Coupling Between Neuronal Firing, Field Potentials, and fMRI in Human Auditory Cortex

Mukamel, Roy; Gelbard, Harris A.; Arieli, Amos; Hasson, Uri; Fried, Itzhak; Malach, Rafael

doi:10.1126/science.1110913

Cited by 924 publications

(868 citation statements)

References 24 publications

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“…LFP-BOLD coupling was dependant on frequency band and brain region but generally, positive correlations were seen in the gamma band, and negative correlation in the beta band. This general pattern was also shown by Mukamel et al (Mukamel et al, 2005).…”

Section: Boldsupporting

confidence: 85%

“…MEG results bear distinct similarities to results acquired using invasive electrode recording of LFP signals in the auditory cortex of conscious epilepsy patients during natural auditory stimulation. These results, published by Mukamel and colleagues (Mukamel et al, 2005), are captured in Figure 3B for comparison. Notice the general similarities between MEG and LFP, with negative correlation at low frequency and positive correlation at high frequency.…”

Section: Temporal and Spectral Relationshipsmentioning

confidence: 58%

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The relationship between MEG and fMRI

et al. 2014

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In recent years functional neuroimaging techniques such as fMRI, MEG, EEG and PET have provided researchers with a wealth of information on human brain function. However none of these modalities can measure directly either the neuro-electrical or neuro-chemical processes that mediate brain function. This means that metrics directly reflecting brain 'activity' must be inferred from other metrics (e.g. magnetic fields (MEG) or haemodynamics (fMRI)). To overcome this limitation, many studies seek to combine multiple complementary modalities and an excellent example of this is the combination of MEG (which has high temporal resolution) with fMRI (which has high spatial resolution). However, the full potential of multi-modal approaches can only be truly realised in cases where the relationship between metrics is known. In this paper, we explore the relationship between measurements made using fMRI and MEG. We describe the origins of the two signals as well as their relationship to electrophysiology. We review multiple studies that have attempted to characterise the spatial relationship between fMRI and MEG, and we also describe studies that exploit the rich information content of MEG to explore differing relationships between MEG and fMRI across neural oscillatory frequency bands. Monitoring the brain at "rest" has become of significant recent interest to the neuroimaging community and we review recent evidence comparing MEG and fMRI metrics of functional connectivity. A brief discussion of the use of magnetic resonance spectroscopy (MRS) to probe the relationship between MEG/fMRI and neurochemistry is also given. Finally, we highlight future areas of interest and offer some recommendations for the parallel use of fMRI and MEG.

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Section: Boldsupporting

confidence: 85%

Section: Temporal and Spectral Relationshipsmentioning

confidence: 58%

The relationship between MEG and fMRI

et al. 2014

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“…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]. Previous studies examined the relationship between spectral power change and BOLD change within a specific region [Logothetis et al, 2001;Maier et al, 2008;Mukamel et al, 2005;Niessing et al, 2005]. We extend this relationship found at the neuronal population volumes sampled by microelectrodes [<500 lm (Katzner et al, 2009)] to a widespread network of movement-related regions on the cortical surface.…”

Section: Discussionmentioning

confidence: 64%

“…Previous studies investigating the relationship between BOLD signal change and neurophysiology have adopted the strategy of selecting a small patch of cortex in a functionally relevant area, and then tracking both BOLD signal change and electrophysiological change over time [Logothetis et al, 2001;Mukamel et al, 2005;Niessing et al, 2005]. These studies have shown that in one area of cortex BOLD change is best related to high frequency power changes in the local field potential.…”

Section: Introductionmentioning

confidence: 99%

Neurophysiologic correlates of fMRI in human motor cortex

Hermes¹,

Miller²,

Vansteensel³

et al. 2011

Human Brain Mapping

174

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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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“…In healthy populations, attention to speech results in entrainment of the subject's evoked activity not only to low‐level features of the stimulus itself, but also the cortical activity of other subjects experiencing the same stimulus 18, 19, 20, 21. This effect has been observed in visual as well as auditory contexts for EEG,19, 20, 22 functional magnetic resonance imaging,23, 24 and magnetoencephalography 25, 26. Moreover, intersubject correlation (ISC) of EEG evoked responses has been shown to discriminate attention better than conventional EEG measures19 and is able to predict selective auditory attention during auditory stream segregation 27, 28.…”

Section: Introductionmentioning

confidence: 97%

Divergent neural responses to narrative speech in disorders of consciousness

Iotzov

Fidali

Petroni

et al. 2017

Ann Clin Transl Neurol

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ObjectiveClinical assessment of auditory attention in patients with disorders of consciousness is often limited by motor impairment. Here, we employ intersubject correlations among electroencephalography responses to naturalistic speech in order to assay auditory attention among patients and healthy controls.MethodsElectroencephalographic data were recorded from 20 subjects with disorders of consciousness and 14 healthy controls during of two narrative audio stimuli, presented both forwards and time‐reversed. Intersubject correlation of evoked electroencephalography signals were calculated, comparing responses of both groups to those of the healthy control subjects. This analysis was performed blinded and subsequently compared to the diagnostic status of each patient based on the Coma Recovery Scale‐Revised.ResultsSubjects with disorders of consciousness exhibit significantly lower intersubject correlation than healthy controls during narrative speech. Additionally, while healthy subjects had higher intersubject correlation values in forwards versus backwards presentation, neural responses did not vary significantly with the direction of playback in subjects with disorders of consciousness. Increased intersubject correlation values in the backward speech condition were noted with improving disorder of consciousness diagnosis, both in cross‐sectional analysis and in a subset of patients with longitudinal data.InterpretationIntersubject correlation of neural responses to narrative speech audition differentiates healthy controls from patients and appears to index clinical diagnoses in disorders of consciousness.

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Coupling Between Neuronal Firing, Field Potentials, and fMRI in Human Auditory Cortex

Cited by 924 publications

References 24 publications

The relationship between MEG and fMRI

The relationship between MEG and fMRI

Neurophysiologic correlates of fMRI in human motor cortex

Divergent neural responses to narrative speech in disorders of consciousness

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