Modelling large motion events in fMRI studies of patients with epilepsy

EEG-correlated fMRI can provide localisation information on the generators of epileptiform discharges in patients with focal epilepsy. To increase the technique's clinical potential, it is important to consider ways of optimising the yield of each experiment while minimizing the risk of false-positive activation. Head motion can lead to severe image degradation and result in false-positive activation and is usually worse in patients than in healthy subjects. We performed general linear model fMRI data analysis on simultaneous EEG–fMRI data acquired in 34 cases with focal epilepsy. Signal changes associated with large inter-scan motion events (head jerks) were modelled using modified design matrices that include ‘scan nulling’ regressors. We evaluated the efficacy of this approach by mapping the proportion of the brain for which F-tests across the additional regressors were significant. In 95% of cases, there was a significant effect of motion in 50% of the brain or greater; for the scan nulling effect, the proportion was 36%; this effect was predominantly in the neocortex. We conclude that careful consideration of the motion-related effects in fMRI studies of patients with epilepsy is essential and that the proposed approach can be effective

EEG–fMRI of idiopathic and secondarily generalized epilepsies

We used simultaneous EEG and functional MRI (EEG–fMRI) to study generalized spike wave activity (GSW) in idiopathic and secondary generalized epilepsy (SGE). Recent studies have demonstrated thalamic and cortical fMRI signal changes in association with GSW in idiopathic generalized epilepsy (IGE). We report on a large cohort of patients that included both IGE and SGE, and give a functional interpretation of our findings. Forty-six patients with GSW were studied with EEG–fMRI; 30 with IGE and 16 with SGE. GSW-related BOLD signal changes were seen in 25 of 36 individual patients who had GSW during EEG–fMRI. This was seen in thalamus (60%) and symmetrically in frontal cortex (92%), parietal cortex (76%), and posterior cingulate cortex/precuneus (80%). Thalamic BOLD changes were predominantly positive and cortical changes predominantly negative. Group analysis showed a negative BOLD response in the cortex in the IGE group and to a lesser extent a positive response in thalamus. Thalamic activation was consistent with its known role in GSW, and its detection in individual cases with EEG–fMRI may in part be related to the number and duration of GSW epochs recorded. The spatial distribution of the cortical fMRI response to GSW in both IGE and SGE involved areas of association cortex that are most active during conscious rest. Reduction of activity in these regions during GSW is consistent with the clinical manifestation of absence seizures

Encoding of electrophysiology and other signals in MR images.

PURPOSE: To develop a gradient insensitive, generic technique for recording of non-MR signals by use of surplus scanner bandwidth. MATERIALS AND METHODS: Relatively simple battery driven hardware is used to transform one or more signals into radio waves detectable by the MR scanner. Similar to the "magstripe" technique used for encoding of soundtracks in motion pictures, the electrical signals are in this way encoded as artifacts appearing in the MR images or spectra outside the region of interest. The encoded signals are subsequently reconstructed from the signal recorded by the scanner. RESULTS: Electrophysiological (EP) eye and heart muscular recording (electrooculography [EOG] and electrocardiography [ECG]) during fast echo planar imaging (EPI) is demonstrated with an expandable, modular 8-channel prototype implementation. The gradient artifacts that would normally be dominating EOG are largely eliminated. CONCLUSION: The method provides relatively inexpensive sampling with inherent microsecond synchronization and it reduces gradient artifacts in physiological recordings significantly. When oversampling is employed, the method is compatible with all MR reconstruction and postprocessing techniques

EEG correlated functional MRI and postoperative outcome in focal epilepsy

Background: The main challenge in assessing patients with epilepsy for resective surgery is localising seizure onset. Frequently, identification of the irritative and seizure onset zones requires invasive EEG. EEG correlated functional MRI (EEG-fMRI) is a novel imaging technique which may provide localising information with regard to these regions. In patients with focal epilepsy, interictal epileptiform discharge (IED) correlated blood oxygen dependent level (BOLD) signal changes were observed in approximately 50% of patients in whom IEDs are recorded. In 70%, these are concordant with expected seizure onset defined by non-invasive electroclinical information. Assessment of clinical validity requires post-surgical outcome studies which have, to date, been limited to case reports of correlation with intracranial EEG. The value of EEG-fMRI was assessed in patients with focal epilepsy who subsequently underwent epilepsy surgery, and IED correlated fMRI signal changes were related to the resection area and clinical outcome. Methods: Simultaneous EEG-fMRI was recorded in 76 patients undergoing presurgical evaluation and the locations of IED correlated preoperative BOLD signal change were compared with the resected area and postoperative outcome. Results: 21 patients had activations with epileptic activity on EEG-fMRI and 10 underwent surgical resection. Seven of 10 patients were seizure free following surgery and the area of maximal BOLD signal change was concordant with resection in six of seven patients. In the remaining three patients, with reduced seizure frequency post-surgically, areas of significant IED correlated BOLD signal change lay outside the resection. 42 of 55 patients who had no IED related activation underwent resection. Conclusion: These results show the potential value of EEG-fMRI in presurgical evaluation

Temporal lobe interictal epileptic discharges affect cerebral activity in "default mode" brain regions

