Integration of multimodal neuroimaging methods: a rationale for clinical applications of simultaneous EEG-fMRI

Abstract

Functional magnetic resonance imaging (fMRI), which has high spatial resolution, is increasingly used to evaluate cerebral functions in neurological and psychiatric diseases. The main limitation of fMRI is that it detects neural activity indirectly, through the associated slow hemodynamic variations. Because neurovascular coupling can be regionally altered by pathological conditions or drugs, fMRI responses may not truly reflect neural activity. Electroencephalography (EEG) recordings, which directly detect neural activity with optimal temporal resolution, can now be obtained during fMRI data acquisition. Therefore, there is a growing interest in combining the techniques to obtain simultaneous EEG-fMRI recordings. The EEG-fMRI approach has several promising clinical applications. The first is the detection of cortical areas involved in interictal and ictal epileptic activity. Second, combining evoked potentials with fMRI could be an accurate way to study eloquent cortical areas for the planning of neurosurgery or rehabilitation, circumventing the above-mentioned limitation of fMRI. Finally, the use of this approach to evaluate the functional connectivity of resting-state networks would extend the applications of EEG-fMRI to uncooperative or unconscious patients. Integration of multimodal neuroimaging methods: a rationale for clinical applications of simultaneous EEG-fMRI.

Figure 1

The classical spike-triggered method in a case of focal epilepsy. Patient (female, 23 yrs) with focal epilepsy and multiple nodules of subependymal heterotopia, mainly in the right hemisphere (A). EEG-fMRI acquisition of two EPI scans triggered by interictal epileptic activities (spikes and waves) recorded on the scalp, mainly from the T4-T6-P4 electrodes (B). After acquiring an equal number of EPI scans without spikes for at least 25”, the interictal and basal images were statistically compared by t-test analysis (statistical parametric mapping). The fMRI map disclosed right temporoparietal areas of BOLD decrease, including a deep cluster located within one of the subependymal nodules (C).

Figure 2

Continuous EEG-fMRI in focal epilepsy. Structural MRI scan shows bilateral periventricular nodular heterotopia (Panel A, red arrows). Scalp EEG demonstrates short sequences of interictal spike and spike-wave discharges mainly on the right frontotemporal leads, highlighted in the red box (Panel B, left image). Panel B, right image shows the EEG recorded simultaneously during fMRI acquisitions after off-line subtraction of gradient artifacts. The EEG trace (32 channels) is displayed in bipolar montage. The consecutive numbers on the EEG (in blue) indicate the corresponding EPI acquired. Note the presence of interictal abnormalities over the right frontotemporal regions, highlighted by the red box. Panel C: IED-related BOLD results (p<0.05 corrected for family-wise errors). SPM8 software (http://www.fil.ion.ucl.ac.uk/spm/) was used for data analysis. Main clusters of BOLD signal increase (global maxima) were detected at the right temporopolar cortex and at the right nodules of subependymal heterotopia. No decrease in BOLD signal was observed. The fMRI results are displayed on the patient’s high-resolution T1-weighted structural scan. L: left; R: right.

Figure 3

Continuous EEG-fMRI. Another case of focal epilepsy, with iEEG and good post-operative outcome. Interictal scalp EEG demonstrated isolated spikes and sharp waves over the frontocentral leads (Panel A). Panel B shows the patient’s structural FLAIR images (coronal and axial slices): the red arrow indicates a large cortical gliotic lesion over the left frontomedial region. Panel C: IED-related BOLD results derived from simultaneous acquisition of EEG and fMRI data (p<0.05 corrected for family-wise errors). SPM8 software (http://www.fil.ion.ucl.ac.uk/spm/) was used for data analysis. A main cluster of BOLD signal increase (global maxima) was detected at the left frontomedial cortex, overlapping the lesion. Other blobs were detected at the ipsilateral cerebellum and thalamus and a small cluster was detected over the left posterior cingulate. No decreases in BOLD signal were detected. The fMRI results are displayed on the patient’s high-resolution T1-weighted structural scan. Panel D: representative page of the intracranial recordings with subdural electrodes performed for pre-surgical purposes. A 5x4 grid was located over the left frontomedial cortex covering the structural lesion (small snapshot at the bottom right of the image). The electrodes A1, A2, A3, A4, B3, B4, C3, C4 (highlighted in red) showed continuous interictal spiking. Panel E: following the icEEG recording, a lesionectomy was performed (left image, the continuous red line indicates the boundary of the surgical resection). The right image shows a CT scan performed after surgery. The patient is seizure-free at three years of follow-up (ILAE, Class Ia). L: left; R: right.

Figure 4

The standard networks usually identified in rs-fMRI. Twelve resting-state networks identified by independent component analysis (by MELODIC, part of FSL software package) of the total fMRI data from 27 elderly subjects (mean age: 65 years). MVN and LVN=medial visual and lateral visual networks; AN=auditory network; MN=motor network; R FPN and L FPN=right and left frontoparietal networks; Inf and Sup Cerebellum=inferior and superior cerebellum; BGN=basal ganglia network; EN=executive control network; DAN=dorsal attentional network; DMN=default mode network. All images are z-statistics thresholded at p<0.05, overlaid onto the average scan in the standard MNI152 space, according to radiological convention. Figure courtesy of Dr Letizia Casiraghi.