Early changes in alpha band power and DMN BOLD activity in Alzheimer's disease: a simultaneous resting state EEG-fMRI study

Simultaneous resting state functional magnetic resonance imaging (rsfMRI)-resting state electroencephalography (rsEEG) studies in healthy adults showed robust positive associations of signal power in the alpha band with BOLD signal in the thalamus, and more heterogeneous associations in cortical default mode network (DMN) regions. Negative associations were found in occipital regions. In Alzheimer's disease (AD), rsfMRI studies revealed a disruption of the DMN, while rsEEG studies consistently reported a reduced power within the alpha band. The present study is the first to employ simultaneous rsfMRI-rsEEG in an AD sample, investigating the association of alpha band power and BOLD signal, compared to healthy controls (HC). We hypothesized to find reduced positive associations in DMN regions and reduced negative associations in occipital regions in the AD group. Simultaneous resting state fMRI-EEG was recorded in 14 patients with mild AD and 14 HC, matched for age and gender. Power within the EEG alpha band (8-12 Hz, 8-10 Hz, and 10-12 Hz) was computed from occipital electrodes and served as regressor in voxel-wise linear regression analyses, to assess the association with the BOLD signal. Compared to HC, the AD group showed significantly decreased positive associations between BOLD signal and occipital alpha band power in clusters in the superior, middle and inferior frontal cortex, inferior temporal lobe and thalamus (p < 0.01, uncorr., cluster size ≥ 50 voxels). This group effect was more pronounced in the upper alpha sub-band, compared to the lower alpha sub-band. Notably, we observed a high inter-individual heterogeneity. Negative associations were only reduced in the lower alpha range in the hippocampus, putamen and cerebellum. The present study gives first insights into the relationship of resting-state EEG and fMRI characteristics in an AD sample. The results suggest that positive associations between alpha band power and BOLD signal in numerous regions, including DMN regions, are diminished in AD

Imaging haemodynamic changes related to seizures: comparison of EEG-based general linear model, independent component analysis of fMRI and intracranial EEG

Background: Simultaneous EEG-fMRI can reveal haemodynamic changes associated with epileptic activity which may contribute to understanding seizure onset and propagation. Methods: Nine of 83 patients with focal epilepsy undergoing pre-surgical evaluation had seizures during EEG-fMRI and analysed using three approaches, two based on the general linear model (GLM) and one using independent component analysis (ICA): 1. EEGs were divided into up to three phases: early ictal EEG change, clinical seizure onset and late ictal EEG change and convolved with a canonical haemodynamic response function (HRF) (canonical GLM analysis). 2. Seizures lasting three scans or longer were additionally modelled using a Fourier basis set across the entire event (Fourier GLM analysis). 3. Independent component analysis (ICA) was applied to the fMRI data to identify ictal BOLD patterns without EEG. The results were compared with intracranial EEG. Results: The canonical GLM analysis revealed significant BOLD signal changes associated with seizures on EEG in 7/9 patients, concordant with the seizure onset zone in 4/7. The Fourier GLM analysis revealed changes in BOLD signal corresponding with the results of the canonical analysis in two patients. ICA revealed components spatially concordant with the seizure onset zone in all patients (8/9 confirmed by intracranial EEG). Conclusion: Ictal EEG-fMRI visualises plausible seizure related haemodynamic changes. The GLM approach to analysing EEG-fMRI data reveals localised BOLD changes concordant with the ictal onset zone when scalp EEG reflects seizure onset. ICA provides additional information when scalp EEG does not accurately reflect seizures and may give insight into ictal haemodynamics

Independent component analysis of interictal fMRI in focal epilepsy: comparison with general linear model-based EEG-correlated fMRI

