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Both electroencephalography (EEG) and functional Magnetic Resonance Imaging (fMRI) are non-invasive methods that show complementary aspects of human brain activity. Despite measuring different proxies of brain activity, both the measured blood-oxygenation (fMRI) and neurophysiological recordings (EEG) are indirectly coupled. The electrophysiological and BOLD signal can map the underlying functional connectivity structure at the whole brain scale at different timescales. Previous work demonstrated a moderate but significant correlation between resting-state functional connectivity of both modalities, however there is a wide range of technical setups to measure simultaneous EEG-fMRI and the reliability of those measures between different setups remains unknown. This is true notably with respect to different magnetic field strengths (low and high field) and different spatial sampling of EEG (medium to high-density electrode coverage). Here, we investigated the reproducibility of the bimodal EEG-fMRI functional connectome in the most comprehensive resting-state simultaneous EEG-fMRI dataset compiled to date including a total of 72 subjects from four different imaging centers. Data was acquired from 1.5T, 3T and 7T scanners with simultaneously recorded EEG using 64 or 256 electrodes. We demonstrate that the whole-brain monomodal connectivity reproducibly correlates across different datasets and that a moderate crossmodal correlation between EEG and fMRI connectivity of r ≈ 0.3 can be reproducibly extracted in low- and high-field scanners. The crossmodal correlation was strongest in the EEG-β frequency band but exists across all frequency bands. Both homotopic and within intrinsic connectivity network (ICN) connections contributed the most to the crossmodal relationship. This study confirms, using a considerably diverse range of recording setups, that simultaneous EEG-fMRI offers a consistent estimate of multimodal functional connectomes in healthy subjects that are dominantly linked through a functional core of ICNs across spanning across the different timescales measured by EEG and fMRI. This opens new avenues for estimating the dynamics of brain function and provides a better understanding of interactions between EEG and fMRI measures. This observed level of reproducibility also defines a baseline for the study of alterations of this coupling in pathological conditions and their role as potential clinical markers., (Copyright © 2021. Published by Elsevier Inc.)

Long-range connectivity has become the most studied feature of human functional Magnetic Resonance Imaging (fMRI), yet the spatial and temporal relationship between its whole-brain dynamics and electrophysiological connectivity remains largely unknown. FMRI-derived functional connectivity exhibits spatial reconfigurations or time-varying dynamics at infraslow (<0.1Hz) speeds. Conversely, electrophysiological connectivity is based on cross-region coupling of fast oscillations (~1-100Hz). It is unclear whether such fast oscillation-based coupling varies at infraslow speeds, temporally coinciding with infraslow dynamics across the fMRI-based connectome. If so, does the association of fMRI-derived and electrophysiological dynamics spatially vary over the connectome across the functionally distinct electrophysiological oscillation bands? In two concurrent electroencephalography (EEG)-fMRI resting-state datasets, oscillation-based coherence in all canonical bands (delta through gamma) indeed reconfigured at infraslow speeds in tandem with fMRI-derived connectivity changes in corresponding region-pairs. Interestingly, irrespective of EEG frequency-band the cross-modal tie of connectivity dynamics comprised a large proportion of connections distributed across the entire connectome. However, there were frequency-specific differences in the relative strength of the cross-modal association. This association was strongest in visual to somatomotor connections for slower EEG-bands, and in connections involving the Default Mode Network for faster EEG-bands. Methodologically, the findings imply that neural connectivity dynamics can be reliably measured by fMRI despite heavy susceptibility to noise, and by EEG despite shortcomings of source reconstruction. Biologically, the findings provide evidence that contrast with known territories of oscillation power, oscillation coupling in all bands slowly reconfigures in a highly distributed manner across the whole-brain connectome., Competing Interests: Declaration of competing interest The authors declare no competing interests., (Copyright © 2020 The Authors. Published by Elsevier Inc. All rights reserved.)

