Task-Related Changes in Cortical Synchronization Are Spatially Coincident with the Hemodynamic Response

Singh, Krish Devi; Barnes, Gareth R.; Hillebrand, Arjan; Forde, Emer M. E.; Williams, AE

doi:10.1006/nimg.2001.1050

Cited by 262 publications

(212 citation statements)

References 52 publications

Supporting

Mentioning

180

Contrasting

Unclassified

Order By: Relevance

“…Indeed, a wide range of disparate MEG-derived signals have demonstrated a close spatial relationship with BOLD, including task induced changes in oscillatory power in multiple frequency bands from theta to gamma, as well as the phase locked evoked response (Moradi et al, 2003, Brookes et al, 2005, Winterer et al, 2007, Muthukumaraswamy and Singh, 2008, Zumer et al, 2010, Stevenson et al, 2011, Stevenson et al, 2012. For example, Singh and colleagues (Singh et al, 2002) Table frameworks in which to test the existence of significant spatial relationships between MEG and fMRI. This said, studies aimed at data fusion in this way must still bear in mind the potential for systematic errors in localisation, as described above.…”

Section: Spatial Relationshipsmentioning

confidence: 99%

The relationship between MEG and fMRI

et al. 2014

View full text Add to dashboard Cite

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.

show abstract

Section: Spatial Relationshipsmentioning

confidence: 99%

The relationship between MEG and fMRI

et al. 2014

View full text Add to dashboard Cite

show abstract

“…Differential estimates of power integrated over pre-defined time windows for both active and baseline activity are computed [26]; these use single-trial data over specified frequency bands and time windows throughout the brain and generate a distribution of pseudo-t values which can be displayed on individual MRIs resulting in co-registered 3-dimensional source images. Negative pseudo-t values indicate event-related desynchrony which has been shown to be related to cognitive function [27].…”

Section: Megmentioning

confidence: 99%

Localization of Broca's area using verb generation tasks in the MEG: Validation against fMRI

Pang

Wang

Malone

et al. 2011

Neuroscience Letters

View full text Add to dashboard Cite

Functional MRI (fMRI) is routinely used to non-invasively localize language areas. Magnetoencephalography (MEG) is being explored as an alternative technique. MEG tasks to localize receptive language are well established although there are no standardized tasks to localize expressive language areas. We developed two expressive language tasks for MEG and validated their localizations against fMRI data. Ten right-handed adolescents (μ=17.5 years) were tested with fMRI and MEG on two tasks: verb generation to pictures and verb generation to words. MEG and fMRI data were normalized and overlaid. The number of overlapping voxels activated in fMRI and MEG were counted for each subject, for each task, at different thresholding levels. For picture verb generation, there was 100% concordance between MEG and fMRI lateralization, and for word verb generation, there was 75% concordance. A count showed 79.6% overlap of voxels activated by both MEG and fMRI for picture verb generation and 50.2% overlap for word verb generation. The percentage overlap decreased with increasingly stringent activation thresholds. Our novel MEG expressive language tasks successfully identified neural regions involved in language production and showed high concordance with fMRI laterality. Percentage overlap of activated voxels was also high when validated against fMRI, but showed task-specific and threshold-related effects. The high concordance and high percentage overlap between fMRI and MEG activations confirm the validity of our new MEG task. Furthermore, the higher concordance from the picture verb generation task suggests that this is a promising task for use in the young clinical population.

show abstract

“…Induced oscillations are a hallmark of many neuronal systems (Gray et al, 1989;Tiitinen et al, 1993;Tass et al, 1998;Singer, 1999;Tallon-Baudry and Bertrand, 1999;Varela et al, 2001;Singh et al, 2002;TallonBaudry et al, 1997;Pantev, 1995). They are ubiquitous in both the sensory and motor systems and may play an important role in the functional integration of distributed brain systems.…”

Section: Introductionmentioning

confidence: 99%

Dynamic causal modelling of induced responses

2008

View full text Add to dashboard Cite

This paper describes a dynamic causal model (DCM) for induced or spectral responses as measured with the electroencephalogram (EEG) or the magnetoencephalogram (MEG). We model the time-varying power, over a range of frequencies, as the response of a distributed system of coupled electromagnetic sources to a spectral perturbation. The model parameters encode the frequency response to exogenous input and coupling among sources and different frequencies. The Bayesian inversion of this model, given data enables inferences about the parameters of a particular model and allows us to compare different models, or hypotheses. One key aspect of the model is that it differentiates between linear and non-linear coupling; which correspond to within and betweenfrequency coupling respectively. To establish the face validity of our approach, we generate synthetic data and test the identifiability of various parameters to ensure they can be estimated accurately, under different levels of noise. We then apply our model to EEG data from a faceperception experiment, to ask whether there is evidence for non-linear coupling between early visual cortex and fusiform areas.

show abstract

Task-Related Changes in Cortical Synchronization Are Spatially Coincident with the Hemodynamic Response

Cited by 262 publications

References 52 publications

The relationship between MEG and fMRI

The relationship between MEG and fMRI

Localization of Broca's area using verb generation tasks in the MEG: Validation against fMRI

Dynamic causal modelling of induced responses

Contact Info

Product

Resources

About