- Email: [email protected]
24. Methods to determine anatomical and functional connectivity
Society Proceedings / Clinical Neurophysiology 119 (2008) e99–e164
alternating pattern; (5) the abnormalities of sleep microstructure; (6) the abnormalities of EEG spectral activities; (7) the relations between EEG and non EEG variables; (8) the presence of abnormal phenomena either in the EEG or in the non-EEG variables. Taking as examples insomnia, fibromyalgia, periodic limb movements, sleep apnea and sleepwalking these abnormalities are presented and analysed in order to achieve physiopathological information. Sleep fragmentation is a feature of poor sleep. It can be induced by periodic limb movements of even by sleep apnea. Furthermore other parameters and symptoms may induce awakenings such as arrhythmias, oesophageal reflux, nicturia, pain, headaches, nocturnal eating and excessive dreaming. Their corresponding relations to the sleep structure are detailed. doi:10.1016/j.clinph.2008.04.038
23. EEG–fMRI: (Germany)
Neurovascular
coupling—K. Uludag
The relationship between hemodynamic response and underlying neural activity is still poorly understood. Complementary non-invasive multimodality experiments on human subjects such as EEG and fMRI can provide new insights into this link. In this study, using very short visual stimulus durations (0.1–5 ms) we have investigated the relationship between fMRI and visual evoked potentials (VEP). Short stimulus durations rather than commonly used standard durations in fMRI experiments are ideal to investigate the neuro-vascular coupling because non-linearities of hemodynamic response are minimized. We found that both the integral of the BOLD response and the peak value of N75 response increase monotonically with increasing stimulus duration. Other VEP peaks (e.g. P100) did not correlate with the BOLD signal. However, to alteration in stimulus duration, both measurements respond non-linearly though differently. Thus, the non-linearities in N75 component of VEP response cannot alone account for the non-linearities observed in BOLD response. In addition, we will present results of how EEG oscillations (power and phase) are altered by very short stimulations. This study suggests that, although under some experimental conditions correlations exist between fMRI and electrophysiology signals, both are not causally linked to each other. doi:10.1016/j.clinph.2008.04.039
e105
anatomical information can be introduced into the problem of characterizing brain functional circuits involved in the cognitive and sensorial processing using the electric/magnetic activity from EEG/MEG and fMRI. The new method to characterize the intravoxel anisotropy provides information about the probability of finding a fiber in a particular spatial orientation; and maps of the probability to find a particular number of fibers and the most probable number of fibers for each voxel. On other hand the fiber tracking methodology is developed under Graph theory formalism, where different anatomical connectivity matrices were defined: Anatomical Connection Strength (ACS), Anatomical Connection Density (ACD) and Anatomical Connection Probability (ACP). Based on this approach, complex networks properties such as small-world attributes, efficiency, degree distribution, are studied in subjects of the Cuban Human Brain Mapping Project. doi:10.1016/j.clinph.2008.04.040
25. Simultaneous EEG and fMRI– A unique neurophysiologic technique—J. Stern (USA) The simultaneous recording of EEG and functional MRI (SEM) is unique in its direct integration of two central brain mapping techniques. As such, SEM promises equally unique insights into cerebral activity, but it also presents significant challenges. Combining two techniques is not a novel concept. Indeed, all brain mapping techniques are expected to provide incomplete information about brain function and a more full understanding arises from comparisons of different techniques’ results. However, SEM is unique by producing images that include aspects of EEG’s high temporal resolution and sensitivity to electrophysiologic changes and functional MRI’s high spatial resolution and sensitivity to metabolic changes. Combining these differing aspects of brain function poses a challenge to interpretation because the result conveys something different than both EEG and functional MRI. Acquisition of data with SEM is another challenge. Safely recording EEG from individuals in the MRI environment and then removing the electrical noise from the EEG data is not straightforward, but several successful solutions are now in place. Despite these challenges, SEM continues to develop in its applicability to multiple areas of clinical neurophysiology, including epilepsy, sleep, and cognitive neuroscience. doi:10.1016/j.clinph.2008.04.041
24. Methods to determine anatomical and functional connectivity—L. Melie Garcı´a, Y. Iturria Medina, E. Canales Rodrı´guez, Y. Alema´n Go´mez, P.A. Valde´s Herna´ndez (Cuba)
26. Using software for change in science—M. Brett (United Kingdom)
Diffusion Weighted Imaging is a noninvasive technique that provides quantitative maps of the micro structural organization and physiological features of living tissues. There are three levels of analysis of this neuroimaging modality: (1) characterization of the intravoxel anisotropy, (2) fiber tracking that estimates routes linking two particular structures in the brain, (3) anatomic measures definition to characterize the anatomical networks in the brain. The aim of this work is twofold: (1) to develop new methods in the three levels above mentioned and (2) to discuss how this
It used to be said that the world runs on oil, but now it is at least as true to say that the world runs on software. This is nowhere more true than the world of neuroimaging. The most successful neuroimaging software is open-source, for good reason. To understand the data, you need to understand the software, and, as methods change fast, understanding data means being able to read and use code. This is one major reason why SPM has been so successful in fMRI analysis. The move towards open-source has brought with it a new spirit of openness and
