Spectral Changes in Cortical Surface Potentials during Motor Movement

Miller, Kai J.; Leuthardt, Eric C.; Schalk, Gerwin; Rao, Rajesh P. N.; Anderson, Nicholas; Moran, Daniel W.; Miller, John W.; Ojemann, Jeffrey G.

doi:10.1523/jneurosci.3886-06.2007

Cited by 692 publications

(761 citation statements)

References 46 publications

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“…The additional variance in BOLD explained by low frequencies was not restricted to primary areas, suggesting that low frequencies are related to more distributed BOLD changes. Consistent with previous studies [Crone et al, 1998b;Lachaux et al, 2006;Miller et al, 2007], low frequency power decreases were spatially more distributed than high frequency power increases. Understanding how different processes reflected in the LFP are integrated in fMRI activation maps is essential to link fMRI findings to both noninvasive EEG and MEG experiments that measure neuronal signals over larger areas of cortex and invasive studies in nonhuman primates that extract neuronal signals from small areas of cortex.…”

Section: Discussionsupporting

confidence: 91%

“…Increases in HFB change were focused on primary sensorimotor electrodes during movement (Figs. 1, 2, and 5), consistent with previous studies [Crone et al, 1998a;Leuthardt et al, 2007;Miller et al, 2007;Miller et al, 2009b]. This high frequency spectral power change has been shown to correlate directly with firing rate [Manning et al, 2009;Miller et al, 2009a;Whittingstall and Logothetis, 2009], and has been demonstrated to reflect broadspectral change across all frequencies Miller et al, 2009b].…”

Section: Discussionsupporting

confidence: 88%

“…They have shown that broadband power increases, revealed at high frequencies, are typically local, on areas primarily involved in the task [Crone et al, 1998a;Miller et al, 2009b], and these high frequency changes correspond well to sites found with electrocortical stimulation of language and motor regions Sinai et al, 2005]. Power decreases in low frequency sensorimotor rhythms are distributed over larger areas of cortex [Crone et al, 1998b;Miller et al, 2007]. These spectral changes are associated with different processes: broadband power change is associated with local neuronal processing [Manning et al, 2009;Miller et al, 2009a], whereas low frequency oscillations reflect an aspect of subcortical-cortical interaction [Brown, 2003;Feige et al, 2005;Pfurtscheller and Lopes da Silva, 1999;Schnitzler et al, 2006].…”

Section: Introductionmentioning

confidence: 55%

See 2 more Smart Citations

Neurophysiologic correlates of fMRI in human motor cortex

Hermes¹,

Miller²,

Vansteensel³

et al. 2011

Human Brain Mapping

179

177

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Abstract:The neurophysiological underpinnings of functional magnetic resonance imaging (fMRI) are not well understood. To understand the relationship between the fMRI blood oxygen level dependent (BOLD) signal and neurophysiology across large areas of cortex, we compared task related BOLD change during simple finger movement to brain surface electric potentials measured on a similar spatial scale using electrocorticography (ECoG). We found that spectral power increases in high frequencies (65-95 Hz), which have been related to local neuronal activity, colocalized with spatially focal BOLD peaks on primary sensorimotor areas. Independent of high frequencies, decreases in low frequency rhythms (<30 Hz), thought to reflect an aspect of cortical-subcortical interaction, colocalized with weaker BOLD signal increase. A spatial regression analysis showed that there was a direct correlation between the amplitude of the task induced BOLD change on different areas of primary sensorimotor cortex and the amplitude of the high frequency change. Low frequency change explained an additional, different part of the spatial BOLD variance. Together, these spectral power changes explained a significant 36% of the spatial variance in the BOLD signal change (R 2 ¼ 0.36). These results suggest that BOLD signal change is largely induced by two separate neurophysiological mechanisms, one being spatially focal neuronal processing and the other spatially distributed low frequency rhythms. Hum Brain Mapp 33:1689-1699,

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Section: Discussionsupporting

confidence: 91%

Section: Discussionsupporting

confidence: 88%

Section: Introductionmentioning

confidence: 55%

See 1 more Smart Citation

Neurophysiologic correlates of fMRI in human motor cortex

Hermes¹,

Miller²,

Vansteensel³

et al. 2011

Human Brain Mapping

179

177

View full text Add to dashboard Cite

show abstract

“…Mu/beta (10-30 Hz) is a motor rhythm that broadly decreases in power over motor areas in response to movement or imagined movement (21). In contrast, power in the high-gamma (70-100 Hz) band increases very locally in response to specific motor movement or imagery (22). Both signals have been successfully used for BCI control (23)(24)(25).…”

Section: Resultsmentioning

confidence: 99%

Sleep spindles are locally modulated by training on a brain–computer interface

Johnson

Blakely

Hermes

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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The learning of a motor task is known to be improved by sleep, and sleep spindles are thought to facilitate this learning by enabling synaptic plasticity. In this study subjects implanted with electrocorticography (ECoG) arrays for long-term epilepsy monitoring were trained to control a cursor on a computer screen by modulating either the high-gamma or mu/beta power at a single electrode located over the motor or premotor area. In all trained subjects, spindle density in posttraining sleep was increased with respect to pretraining sleep in a remarkably spatially specific manner. The pattern of increased spindle activity reflects the functionally specific regions that were involved in learning of a highly novel and salient task during wakefulness, supporting the idea that sleep spindles are involved in learning to use a motorbased brain-computer interface device.

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“…We also tested and did not find any evidence for significant correlation with other frequency bands (i.e. δ = 1–4 Hz, θ = 4–8 Hz, α = 8–12 Hz, β = 18–26 Hz, low γ = 30–50 Hz11, 12, 13). …”

Section: Resultsmentioning

confidence: 89%

Muscle synergies after stroke are correlated with perilesional high gamma

Godlove

Gulati

Dichter

et al. 2016

Ann Clin Transl Neurol

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Movements can be factored into modules termed “muscle synergies”. After stroke, abnormal synergies are linked to impaired movements; however, their neural basis is not understood. In a single subject, we examined how electrocorticography signals from the perilesional cortex were associated with synergies. The measured synergies contained a mix of both normal and abnormal patterns and were remarkably similar to those described in past work. Interestingly, we found that both normal and abnormal synergies were correlated with perilesional high gamma. Given the link between high gamma and cortical spiking, our results suggest that perilesional spiking may organize synergies after stroke.

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Spectral Changes in Cortical Surface Potentials during Motor Movement

Cited by 692 publications

References 46 publications

Neurophysiologic correlates of fMRI in human motor cortex

Neurophysiologic correlates of fMRI in human motor cortex

Sleep spindles are locally modulated by training on a brain–computer interface

Muscle synergies after stroke are correlated with perilesional high gamma

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