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Dive into the research topics where Arjan Hillebrand is active.

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Featured researches published by Arjan Hillebrand.


Human Brain Mapping | 2005

A new approach to neuroimaging with magnetoencephalography

Arjan Hillebrand; Krish Devi Singh; Ian E. Holliday; Paul L. Furlong; Gareth R. Barnes

We discuss the application of beamforming techniques to the field of magnetoencephalography (MEG). We argue that beamformers have given us an insight into the dynamics of oscillatory changes across the cortex not explored previously with traditional analysis techniques that rely on averaged evoked responses. We review several experiments that have used beamformers, with special emphasis on those in which the results have been compared to those observed in functional magnetic resonance imaging (fMRI) and on those studying induced phenomena. We suggest that the success of the beamformer technique, despite the assumption that there are no linear interactions between the mesoscopic local field potentials across distinct cortical areas, may tell us something of the balance between functional integration and segregation in the human brain. What is more, MEG beamformer analysis facilitates the study of these complex interactions within cortical networks that are involved in both sensory‐motor and cognitive processes. Hum. Brain Mapp 25:199–211, 2005.


NeuroImage | 2002

Task-related changes in cortical synchronization are spatially coincident with the hemodynamic response.

Krish D. Singh; Gareth R. Barnes; Arjan Hillebrand; Emer M. E. Forde; Adrian Williams

Using group functional Magnetic Resonance Imaging (fMRI) and group Magnetoencephalography (MEG) we studied two cognitive paradigms: A language task involving covert letter fluency and a visual task involving biological motion direction discrimination. The MEG data were analyzed using an adaptive beam-former technique known as Synthetic Aperture Magnetometry (SAM), which provides continuous 3-D images of cortical power changes. These images were spatially normalized and averaged across subjects to provide a group SAM image in the same template space as the group fMRI data. The results show that frequency-specific, task-related changes in cortical synchronization, detected using MEG, match those areas of the brain showing an evoked cortical hemodynamic response with fMRI. The majority of these changes were event-related desynchronizations (ERDs) in the 5-10 Hz and 15-25 Hz frequency ranges. Our study demonstrates how SAM, spatial normalization, and intersubject averaging enable group MEG studies to be performed. SAM analysis also allows the MEG experiment to have exactly the same task design as the corresponding fMRI experiment. This new analysis framework represents an important advance in the use of MEG as a cognitive neuroimaging technique and also allows mutual cross-validation with fMRI.


NeuroImage | 2002

A quantitative assessment of the sensitivity of whole-head MEG to activity in the adult human cortex.

Arjan Hillebrand; Gareth R. Barnes

MagnetoEncephaloGraphy (MEG) relies on the detection of cortical current flow by measurement of the associated magnetic field outside the head. The amplitude of this magnetic field depends strongly on the depth of the electrical brain activity. Additionally, radially orientated sources are magnetically silent in a concentrically homogeneous volume conductor, giving rise to the anecdotal assumptions that MEG is insensitive to both deep and gyral sources. Utilising cortical surfaces extracted from Magnetic Resonance Images (MRIs) of two adult brains we constructed all possible single source elements and examined the proportion of active neocortex that is actually detectable with a whole-head MEG system. We identified those electrically active regions to which MEG is maximally sensitive by analytically computing the probability of detecting a source within a specified confidence volume. Our findings show that source depth, and not orientation, is the main factor that compromises the sensitivity of MEG to activity in the adult human cortex. There are thin strips (approximately 2 mm wide) of poor resolvability at the crests of gyri; however, these strips account for only a relatively small proportion of the cortical area and are abutted by elements with nominal tangential component yet high resolvability due to their proximity to the sensor array. Finally, we varied the extent of the patches of cortical activity, showing that small patches have a small net-current moment and are therefore less visible whereas large patches have a strong net-current moment, are generally more visible to the MEG system, yet are less appropriately modelled as single dipoles.


NeuroImage | 2003

Group imaging of task-related changes in cortical synchronisation using nonparametric permutation testing.

