Electrophysiological correlates of the BOLD signal for EEG-informed fMRI

EEG and fMRI are important tools in cognitive and clinical neuroscience. Combined EEGfMRI has been shown to help to characterise brain networks involved in epileptic activity, as well as in different sensory, motor and cognitive functions. A good understanding of the electrophysiological correlates of the blood oxygen level dependent (BOLD) signal is necessary to interpret fMRI maps, particularly when obtained in combination with EEG. We review the current understanding of electrophysiological-haemodynamic correlates, during different types of brain activity. We start by describing the basic mechanisms underlying EEG and BOLD signals, and proceed by reviewing EEG-informed fMRI studies using fMRI to map specific EEG phenomena over the entire brain (“EEG-fMRI mapping”), or exploring a range of EEGderived quantities to determine which best explain co-localised BOLD fluctuations (“local EEG-fMRI coupling”). While reviewing studies of different forms of brain activity (epileptic and non-epileptic spontaneous activity; cognitive, sensory and motor functions), a significant attention is given to epilepsy because the investigation of its haemodynamic correlates is the most common application of EEG-informed fMRI. Our review is focused on EEG-informed fMRI, an asymmetric approach of data integration. We give special attention to the invasiveness of electrophysiological measurements and the simultaneity of multimodal acquisitions because these methodological aspects determine the nature of the conclusions that can be drawn from EEG-informed fMRI studies. We emphasise the advantages of, and need for, simultaneous intracranial EEG-fMRI studies in humans, which recently became available and hold great potential to improve our understanding of the electrophysiological correlates of BOLD fluctuations

Imaging functional and structural networks in the human epileptic brain

Epileptic activity in the brain arises from dysfunctional neuronal networks involving cortical and subcortical grey matter as well as their connections via white matter fibres. Physiological brain networks can be affected by the structural abnormalities causing the epileptic activity, or by the epileptic activity itself. A better knowledge of physiological and pathological brain networks in patients with epilepsy is critical for a better understanding the patterns of seizure generation, propagation and termination as well as the alteration of physiological brain networks by a chronic neurological disorder. Moreover, the identification of pathological and physiological networks in an individual subject is critical for the planning of epilepsy surgery aiming at resection or at least interruption of the epileptic network while sparing physiological networks which have potentially been remodelled by the disease. This work describes the combination of neuroimaging methods to study the functional epileptic networks in the brain, structural connectivity changes of the motor networks in patients with localisation-related or generalised epilepsy and finally structural connectivity of the epileptic network. The combination between EEG source imaging and simultaneous EEG-fMRI recordings allowed to distinguish between regions of onset and propagation of interictal epileptic activity and to better map the epileptic network using the continuous activity of the epileptic source. These results are complemented by the first recordings of simultaneous intracranial EEG and fMRI in human. This whole-brain imaging technique revealed regional as well as distant haemodynamic changes related to very focal epileptic activity. The combination of fMRI and DTI tractography showed subtle changes in the structural connectivity of patients with Juvenile Myoclonic Epilepsy, a form of idiopathic generalised epilepsy. Finally, a combination of intracranial EEG and tractography was used to explore the structural connectivity of epileptic networks. Clinical relevance, methodological issues and future perspectives are discussed

Early soft and flexible fusion of electroencephalography and functional magnetic resonance imaging via double coupled matrix tensor factorization for multisubject group analysis

Data fusion refers to the joint analysis of multiple datasets that provide different (e.g., complementary) views of the same task. In general, it can extract more information than separate analyses can. Jointly analyzing electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) measurements has been proved to be highly beneficial to the study of the brain function, mainly because these neuroimaging modalities have complementary spatiotemporal resolution: EEG offers good temporal resolution while fMRI is better in its spatial resolution. The EEG–fMRI fusion methods that have been reported so far ignore the underlying multiway nature of the data in at least one of the modalities and/or rely on very strong assumptions concerning the relation of the respective datasets. For example, in multisubject analysis, it is commonly assumed that the hemodynamic response function is a priori known for all subjects and/or the coupling across corresponding modes is assumed to be exact (hard). In this article, these two limitations are overcome by adopting tensor models for both modalities and by following soft and flexible coupling approaches to implement the multimodal fusion. The obtained results are compared against those of parallel independent component analysis and hard coupling alternatives, with both synthetic and real data (epilepsy and visual oddball paradigm). Our results demonstrate the clear advantage of using soft and flexible coupled tensor decompositions in scenarios that do not conform with the hard coupling assumption

Imaging brain networks in focal epilepsy: a prospective study of the clinical application of simultaneous EEG-fMRI in pre-surgical evaluation