The general linear model (GLM) has been used to analyze simultaneous EEG–fMRI to reveal BOLD changes linked to interictal epileptic discharges (IED) identified on scalp EEG. This approach is ineffective when IED are not evident in the EEG. Data-driven fMRI analysis techniques that do not require an EEG derived model may offer a solution in these circumstances. We compared the findings of independent components analysis (ICA) and EEG-based GLM analyses of fMRI data from eight patients with focal epilepsy. Spatial ICA was used to extract independent components (IC) which were automatically classified as either BOLD-related, motion artefacts, EPI-susceptibility artefacts, large blood vessels, noise at high spatial or temporal frequency. The classifier reduced the number of candidate IC by 78%, with an average of 16 BOLD-related IC. Concordance between the ICA and GLM-derived results was assessed based on spatio-temporal criteria. In each patient, one of the IC satisfied the criteria to correspond to IED-based GLM result. The remaining IC were consistent with BOLD patterns of spontaneous brain activity and may include epileptic activity that was not evident on the scalp EEG. In conclusion, ICA of fMRI is capable of revealing areas of epileptic activity in patients with focal epilepsy and may be useful for the analysis of EEG–fMRI data in which abnormalities are not apparent on scalp EEG

A Dose Relationship Between Brain Functional Connectivity and Cumulative Head Impact Exposure in Collegiate Water Polo Players.

A growing body of evidence suggests that chronic, sport-related head impact exposure can impair brain functional integration and brain structure and function. Evidence of a robust inverse relationship between the frequency and magnitude of repeated head impacts and disturbed brain network function is needed to strengthen an argument for causality. In pursuing such a relationship, we used cap-worn inertial sensors to measure the frequency and magnitude of head impacts sustained by eighteen intercollegiate water polo athletes monitored over a single season of play. Participants were evaluated before and after the season using computerized cognitive tests of inhibitory control and resting electroencephalography. Greater head impact exposure was associated with increased phase synchrony [r (16) &gt; 0.626, p &lt; 0.03 corrected], global efficiency [r (16) &gt; 0.601, p &lt; 0.04 corrected], and mean clustering coefficient [r (16) &gt; 0.625, p &lt; 0.03 corrected] in the functional networks formed by slow-wave (delta, theta) oscillations. Head impact exposure was not associated with changes in performance on the inhibitory control tasks. However, those with the greatest impact exposure showed an association between changes in resting-state connectivity and a dissociation between performance on the tasks after the season [r (16) = 0.481, p = 0.043] that could also be attributed to increased slow-wave synchrony [F (4, 135) = 113.546, p &lt; 0.001]. Collectively, our results suggest that athletes sustaining the greatest head impact exposure exhibited changes in whole-brain functional connectivity that were associated with altered information processing and inhibitory control

Mapping preictal and ictal haemodynamic networks using video-electroencephalography and functional imaging

Ictal patterns on scalp-electroencephalography are often visible only after propagation, therefore rendering localization of the seizure onset zone challenging. We hypothesized that mapping haemodynamic changes before and during seizures using simultaneous video-electroencephalography and functional imaging will improve the localization of the seizure onset zone. Fifty-five patients with ≥2 refractory focal seizures/day, and who had undergone long-term video-electroencephalography monitoring were included in the study. ‘Preictal' (30 s immediately preceding the electrographic seizure onset) and ictal phases, ‘ictal-onset'; ‘ictalestablished' and ‘late ictal', were defined based on the evolution of the electrographic pattern and clinical semiology. The functional imaging data were analysed using statistical parametric mapping to map ictal phase-related haemodynamic changes consistent across seizures. The resulting haemodynamic maps were overlaid on co-registered anatomical scans, and the spatial concordance with the presumed and invasively defined seizure onset zone was determined. Twenty patients had typical seizures during functional imaging. Seizures were identified on video-electroencephalography in 15 of 20, on electroencephalography alone in two and on video alone in three patients. All patients showed significant ictal-related haemodynamic changes. In the six cases that underwent invasive evaluation, the ictal-onset phase-related maps had a degree of concordance with the presumed seizure onset zone for all patients. The most statistically significant haemodynamic cluster within the presumed seizure onset zone was between 1.1 and 3.5 cm from the invasively defined seizure onset zone, which was resected in two of three patients undergoing surgery (Class I post-surgical outcome) and was not resected in one patient (Class III post-surgical outcome). In the remaining 14 cases, the ictal-onset phase-related maps had a degree of concordance with the presumed seizure onset zone in six of eight patients with structural-lesions and five of six non-lesional patients. The most statistically significant haemodynamic cluster was localizable at sub-lobar level within the presumed seizure onset zone in six patients. The degree of concordance of haemodynamic maps was significantly better (P < 0.05) for the ictal-onset phase [entirely concordant/concordant plus (13/20; 65%) + some concordance (4/20; 20%) = 17/20; 85%] than ictal-established [entirely concordant/concordant plus (5/13; 38%) + some concordance (4/13; 31%) = 9/13; 69%] and late ictal [concordant plus (1/9; 11%) + some concordance (4/9; 44%) = 5/9; 55%] phases. Ictal propagation-related haemodynamic changes were also seen in symptomatogenic areas (9/20; 45%) and the default mode network (13/20; 65%). A common pattern of preictal changes was seen in 15 patients, starting between 98 and 14 s before electrographic seizure onset, and the maps had a degree of concordance with the presumed seizure onset zone in 10 patients. In conclusion, preictal and ictal haemodynamic changes in refractory focal seizures can non-invasively localize seizure onset at sub-lobar/gyral level when ictal scalp-electroencephalography is not helpfu