Krish Devi Singh; Gareth R. Barnes; Arjan Hillebrand

Synthetic aperture magnetometry (SAM) is a nonlinear beamformer technique for producing 3D images of cortical activity from magnetoencephalography data. We have previously shown how SAM images can be spatially normalised and averaged to form a group image. In this paper we show how nonparametric permutation methods can be used to make robust statistical inference about group SAM data. Data from a biological motion direction discrimination experiment were analysed using both a nonparametric analysis toolbox (SnPM) and a conventional parametric approach utilising Gaussian field theory. In data from a group of six subjects, we were able to show robust group activation at the P < 0.05 (corrected) level using the nonparametric methods, while no significant clusters were found using the conventional parametric approach. Activation was found using SnPM in several regions of right occipital-temporal cortex, including the superior temporal sulcus, V5/MT, the fusiform gyrus, and the lateral occipital complex.


Human Brain Mapping | 2003

Statistical flattening of MEG beamformer images

Gareth R. Barnes; Arjan Hillebrand

We propose a method of correction for multiple comparisons in MEG beamformer based Statistical Parametric Maps (SPMs). We introduce a modification to the minimum‐variance beamformer, in which beamformer weights and SPMs of source‐power change are computed in distinct steps. This approach allows the calculation of image smoothness based on the computed weights alone. In the first instance we estimate image smoothness by looking at local spatial correlations in residual images generated using random data; we then go on to show how the smoothness of the SPM can be obtained analytically by measuring the correlations between the adjacent weight vectors. In simulations we show that the smoothness of the SPM is highly inhomogeneous and depends on the source strength. We show that, for the minimum variance beamformer, knowledge of image smoothness is sufficient to allow for correction of the multiple comparison problem. Per‐voxel threshold estimates, based on the voxels extent (or cluster size) in flattened space, provide accurate corrected false positive error rates for these highly inhomogeneously smooth images. Hum. Brain Mapping 18:1–12, 2003.


NeuroImage | 2005

GLM-beamformer method demonstrates stationary field, alpha ERD and gamma ERS co-localisation with fMRI BOLD response in visual cortex

Matthew J. Brookes; Andrew M. Gibson; Stephen D. Hall; Paul L. Furlong; Gareth R. Barnes; Arjan Hillebrand; Krish Devi Singh; Ian E. Holliday; Peter G. Morris

Recently, we introduced a new GLM-beamformer technique for MEG analysis that enables accurate localisation of both phase-locked and non-phase-locked neuromagnetic effects, and their representation as statistical parametric maps (SPMs). This provides a useful framework for comparison of the full range of MEG responses with fMRI BOLD results. This paper reports a proof of principle study using a simple visual paradigm (static checkerboard). The five subjects each underwent both MEG and fMRI paradigms. We demonstrate, for the first time, the presence of a sustained (DC) field in the visual cortex, and its co-localisation with the visual BOLD response. The GLM-beamformer analysis method is also used to investigate the main non-phase-locked oscillatory effects: an event-related desynchronisation (ERD) in the alpha band (8-13 Hz) and an event-related synchronisation (ERS) in the gamma band (55-70 Hz). We show, using SPMs and virtual electrode traces, the spatio-temporal covariance of these effects with the visual BOLD response. Comparisons between MEG and fMRI data sets generally focus on the relationship between the BOLD response and the transient evoked response. Here, we show that the stationary field and changes in oscillatory power are also important contributors to the BOLD response, and should be included in future studies on the relationship between neuronal activation and the haemodynamic response.


NeuroImage | 2004

Visual word recognition: the first half second.

Kristen Pammer; Peter C. Hansen; Morten L. Kringelbach; Ian E. Holliday; Gareth R. Barnes; Arjan Hillebrand; Krish Devi Singh; Piers L. Cornelissen

We used magnetoencephalography (MEG) to map the spatiotemporal evolution of cortical activity for visual word recognition. We show that for five-letter words, activity in the left hemisphere (LH) fusiform gyrus expands systematically in both the posterior-anterior and medial-lateral directions over the course of the first 500 ms after stimulus presentation. Contrary to what would be expected from cognitive models and hemodynamic studies, the component of this activity that spatially coincides with the visual word form area (VWFA) is not active until around 200 ms post-stimulus, and critically, this activity is preceded by and co-active with activity in parts of the inferior frontal gyrus (IFG, BA44/6). The spread of activity in the VWFA for words does not appear in isolation but is co-active in parallel with spread of activity in anterior middle temporal gyrus (aMTG, BA 21 and 38), posterior middle temporal gyrus (pMTG, BA37/39), and IFG.


