The Experts below are selected from a list of 240 Experts worldwide ranked by ideXlab platform
Louis Lemieux - One of the best experts on this subject based on the ideXlab platform.
-
modelling cardiac signal as a confound in eeg fmri and its application in focal Epilepsy Studies
NeuroImage, 2006Co-Authors: Adam D Liston, Torben Lund, Afraim Salekhaddadi, Khalid Hamandi, Karl J Friston, Louis LemieuxAbstract:Abstract Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance Imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet to take it into account in routine fMRI analysis. This paper reports the development of a general and robust technique to improve the reliability of EEG-fMRI Studies to BOLD signal correlated with interictal epileptiform discharges (IEDs). In these Studies, ECG is routinely recorded, enabling cardiac effects to be modelled, as effects of no interest. Our model is based on an over-complete basis set covering a linear relationship between cardiac-related MR signal and the phase of the cardiac cycle or time after pulse (TAP). This method showed that, on average, 24.6 ± 10.9% of grey matter voxels contained significant cardiac effects and 22.3 ± 24.1% of those voxels exhibiting significantly IED-correlated BOLD signal also contained significant cardiac effects. We quantified the improvement of the TAP model over the original model, without cardiac effects, by evaluating changes in efficiency, with respect to estimating the contrast of the effects of interest. Over voxels containing significant, cardiac-related signal, efficiency was improved by 18.5 ± 4.8%. Over the remaining voxels, no improvement was demonstrated. This suggests that, while improving sensitivity in particular regions of the brain, there is no risk that the TAP model will reduce sensitivity elsewhere.
-
Modelling cardiac signal as a confound in EEG-fMRI and its application in focal Epilepsy Studies
NEUROIMAGE, 2006Co-Authors: Louis LemieuxAbstract:Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet to take it into account in routine fMRI analysis. This paper reports the development of a general and robust technique to improve the reliability of EEG-fMRI Studies to BOLD signal correlated with interictal epileptiform discharges (IEDs). In these Studies, ECG is routinely recorded, enabling cardiac effects to be modelled, as effects of no interest. Our model is based on an over-complete basis set covering a linear relationship between cardiac-related MR signal and the phase of the cardiac cycle or time after pulse (TAP). This method showed that, on average, 24.6 +/- 10.9% of grey matter voxels contained significant cardiac effects and 22.3 +/- 24.1% of those voxels exhibiting significantly IED-correlated BOLD signal also contained significant cardiac effects. We quantified the improvement of the TAP model over the original model, without cardiac effects, by evaluating changes in efficiency, with respect to estimating the contrast of the effects of interest. Over voxels containing significant, cardiac-related signal, efficiency was improved by 18.5 +/- 4.8%. Over the remaining voxels, no improvement was demonstrated. This suggests that, while improving sensitivity in particular regions of the brain, there is no risk that the TAP model will reduce sensitivity elsewhere. (c) 2005 Elsevier Inc. All rights reserved.
Seokyong Choi - One of the best experts on this subject based on the ideXlab platform.
-
Author Correction: Zebrafish as an animal model in Epilepsy Studies with multichannel EEG recordings
Scientific Reports, 2017Co-Authors: Donghak Byun, Seokyong ChoiAbstract:A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.
-
zebrafish as an animal model in Epilepsy Studies with multichannel eeg recordings
Scientific Reports, 2017Co-Authors: Donghak Byun, Seokyong ChoiAbstract:Despite recent interest in using zebrafish in human disease Studies, sparked by their economics, fecundity, easy handling, and homologies to humans, the electrophysiological tools or methods for zebrafish are still inaccessible. Although zebrafish exhibit more significant larval–adult duality than any other animal, most electrophysiological Studies using zebrafish are biased by using larvae these days. The results of larval Studies not only differ from those conducted with adults but also are unable to delicately manage electroencephalographic montages due to their small size. Hence, we enabled non-invasive long-term multichannel electroencephalographic recording on adult zebrafish using custom-designed electrodes and perfusion system. First, we exploited demonstration of long-term recording on pentylenetetrazole-induced seizure models, and the results were quantified. Second, we studied skin–electrode impedance, which is crucial to the quality of signals. Then, seizure propagations and gender differences in adult zebrafish were exhibited for the first time. Our results provide a new pathway for future neuroscience research using zebrafish by overcoming the challenges for aquatic organisms such as precision, serviceability, and continuous water seepage.
Adam D Liston - One of the best experts on this subject based on the ideXlab platform.
-
modelling cardiac signal as a confound in eeg fmri and its application in focal Epilepsy Studies
NeuroImage, 2006Co-Authors: Adam D Liston, Torben Lund, Afraim Salekhaddadi, Khalid Hamandi, Karl J Friston, Louis LemieuxAbstract:Abstract Cardiac noise has been shown to reduce the sensitivity of functional Magnetic Resonance Imaging (fMRI) to an experimental effect due to its confounding presence in the blood oxygenation level-dependent (BOLD) signal. Its effect is most severe in particular regions of the brain and a method is yet to take it into account in routine fMRI analysis. This paper reports the development of a general and robust technique to improve the reliability of EEG-fMRI Studies to BOLD signal correlated with interictal epileptiform discharges (IEDs). In these Studies, ECG is routinely recorded, enabling cardiac effects to be modelled, as effects of no interest. Our model is based on an over-complete basis set covering a linear relationship between cardiac-related MR signal and the phase of the cardiac cycle or time after pulse (TAP). This method showed that, on average, 24.6 ± 10.9% of grey matter voxels contained significant cardiac effects and 22.3 ± 24.1% of those voxels exhibiting significantly IED-correlated BOLD signal also contained significant cardiac effects. We quantified the improvement of the TAP model over the original model, without cardiac effects, by evaluating changes in efficiency, with respect to estimating the contrast of the effects of interest. Over voxels containing significant, cardiac-related signal, efficiency was improved by 18.5 ± 4.8%. Over the remaining voxels, no improvement was demonstrated. This suggests that, while improving sensitivity in particular regions of the brain, there is no risk that the TAP model will reduce sensitivity elsewhere.