EEG-Based Quantification of Cortical Current Density and Dynamic Causal Connectivity Generalized across Subjects Performing BCI-Monitored Cognitive Tasks.

Quantification of dynamic causal interactions among brain regions constitutes an important component of conducting research and developing applications in experimental and translational neuroscience. Furthermore, cortical networks with dynamic causal connectivity in brain-computer interface (BCI) applications offer a more comprehensive view of brain states implicated in behavior than do individual brain regions. However, models of cortical network dynamics are difficult to generalize across subjects because current electroencephalography (EEG) signal analysis techniques are limited in their ability to reliably localize sources across subjects. We propose an algorithmic and computational framework for identifying cortical networks across subjects in which dynamic causal connectivity is modeled among user-selected cortical regions of interest (ROIs). We demonstrate the strength of the proposed framework using a "reach/saccade to spatial target" cognitive task performed by 10 right-handed individuals. Modeling of causal cortical interactions was accomplished through measurement of cortical activity using (EEG), application of independent component clustering to identify cortical ROIs as network nodes, estimation of cortical current density using cortically constrained low resolution electromagnetic brain tomography (cLORETA), multivariate autoregressive (MVAR) modeling of representative cortical activity signals from each ROI, and quantification of the dynamic causal interaction among the identified ROIs using the Short-time direct Directed Transfer function (SdDTF). The resulting cortical network and the computed causal dynamics among its nodes exhibited physiologically plausible behavior, consistent with past results reported in the literature. This physiological plausibility of the results strengthens the framework's applicability in reliably capturing complex brain functionality, which is required by applications, such as diagnostics and BCI

Neuronal networks in children with continuous spikes and waves during slow sleep

Epileptic encephalopathy with continuous spikes and waves during slow sleep is an age-related disorder characterized by the presence of interictal epileptiform discharges during at least >85% of sleep and cognitive deficits associated with this electroencephalography pattern. The pathophysiological mechanisms of continuous spikes and waves during slow sleep and neuropsychological deficits associated with this condition are still poorly understood. Here, we investigated the haemodynamic changes associated with epileptic activity using simultaneous acquisitions of electroencephalography and functional magnetic resonance imaging in 12 children with symptomatic and cryptogenic continuous spikes and waves during slow sleep. We compared the results of magnetic resonance to electric source analysis carried out using a distributed linear inverse solution at two time points of the averaged epileptic spike. All patients demonstrated highly significant spike-related positive (activations) and negative (deactivations) blood oxygenation-level-dependent changes (P < 0.05, family-wise error corrected). The activations involved bilateral perisylvian region and cingulate gyrus in all cases, bilateral frontal cortex in five, bilateral parietal cortex in one and thalamus in five cases. Electrical source analysis demonstrated a similar involvement of the perisylvian brain regions in all patients, independent of the area of spike generation. The spike-related deactivations were found in structures of the default mode network (precuneus, parietal cortex and medial frontal cortex) in all patients and in caudate nucleus in four. Group analyses emphasized the described individual differences. Despite aetiological heterogeneity, patients with continuous spikes and waves during slow sleep were characterized by activation of the similar neuronal network: perisylvian region, insula and cingulate gyrus. Comparison with the electrical source analysis results suggests that the activations correspond to both initiation and propagation pathways. The deactivations in structures of the default mode network are consistent with the concept of epileptiform activity impacting on normal brain function by inducing repetitive interruptions of neurophysiological functio