Between Estimated LFPs and BOLD Responses in Humans

Martuzzi¹,

Murray²,

Meuli³

et al. 2009

Journal of Neurophysiology

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Here we present a method that uses fMRI data and singe-trial electroencephalography (EEG) analyses to assess the spatial and spectral dependencies between the blood-oxygenation-level-dependent (BOLD) responses and the noninvasively estimated local field potentials (eLFPs) over a wide range of frequencies (0 -256 Hz) throughout the entire brain volume. This method was applied in a study where human subjects completed separate fMRI and EEG sessions while performing a passive visual task. Intracranial LFPs were estimated from the scalp-recorded data using the ELECTRA source model. We compared statistical images from BOLD signals with statistical images of each frequency of the eLFPs. In agreement with previous studies in animals, we found a significant correspondence between LFP and BOLD statistical images in the gamma band (44 -78 Hz) within primary visual cortices. In addition, significant correspondence was observed at low frequencies (Ͻ14 Hz) and also at very high frequencies (Ͼ100 Hz). Effects within extrastriate visual areas showed a different correspondence that not only included those frequency ranges observed in primary cortices but also additional frequencies. Results therefore suggest that the relationship between electrophysiological and hemodynamic signals thus might vary both as a function of frequency and anatomical region.

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“…The data shown correspond to a trial where the subject failed to perceive the flash. Note that the ongoing alpha oscillations are modified by the onset of the flash even if there is no conscious perception discriminating facial expressions in blindsight patient able to identify (above chance) the affective content of faces without awareness [33].…”

Section: What Information Is Coded At Each Level Of Recording?mentioning

confidence: 99%

Spatiotemporal scales and links between electrical neuroimaging modalities

Andino

Perrig

Menéndez

2011

Med Biol Eng Comput

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Recordings of brain electrophysiological activity provide the most direct reflect of neural function. Information contained in these signals varies as a function of the spatial scale at which recordings are done: from single cell recording to large scale macroscopic fields, e.g., scalp EEG. Microscopic and macroscopic measurements and models in Neuroscience are often in conflict. Solving this conflict might require the developments of a sort of bio-statistical physics, a framework for relating the microscopic properties of individual cells to the macroscopic or bulk properties of neural circuits. Such a framework can only emerge in Neuroscience from the systematic analysis and modeling of the diverse recording scales from simultaneous measurements. In this article we briefly review the different measurement scales and models in modern neuroscience to try to identify the sources of conflict that might ultimately help to create a unified theory of brain electromagnetic fields. We argue that seen the different recording scales, from the single cell to the large scale fields measured by the scalp electroencephalogram, as derived from a unique physical magnitude-the electric potential that is measured in all cases-might help to conciliate microscopic and macroscopic models of neural function as well as the animal and human neuroscience literature.

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Very high frequency oscillations (VHFO) as a predictor of movement intentions

Cited by 53 publications

References 36 publications

Topographic ERP Analyses: A Step-by-Step Tutorial Review

Topographic ERP Analyses: A Step-by-Step Tutorial Review

Methods for Determining Frequency- and Region-Dependent Relationships Between Estimated LFPs and BOLD Responses in Humans

Spatiotemporal scales and links between electrical neuroimaging modalities

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