Epilepsy is a common disorder with significant associated morbidity and mortality. Despite advances in treatment, there remain a minority of people with pharmacoresistant focal epilepsy for whom surgery may be beneficial. It has been suggested that not enough people are offered surgical treatment, partly owing to the fact that current non-invasive techniques do not always adequately identify the seizure onset zone so that invasive EEG is required. EEG-fMRI is an imaging technique, developed in the 1990s (Ives, Warach et al. 1993) which identifies regions of interictal epileptiform discharge associated haemodynamic changes, that are concordant with the seizure onset zone in some patients (Salek-Haddadi, Diehl et al. 2006). To date there has been no large scale prospective comparison with icEEG and postoperative outcome. This thesis presents a series of experiments, carried out in a cohort of patients scanned using EEG-fMRI as part of a multi-centre programme, designed to investigate the relationship between EEG-fMRI and intracranial EEG and to assess its potential role in pre-surgical evaluation of patients with focal epilepsy. The results suggested that positive, localised IED-related BOLD signal changes were sensitive for the seizure onset zone, as determined on icEEG, both in patients neocortical epilepsies, but were not predictive of outcome. Widespread regions of positive IEDrelated BOLD signal change were associated with widespread or multifocal abnormalities on icEEG and poor outcome. Patterns of haemodynamic change, identified using both data driven and EEG derived modeling approaches, correspond to regions of seizure onset on icEEG, but improvements for modeling seizures are required. A study of a single seizure in a patient who underwent simultaneous icEEGfMRI, showed similar findings.. An exploratory investigation of fMRI-DCM in EEG-fMRI, suggested it can provide information about seizure propagation and this opens new avenues for the non-invasive study of the epileptic network and interactions with function

Neuroimaging of Epilepsy: Lesions, Networks, Oscillations

While analysis and interpretation of structural epileptogenic lesion is an essential task for the neuroradiologist in clinical practice, a substantial body of epilepsy research has shown that focal lesions influence brain areas beyond the epileptogenic lesion, across ensembles of functionally and anatomically connected brain areas. In this review article, we aim to provide an overview about altered network compositions in epilepsy, as measured with current advanced neuroimaging techniques to characterize the initiation and spread of epileptic activity in the brain with multimodal noninvasive imaging techniques. We focus on resting-state functional magnetic resonance imaging (MRI) and simultaneous electroencephalography/fMRI, and oppose the findings in idiopathic generalized versus focal epilepsies. These data indicate that circumscribed epileptogenic lesions can have extended effects on many brain systems. Although epileptic seizures may involve various brain areas, seizure activity does not spread diffusely throughout the brain but propagates along specific anatomic pathways that characterize the underlying epilepsy syndrome. Such a functionally oriented approach may help to better understand a range of clinical phenomena such as the type of cognitive impairment, the development of pharmacoresistance, the propagation pathways of seizures, or the success of epilepsy surgery

Advanced Invasive Neurophysiological Methods to Aid Decision Making in Paediatric Epilepsy Surgery

For patients with drug-resistant focal epilepsy, surgery is the most effective treatment to attain seizure freedom. Intracranial electroencephalogram investigations succeed in defining the seizure onset zone (SOZ) where non-invasive methods fail to identify a single seizure generator. However, resection of the SOZ does not always lead to a surgical benefit and, in addition, eloquent functions like language might be compromised. The aim of this thesis was to use advanced invasive neurophysiological methods to improve pre-surgical planning in two ways. The first aim was to improve delineation of the pathological tissue, the SOZ using novel quantitative neurophysiological biomarkers: high gamma activity (80–150Hz) phase-locked to low frequency iEEG discharges (phase-locked high gamma, PLHG) and high frequency oscillations called fast ripples (FR, 250–500Hz). Resection of contacts containing these markers were recently reported to lead to an improved seizure outcome. The current work shows the first replication of the PLHG metric in a small adult pilot study and a larger paediatric cohort. Furthermore, I tested whether surgical removal of PLHG- and/or FR-generating brain areas resulted in better outcome compared to the current clinical SOZ delineation. The second aim of this work was to aid delineation of eloquent language cortex. Invasive event-related potentials (iERP) and spectral changes in the beta and gamma frequency bands were used to determine cortical dynamics during speech perception and production across widespread brain regions. Furthermore, the relationship between these cortical dynamics and the relationship to electrical stimulation responses was explored. For delineation of pathological tissue, the combination of FRs and SOZ proved to be a promising biomarker. Localising language cortex showed the highest level of activity around the perisylvian brain regions with a significantly higher occurrence rate of iERPs compared to spectral changes. Concerning electrical stimulation mapping beta and high gamma frequency bands represented the most promising markers

Concurrent fNIRS and EEG for brain function investigation: A systematic, methodology-focused review

Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) stand as state-of-the-art techniques for non-invasive functional neuroimaging. On a unimodal basis, EEG has poor spatial resolution while presenting high temporal resolution. In contrast, fNIRS offers better spatial resolution, though it is constrained by its poor temporal resolution. One important merit shared by the EEG and fNIRS is that both modalities have favorable portability and could be integrated into a compatible experimental setup, providing a compelling ground for the development of a multimodal fNIRS-EEG integration analysis approach. Despite a growing number of studies using concurrent fNIRS-EEG designs reported in recent years, the methodological reference of past studies remains unclear. To fill this knowledge gap, this review critically summarizes the status of analysis methods currently used in concurrent fNIRS-EEG studies, providing an up-to-date overview and guideline for future projects to conduct concurrent fNIRS-EEG studies. A literature search was conducted using PubMed and Web of Science through 31 August 2021. After screening and qualification assessment, 92 studies involving concurrent fNIRS-EEG data recordings and analyses were included in the final methodological review. Specifically, three methodological categories of concurrent fNIRS-EEG data analyses, including EEG-informed fNIRS analyses, fNIRS-informed EEG analyses, and parallel fNIRS-EEG analyses, were identified and explained with detailed description. Finally, we highlighted current challenges and potential directions in concurrent fNIRS-EEG data analyses in future research