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Chang-Hwan Im

Publications and source records attributed to Chang-Hwan Im.

7 recordsLinked to original sources

Dealing with mismatched fMRI activations in fMRI constrained EEG cortical source imaging: a simulation study assuming various mismatch types.

Although fMRI constrained EEG source imaging could be a promising approach to enhancing both spatial and temporal resolutions of independent fMRI and EEG analyses, it has been frequently reported that a hard fMRI constraint may cause severe distortion or elimination of significant EEG sources when there are distinct mismatches between fMRI activations and EEG sources. If estimating actual EEG source locations is important and fMRI prior information is used as an auxiliary tool to enhance the concentration of widespread EEG source distributions, it is reasonable to weaken the fMRI constraint when significantly mismatched sources exist. The present study demonstrates that the mismatch problem may be partially solved by extending the prior fMRI activation regions based on the conventional source imaging results. A hard fMRI constraint is then applied when there is no distinct mismatch, while a weakened fMRI constraint is applied when there are significant mismatches. A preliminary simulation study assuming different types of mismatches such as fMRI invisible, extra, and discrepancy sources demonstrated that this approach can be a promising option to treat mismatched fMRI activations in fMRI constrained EEG source imaging.

Algorithms↗

Spatial resolution of EEG cortical source imaging revealed by localization of retinotopic organization in human primary visual cortex.

The aim of the present study is to investigate the spatial resolution of electroencephalography (EEG) cortical source imaging by localizing the retinotopic organization in the human primary visual cortex (V1). Retinotopic characteristics in V1 obtained from functional magnetic resonance imaging (fMRI) study were used as reference to assess the spatial resolution of EEG since fMRI can discriminate small changes in activation in visual field. It is well known that the activation of the early C1 component in the visual evoked potential (VEP) elicited by pattern onset stimuli coincides well with the activation in the striate cortex localized by fMRI. In the present experiments, we moved small circular checkerboard stimuli along horizontal meridian and compared the activations localized by EEG cortical source imaging with those from fMRI. Both fMRI and EEG cortical source imaging identified spatially correlated activity within V1 in each subject studied. The mean location error, between the fMRI-determined activation centers in V1 and the EEG source imaging activation peak estimated at equivalent C1 components (peak latency: 74.8+/-10.6 ms), was 7 mm (25% and 75% percentiles are 6.45 mm and 8.4 mm, respectively), which is less than the change in fMRI activation map by a 3 degrees visual field change (7.8 mm). Moreover, the source estimates at the earliest major VEP component showed statistically good correlation with those obtained by fMRI. The present results suggest that the spatial resolution of the EEG cortical source imaging can correctly discriminate cortical activation changes in V1 corresponding to less than 3 degrees visual field changes.

Adult↗

A technique to consider mismatches between fMRI and EEG/MEG sources for fMRI-constrained EEG/MEG source imaging: a preliminary simulation study.

fMRI-constrained EEG/MEG source imaging can be a powerful tool in studying human brain functions with enhanced spatial and temporal resolutions. Recent studies on the combination of fMRI and EEG/MEG have suggested that fMRI prior information could be readily implemented by simply imposing different weighting factors to cortical sources overlapping with the fMRI activations. It has been also reported, however, that such a hard constraint may cause severe distortions or elimination of meaningful EEG/MEG sources when there are distinct mismatches between the fMRI activations and the EEG/MEG sources. If one wants to obtain the actual EEG/MEG source locations and uses the fMRI prior information as just an auxiliary tool to enhance focality of the distributed EEG/MEG sources, it is reasonable to weaken the strength of fMRI constraint when severe mismatches between fMRI and EEG/MEG sources are observed. The present study suggests an efficient technique to automatically adjust the strength of fMRI constraint according to the mismatch level. The use of the proposed technique rarely affects the results of conventional fMRI-constrained EEG/MEG source imaging if no major mismatch between the two modalities is detected; while the new results become similar to those of typical EEG/MEG source imaging without fMRI constraint if the mismatch level is significant. A preliminary simulation study using realistic EEG signals demonstrated that the proposed technique can be a promising tool to selectively apply fMRI prior information to EEG/MEG source imaging.