Richard A. Robb - One of the best experts on this subject based on the ideXlab platform.
-
quantitative and clinical analysis of spect image registration for Epilepsy Studies
The Journal of Nuclear Medicine, 1999Co-Authors: Benjamin H. Brinkmann, Brian P. Mullan, Terence J Obrien, Shmuel Aharon, Michael K Oconnor, Dennis P Hanson, Richard A. RobbAbstract:This study reports quantitative measurements of the accuracy of two popular voxel-based registration algorithms—Woods'auto mated image registration algorithm and mutual information corre lation—andcompares these with conventional surface matching (SM) registration. Methods: The registration algorithms were compared (15 different matches each) for (a) three-dimensional brain phantom images, (b) an ictal SPECT image from a patient with partial Epilepsy matched to itself after modification to simulate changes in the cerebral blood flow pattern and (c) ictal/interictal SPECT images from 15 patients with partial epi lepsy. Blinded visual ranking and localization of the subtraction images derived from the patient images were also performed. Results: Both voxel-based registrationmethods were more accurate than SM registration (P < 0.0005). Automated image registration algorithm was more accurate than mutual information correlation for the computer-simulated ictal/interictal images and the patient ictal/interictal Studies (P < 0.05). The subtraction SPECTs from SM were poorer in visual ranking more often than the voxel-basedmethods(P< 0.05). Conclusion: Voxelintensity
-
Voxel significance mapping in Epilepsy Studies using subtraction ictal SPECT
Medical Imaging 1999: Physiology and Function from Multidimensional Images, 1999Co-Authors: Benjamin H. Brinkmann, Terence J. O'brien, Desmond B. Webster, Peter D. Robins, Brian P. Mullan, Richard A. RobbAbstract:Subtraction ictal SPECT coregistered to MRI (SISCOM) has been shown to aid epileptogenic localization and improve surgical outcomes in partial Epilepsy patients. This paper reports a new method of identifying significant areas of epileptogenic activation in the SISCOM subtraction image taking into account normal variation between sequential Tc-99m Ethyl Cysteinate Diethylester SPECT scans of single individuals. The method uses the AIR 3.0 nonlinear registration software to combine a group of subtraction images into a common anatomical framework. A map of the pixel intensity standard deviation values in the subtraction images is created, and this map is nonlinearly registered to a patient's SISCOM subtraction image. Pixels in the patient subtraction image may then be evaluated based upon the statistical characteristics of corresponding pixels in the atlas. Validation experiments were performed to verify that local image variances are not constant across the image and that nonlinear registration preserves local image variances. SISCOM images created with the voxel variance method were rated higher in quality than the conventional image variance method in images from fifteen patients. No difference in localization rate was observed between the voxel variance mapping and image variance methods. The voxel significance mapping method was shown to improve the quality of clinical SISCOM images without removing localizing information.
-
Localization, correlation, and visualization of electroencephalographic surface electrodes and brain anatomy in Epilepsy Studies
Medical Imaging 1997: Physiology and Function from Multidimensional Images, 1997Co-Authors: Benjamin H. Brinkmann, Terence J. O'brien, Richard A. Robb, Frank W. SharbroughAbstract:Advances in neuroimaging have enhanced the clinician's ability to localize the epileptogenic zone in focal Epilepsy, but 20-50 percent of these cases still remain unlocalized. Many sophisticated modalities have been used to study Epilepsy, but scalp electrode recorded electroencephalography is particularly useful due to its noninvasive nature and excellent temporal resolution. This study is aimed at specific locations of scalp electrode EEG information for correlation with anatomical structures in the brain. 3D position localizing devices commonly used in virtual reality systems are used to digitize the coordinates of scalp electrodes in a standard clinical configuration. The electrode coordinates are registered with a high- resolution MRI dataset using a robust surface matching algorithm. Volume rendering can then be used to visualize the electrodes and electrode potentials interpolated over the scalp. The accuracy of the coordinate registration is assessed quantitatively with a realistic head phantom.© (1997) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.
Donghak Byun - One of the best experts on this subject based on the ideXlab platform.
-
Author Correction: Zebrafish as an animal model in Epilepsy Studies with multichannel EEG recordings
Scientific Reports, 2017Co-Authors: Donghak Byun, Seokyong ChoiAbstract:A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.
-
zebrafish as an animal model in Epilepsy Studies with multichannel eeg recordings
Scientific Reports, 2017Co-Authors: Donghak Byun, Seokyong ChoiAbstract:Despite recent interest in using zebrafish in human disease Studies, sparked by their economics, fecundity, easy handling, and homologies to humans, the electrophysiological tools or methods for zebrafish are still inaccessible. Although zebrafish exhibit more significant larval–adult duality than any other animal, most electrophysiological Studies using zebrafish are biased by using larvae these days. The results of larval Studies not only differ from those conducted with adults but also are unable to delicately manage electroencephalographic montages due to their small size. Hence, we enabled non-invasive long-term multichannel electroencephalographic recording on adult zebrafish using custom-designed electrodes and perfusion system. First, we exploited demonstration of long-term recording on pentylenetetrazole-induced seizure models, and the results were quantified. Second, we studied skin–electrode impedance, which is crucial to the quality of signals. Then, seizure propagations and gender differences in adult zebrafish were exhibited for the first time. Our results provide a new pathway for future neuroscience research using zebrafish by overcoming the challenges for aquatic organisms such as precision, serviceability, and continuous water seepage.