NeuroImage | 2008

Optimising experimental design for MEG beamformer imaging

Matthew J. Brookes; Jiri Vrba; Stephen E. Robinson; Claire M. Stevenson; Andrew Peters; Gareth R. Barnes; Arjan Hillebrand; Peter G. Morris

In recent years, the use of beamformers for source localisation has significantly improved the spatial accuracy of magnetoencephalography. In this paper, we examine techniques by which to optimise experimental design, and ensure that the application of beamformers yields accurate results. We show that variation in the experimental duration, or variation in the bandwidth of a signal of interest, can significantly affect the accuracy of a beamformer reconstruction of source power. Specifically, power will usually be underestimated if covariance windows are made too short, or bandwidths too narrow. The accuracy of spatial localisation may also be reduced. We conclude that for optimum accuracy, experimenters should aim to collect as much data as possible, and use a bandwidth spanning the entire frequency distribution of the signal of interest. This minimises distortion to reconstructed source images, time courses and power estimation. In the case where experimental duration is short, and small covariance windows are therefore used, we show that accurate power estimation can be achieved by matrix regularisation. However, large amounts of regularisation cause a loss in the spatial resolution of the MEG beamformer, hence regularisation should be used carefully, particularly if multiple sources in close proximity are expected.


International Review of Neurobiology | 2005

Beamformer Analysis of MEG Data

Arjan Hillebrand; Gareth R. Barnes

Publisher Summary This chapter discusses a source reconstruction approach, beamforming, which was only recently introduced to electroencephalography (EEG) and magnetoencephalography (MEG). As with any other source reconstruction method, a set of a priori assumptions are made so that a solution to the inverse problemcan be obtained. The main assumption behind the beamformer approach is that no two distant cortical areas generate coherent local field potentials over long time scales; it has been shown empirically that this is a reasonable assumption set. The reason the beamformer assumption set although simplistic, may indeed be quite plausible is argued on the basis of anatomical and electrophysiological data. The time when the assumptions might fail is described and suggestions for improvements in the beamformer implementations are presented. Beamforming is an exciting new approach to MEGsource reconstruction that could provide another stepping stone on the route towards an appropriate assumption set with which to non-invasively image the brain.


European Journal of Neuroscience | 2004

Induced visual illusions and gamma oscillations in human primary visual cortex

Peyman Adjamian; Ian E. Holliday; Gareth R. Barnes; Arjan Hillebrand; Avgis Hadjipapas; Krish Devi Singh

Using magnetoencephalography, we studied the spatiotemporal properties of cortical responses in terms of event‐related synchronization and event‐related desynchronization to a range of stripe patterns in subjects with no neurological disorders. These stripes are known for their tendency to induce a range of abnormal sensations, such as illusions, nausea, dizziness, headache and attacks of pattern‐sensitive epilepsy. The optimal stimulus must have specific physical properties, and maximum abnormalities occur at specific spatial frequency and contrast. Despite individual differences in the severity of discomfort experienced, psychophysical studies have shown that most observers experience some degree of visual anomaly on viewing such patterns. In a separate experiment, subjects reported the incidence of illusions and discomfort to each pattern. We found maximal cortical power in the gamma range (30–60u2003Hz) confined to the region of the primary visual cortex in response to patterns of 2–4u2003cycles per degree, peaking at 3u2003cycles per degree. This coincides with the peak of mean illusions and discomfort, also maximal for patterns of 2–4u2003cycles per degree. We show that gamma band activity in V1 is a narrow band function of spatial frequency. We hypothesize that the intrinsic properties of gamma oscillations may underlie visual discomfort and play a role in the onset of seizures.

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Gareth R. Barnes

Wellcome Trust Centre for Neuroimaging

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Cornelis J. Stam

VU University Medical Center

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