alternating pattern; (5) the abnormalities of sleep microstructure; (6) the abnormalities of EEG spectral activities; (7) the relations between EEG and non EEG variables; (8) the presence of abnormal phenomena either in the EEG or in the non-EEG variables. Taking as examples insomnia, fibromyalgia, periodic limb movements, sleep apnea and sleepwalking these abnormalities are presented and analysed in order to achieve physiopathological information. Sleep fragmentation is a feature of poor sleep. It can be induced by periodic limb movements of even by sleep apnea. Furthermore other parameters and symptoms may induce awakenings such as arrhythmias, oesophageal reflux, nicturia, pain, headaches, nocturnal eating and excessive dreaming. Their corresponding relations to the sleep structure are detailed. doi:10.1016/j.clinph.2008.04.038
23. EEG–fMRI: (Germany)
Neurovascular
coupling—K. Uludag
The relationship between hemodynamic response and underlying neural activity is still poorly understood. Complementary non-invasive multimodality experiments on human subjects such as EEG and fMRI can provide new insights into this link. In this study, using very short visual stimulus durations (0.1–5 ms) we have investigated the relationship between fMRI and visual evoked potentials (VEP). Short stimulus durations rather than commonly used standard durations in fMRI experiments are ideal to investigate the neuro-vascular coupling because non-linearities of hemodynamic response are minimized. We found that both the integral of the BOLD response and the peak value of N75 response increase monotonically with increasing stimulus duration. Other VEP peaks (e.g. P100) did not correlate with the BOLD signal. However, to alteration in stimulus duration, both measurements respond non-linearly though differently. Thus, the non-linearities in N75 component of VEP response cannot alone account for the non-linearities observed in BOLD response. In addition, we will present results of how EEG oscillations (power and phase) are altered by very short stimulations. This study suggests that, although under some experimental conditions correlations exist between fMRI and electrophysiology signals, both are not causally linked to each other. doi:10.1016/j.clinph.2008.04.039
e105
anatomical information can be introduced into the problem of characterizing brain functional circuits involved in the cognitive and sensorial processing using the electric/magnetic activity from EEG/MEG and fMRI. The new method to characterize the intravoxel anisotropy provides information about the probability of finding a fiber in a particular spatial orientation; and maps of the probability to find a particular number of fibers and the most probable number of fibers for each voxel. On other hand the fiber tracking methodology is developed under Graph theory formalism, where different anatomical connectivity matrices were defined: Anatomical Connection Strength (ACS), Anatomical Connection Density (ACD) and Anatomical Connection Probability (ACP). Based on this approach, complex networks properties such as small-world attributes, efficiency, degree distribution, are studied in subjects of the Cuban Human Brain Mapping Project. doi:10.1016/j.clinph.2008.04.040
25. Simultaneous EEG and fMRI– A unique neurophysiologic technique—J. Stern (USA) The simultaneous recording of EEG and functional MRI (SEM) is unique in its direct integration of two central brain mapping techniques. As such, SEM promises equally unique insights into cerebral activity, but it also presents significant challenges. Combining two techniques is not a novel concept. Indeed, all brain mapping techniques are expected to provide incomplete information about brain function and a more full understanding arises from comparisons of different techniques’ results. However, SEM is unique by producing images that include aspects of EEG’s high temporal resolution and sensitivity to electrophysiologic changes and functional MRI’s high spatial resolution and sensitivity to metabolic changes. Combining these differing aspects of brain function poses a challenge to interpretation because the result conveys something different than both EEG and functional MRI. Acquisition of data with SEM is another challenge. Safely recording EEG from individuals in the MRI environment and then removing the electrical noise from the EEG data is not straightforward, but several successful solutions are now in place. Despite these challenges, SEM continues to develop in its applicability to multiple areas of clinical neurophysiology, including epilepsy, sleep, and cognitive neuroscience. doi:10.1016/j.clinph.2008.04.041
24. Methods to determine anatomical and functional connectivity—L. Melie Garcı´a, Y. Iturria Medina, E. Canales Rodrı´guez, Y. Alema´n Go´mez, P.A. Valde´s Herna´ndez (Cuba)
26. Using software for change in science—M. Brett (United Kingdom)
Diffusion Weighted Imaging is a noninvasive technique that provides quantitative maps of the micro structural organization and physiological features of living tissues. There are three levels of analysis of this neuroimaging modality: (1) characterization of the intravoxel anisotropy, (2) fiber tracking that estimates routes linking two particular structures in the brain, (3) anatomic measures definition to characterize the anatomical networks in the brain. The aim of this work is twofold: (1) to develop new methods in the three levels above mentioned and (2) to discuss how this
It used to be said that the world runs on oil, but now it is at least as true to say that the world runs on software. This is nowhere more true than the world of neuroimaging. The most successful neuroimaging software is open-source, for good reason. To understand the data, you need to understand the software, and, as methods change fast, understanding data means being able to read and use code. This is one major reason why SPM has been so successful in fMRI analysis. The move towards open-source has brought with it a new spirit of openness and