A cerebral network comprising precuneus, medial frontal, and temporoparietal cortices is less active both during goal-directed behavior and states of reduced consciousness than during conscious rest. We tested the hypothesis that the interictal epileptic discharges affect activity in these brain regions in patients with temporal lobe epilepsy who have complex partial seizures. At the group level, using electroencephalography-correlated functional magnetic resonance imaging in 19 consecutive patients with focal epilepsy, we found common decreases of resting state activity in 9 patients with temporal lobe epilepsy (TLE) but not in 10 patients with extra-TLE. We infer that the functional consequences of TLE interictal epileptic discharges are different from those in extra-TLE and affect ongoing brain function. Activity increases were detected in the ipsilateral hippocampus in patients with TLE, and in subthalamic, bilateral superior temporal and medial frontal brain regions in patients with extra-TLE, possibly indicating effects of different interictal epileptic discharge propagation

Causal hierarchy within the thalamo-cortical network in spike and wave discharges

Background: Generalised spike wave (GSW) discharges are the electroencephalographic (EEG) hallmark of absence seizures, clinically characterised by a transitory interruption of ongoing activities and impaired consciousness, occurring during states of reduced awareness. Several theories have been proposed to explain the pathophysiology of GSW discharges and the role of thalamus and cortex as generators. In this work we extend the existing theories by hypothesizing a role for the precuneus, a brain region neglected in previous works on GSW generation but already known to be linked to consciousness and awareness. We analysed fMRI data using dynamic causal modelling (DCM) to investigate the effective connectivity between precuneus, thalamus and prefrontal cortex in patients with GSW discharges. Methodology and Principal Findings: We analysed fMRI data from seven patients affected by Idiopathic Generalized Epilepsy (IGE) with frequent GSW discharges and significant GSW-correlated haemodynamic signal changes in the thalamus, the prefrontal cortex and the precuneus. Using DCM we assessed their effective connectivity, i.e. which region drives another region. Three dynamic causal models were constructed: GSW was modelled as autonomous input to the thalamus (model A), ventromedial prefrontal cortex (model B), and precuneus (model C). Bayesian model comparison revealed Model C (GSW as autonomous input to precuneus), to be the best in 5 patients while model A prevailed in two cases. At the group level model C dominated and at the population-level the p value of model C was ∼1. Conclusion: Our results provide strong evidence that activity in the precuneus gates GSW discharges in the thalamo-(fronto) cortical network. This study is the first demonstration of a causal link between haemodynamic changes in the precuneus - an index of awareness - and the occurrence of pathological discharges in epilepsy. © 2009 Vaudano et al

Motor system hyperconnectivity in juvenile myoclonic epilepsy: a cognitive functional magnetic resonance imaging study

Juvenile myoclonic epilepsy is the most frequent idiopathic generalized epilepsy syndrome. It is characterized by predominant myoclonic jerks of upper limbs, often provoked by cognitive activities, and typically responsive to treatment with sodium valproate. Neurophysiological, neuropsychological and imaging studies in juvenile myoclonic epilepsy have consistently pointed towards subtle abnormalities in the medial frontal lobes. Using functional magnetic resonance imaging with an executive frontal lobe paradigm, we investigated cortical activation patterns and interaction between cortical regions in 30 patients with juvenile myoclonic epilepsy and 26 healthy controls. With increasing cognitive demand, patients showed increasing coactivation of the primary motor cortex and supplementary motor area. This effect was stronger in patients still suffering from seizures, and was not seen in healthy controls. Patients with juvenile myoclonic epilepsy showed increased functional connectivity between the motor system and frontoparietal cognitive networks. Furthermore, we found impaired deactivation of the default mode network during cognitive tasks with persistent activation in medial frontal and central regions in patients. Coactivation in the motor cortex and supplementary motor area with increasing cognitive load and increased functional coupling between the motor system and cognitive networks provide an explanation how cognitive effort can cause myoclonic jerks in juvenile myoclonic epilepsy. The supplementary motor area represents the anatomical link between these two functional systems, and our findings may be the functional correlate of previously described structural abnormalities in the medial frontal lobe in juvenile myoclonic epilepsy

Exploring the relative efficacy of motion artefact correction techniques for EEG data acquired during simultaneous fMRI

Simultaneous EEG-fMRI allows multi-parametric characterisation of brain function, in principle enabling a more complete understanding of brain responses; unfortunately the hostile MRI environment severely reduces EEG data quality. Simply eliminating data segments containing gross motion artefacts [MAs] (generated by movement of the EEG system and head in the MRI scanner’s static magnetic field) was previously believed sufficient. However recently the importance of removal of all MAs has been highlighted and new methods developed.A systematic comparison of the ability to remove MAs and retain underlying neuronal activity using different methods of MA detection and post-processing algorithms is needed to guide the neuroscience community. Using a head phantom, we recorded MAs while simultaneously monitoring the motion using three different approaches: Reference Layer Artefact Subtraction (RLAS), Moire Phase Tracker (MPT) markers, and Wire Loop Motion Sensors (WLMS). These EEG recordings were combined with EEG responses to simple visual tasks acquired on a subject outside the MRI environment. MAs were then corrected using the motion information collected with each of the methods combined with different analysis pipelines.All tested methods retained the neuronal signal. However, often the MA was not removed sufficiently to allow accurate detection of the underlying neuronal signal. We show that the MA is best corrected using the RLAS combined with post-processing using a multi-channel, recursive least squares (M-RLS) algorithm. This method needs to be developed further to enable practical utility; thus, WLMS combined with M-RLS currently provides the best compromise between EEG data quality and practicalities of motion detection