Biomedical subjects

Kevin Whittingstall

Publications and source records attributed to Kevin Whittingstall.

3 recordsLinked to original sources

PubMed2007

Evaluating the spatial relationship of event-related potential and functional MRI sources in the primary visual cortex.

The integration of electroencephalogram (EEG) recordings and functional magnetic resonance imaging (fMRI) can provide considerable insight into brain functionality. However, the direct relationship between neural and hemodynamic activity is still poorly understood. Of particular interest is the spatial correspondence between event-related potential (ERP) and fMRI sources. In the current study we localized sources generated by a checkerboard stimulus presented to eight subjects using both EEG and fMRI. The location of the sources of the visual evoked potential (VEP) were estimated at each timepoint and compared to the location of peak fMRI activity. In the majority of participants we found that the N75 dipole location coincides with a region of positive blood oxygenation level-dependent (BOLD) activation and the P100 dipole location coincides with a region of negative BOLD activation. These findings demonstrate the importance of including the negative BOLD response in combined EEG/fMRI studies.

Adult↗

PubMed2004

Dipole localization accuracy using grand-average EEG data sets.

OBJECTIVE: Dipole localization of grand-average event related potentials only give a tentative description of the estimated underlying neural sources. This study evaluates the differences in dipole solutions between individual and group-average data sets using a standard realistic head model. METHODS: Auditory evoked potentials were recorded from 14 right-handed healthy subjects using a 64 electrode montage. Inverse dipole solutions were obtained for each individual data set, as well as for all individual responses averaged together (grand-average). Differences in dipole solutions between individual and grand-average responses are reported. Simulations using a two dipole model with 15 different electrode sets are then used to investigate the effects of electrode misplacement and random noise on dipole localization. These effects are compared to those due to grand-averaging. RESULTS: The average differences in dipole locations between the individual and grand-averaged data sets were approximately 1.1 cm (SD=0.7 cm). This difference is larger than typical localization errors due to electrode misplacement and typical noise. CONCLUSIONS: Using a standard realistic head model, it is concluded that dipole solutions based on group-averaged EEG datasets are significantly different than those obtained using subject-specific data.

Adolescent↗

PubMed2003

Effects of dipole position, orientation and noise on the accuracy of EEG source localization.

BACKGROUND: The electroencephalogram (EEG) reflects the electrical activity in the brain on the surface of scalp. A major challenge in this field is the localization of sources in the brain responsible for eliciting the EEG signal measured at the scalp. In order to estimate the location of these sources, one must correctly model the sources, i.e., dipoles, as well as the volume conductor in which the resulting currents flow. In this study, we investigate the effects of dipole depth and orientation on source localization with varying sets of simulated random noise in 4 realistic head models. METHODS: Dipole simulations were performed using realistic head models and using the boundary element method (BEM). In all, 92 dipole locations placed in temporal and parietal regions of the head with varying depth and orientation were investigated along with 6 different levels of simulated random noise. Localization errors due to dipole depth, orientation and noise were investigated. RESULTS: The results indicate that there are no significant differences in localization error due tangential and radial dipoles. With high levels of simulated Gaussian noise, localization errors are depth-dependent. For low levels of added noise, errors are similar for both deep and superficial sources. CONCLUSION: It was found that if the signal-to-noise ratio is above a certain threshold, localization errors in realistic head models are, on average the same for deep and superficial sources. As the noise increases, localization errors increase, particularly for deep sources.

Artifacts↗