Biophysical Phenomena↗

Functional cortical source imaging from simultaneously recorded ERP and fMRI.

Feasibility of continuously and simultaneously recording visual evoked potentials (VEPs) with fMRI was assessed by quantitatively comparing cortical source images by means of receiver operating characteristic (ROC) curve analysis. The averaged EEG source images coincided well with simultaneously acquired fMRI activations. Strong correlation was found between the cortical source images of VEPs recorded inside and outside the scanner. Application of fMRI prior information strengthened correlation between estimated source images as well as resulted in source estimates with higher spatial resolution. The present results demonstrate that reliable cortical source images can be acquired during simultaneous fMRI scanning and they may be used for multimodal functional source imaging studies.

Adult↗

Anatomically constrained dipole adjustment (ANACONDA) for accurate MEG/EEG focal source localizations.

This paper proposes an alternative approach to enhance localization accuracy of MEG and EEG focal sources. The proposed approach assumes anatomically constrained spatio-temporal dipoles, initial positions of which are estimated from local peak positions of distributed sources obtained from a pre-execution of distributed source reconstruction. The positions of the dipoles are then adjusted on the cortical surface using a novel updating scheme named cortical surface scanning. The proposed approach has many advantages over the conventional ones: (1) as the cortical surface scanning algorithm uses spatio-temporal dipoles, it is robust with respect to noise; (2) it requires no a priori information on the numbers and initial locations of the activations; (3) as the locations of dipoles are restricted only on a tessellated cortical surface, it is physiologically more plausible than the conventional ECD model. To verify the proposed approach, it was applied to several realistic MEG/EEG simulations and practical experiments. From the several case studies, it is concluded that the anatomically constrained dipole adjustment (ANACONDA) approach will be a very promising technique to enhance accuracy of focal source localization which is essential in many clinical and neurological applications of MEG and EEG.

Algorithms↗

fMRI-constrained MEG source imaging and consideration of fMRI invisible sources.

Recent studies on multimodal brain source imaging have shown that the use of functional MRI (fMRI) prior information could enhance spatial resolution of magnetoencephalography (MEG), while MEG could compensate poor temporal resolution of fMRI. This article deals with a multimodal imaging method, which combines fMRI and MEG for enhancing both spatial and temporal resolutions. Recent studies on the combination of fMRI and MEG have suggested that the fMRI prior information could be very easily implemented by just giving different weighting factors to the diagonal terms of source covariance matrix in linear inverse operator. We applied the fMRI constrained imaging method to several simulation data and experimental data (Japanese language lexical judgment experiment), and found that some MEG sources may be eliminated by the introduction of the fMRI weighting and the eliminated sources may affect source estimation in fMRI activation regions. In this article, in order to check whether the eliminated sources were fMRI invisible ones or just spurious ones, we placed small numbers of regional sources (rotating dipoles) around all possible activation regions and investigated their temporal changes. By investigating the results carefully, we could evaluate whether the missed sources were real or not.

Algorithms↗

Assessment criteria for MEG/EEG cortical patch tests.

To validate newly developed methods or implemented software for magnetoencephalography/electroencephalography (MEG/EEG) source localization problems, many researchers have used human skull phantom experiments or artificially constructed forward data sets. Between the two methods, the use of an artificial data set constructed with forward calculation attains superiority over the use of a human skull phantom in that it is simple to implement, adjust and control various conditions. Nowadays, for the forward calculation, especially for the cortically distributed source models, generating artificial activation patches on a brain cortical surface has been popularized instead of activating some point dipole sources. However, no well-established assessment criterion to validate the reconstructed results quantitatively has yet been introduced. In this paper, we suggest some assessment criteria to compare and validate the various MEG/EEG source localization techniques or implemented software applied to the cortically distributed source model. Four different criteria can be used to measure accuracy, degrees of focalization, noise-robustness, existence of spurious sources and so on. To verify the usefulness of the proposed criteria, four different results from two different noise conditions and two different reconstruction techniques were compared for several patches. The simulated results show that the new criteria can provide us with a reliable index to validate the MEG/EEG source localization techniques.

Algorithms↗