While averaged dynamics of brain function are known to estimate the underlying structure, the exact relationship between large-scale function and structure remains an unsolved issue in network neuroscience. These complex functional dynamics, measured by EEG and fMRI, are thought to arise from a shared underlying structural architecture, which can be measured by diffusion MRI (dMRI). While simulation and data transformation (e.g. graph theory measures) have been proposed to refine the understanding of the underlying function-structure relationship, the potential complementary and/or independent contribution of EEG and fMRI to this relationship is still poorly understood. As such, we explored this relationship by analyzing the function-structure correlation in fourteen healthy subjects with simultaneous resting-state EEG-fMRI and dMRI acquisitions. We show that the combination of EEG and fMRI connectivity better explains dMRI connectivity and that this represents a genuine model improvement over fMRI-only models for both group-averaged connectivity matrices and at the individual level. Furthermore, this model improves the prediction within each resting-state network. The best model fit to underlying structure is mediated by fMRI and EEG-δ connectivity in combination with Euclidean distance and interhemispheric connectivity with more local contributions of EEG-γ at the scale of resting-state networks. This highlights that the factors mediating the relationship between functional and structural metrics of connectivity are context and scale dependent, influenced by topological, geometric and architectural features. It also suggests that fMRI studies employing simultaneous EEG measures may characterize additional and essential parts of the underlying neuronal activity of the resting-state, which might be of special interest for both clinical studies and the investigation of resting-state dynamics., (Copyright © 2017 Elsevier Inc. All rights reserved.)

For the first time in research in humans, we used simultaneous icEEG-fMRI to examine the link between connectivity in haemodynamic signals during the resting-state (rs) and connectivity derived from electrophysiological activity in terms of the inter-modal connectivity correlation (IMCC). We quantified IMCC in nine patients with drug-resistant epilepsy (i) within brain networks in 'healthy' non-involved cortical zones (NIZ) and (ii) within brain networks involved in generating seizures and interictal spikes (IZ1) or solely spikes (IZ2). Functional connectivity (h 2 ) estimates for 10 min of resting-state data were obtained between each pair of electrodes within each clinical zone for both icEEG and fMRI. A sliding window approach allowed us to quantify the variability over time of h 2 (vh 2 ) as an indicator of connectivity dynamics. We observe significant positive IMCC for h 2 and vh 2 , for multiple bands in the NIZ only, with the strongest effect in the lower icEEG frequencies. Similarly, intra-modal h 2 and vh 2 were found to be differently modified as a function of different epileptic processes: compared to NIZ, [Formula: see text] was higher in IZ1, but lower in IZ2, while [Formula: see text] showed the inverse pattern. This corroborates previous observations of inter-modal connectivity discrepancies in pathological cortices, while providing the first direct invasive and simultaneous comparison in humans. We also studied time-resolved FC variability multimodally for the first time, finding that IZ1 shows both elevated internal [Formula: see text] and less rich dynamical variability, suggesting that its chronic role in epileptogenesis may be linked to greater homogeneity in self-sustaining pathological oscillatory states.

In light of technical advancements supporting exploration of MR signals other than 1 H, sodium ( 23 Na) has received attention as a marker of ionic homeostasis and cell viability. Here, we evaluate for the first time the possibility that 23 Na-MRI is sensitive to pathological processes occurring in human epilepsy. A normative sample of 27 controls was used to normalize regions of interest (ROIs) from 1424 unique brain locales on quantitative 23 Na-MRI and high-resolution 1 H-MPRAGE images. ROIs were based on intracerebral electrodes in ten patients undergoing epileptic network mapping. The stereo-EEG gold standard was used to define regions as belonging to primarily epileptogenic, secondarily irritative and to non-involved regions. Estimates of total sodium concentration (TSC) on 23 Na-MRI and cerebrospinal fluid (CSF) on 1 H imaging were extracted for each patient ROI, and normalized against the same region in controls. ROIs with disproportionate CSF contributions (Z CSF ≥1.96) were excluded. TSC levels were found to be elevated in patients relative to controls except in one patient, who suffered non-convulsive seizures during the scan, in whom we found reduced TSC levels. In the remaining patients, an ANOVA (F 1100 = 12.37, p<0.0001) revealed a highly significant effect of clinically-defined zones (F 1100 = 11.13, p<0.0001), with higher normalized TSC in the epileptogenic zone relative to both secondarily irritative (F 1100 = 11, p=0.0009) and non-involved regions (F 1100 = 17.8, p<0.0001). We provide the first non-invasive, in vivo evidence of a chronic TSC elevation alongside Z CSF levels within the normative range, associated with the epileptogenic region even during the interictal period in human epilepsy, and the possibility of reduced TSC levels due to seizure. In line with modified homeostatic mechanisms in epilepsy - including altered mechanisms underlying ionic gating, clearance and exchange - we provide the first indication of 23 Na-MRI as an assay of altered sodium concentrations occurring in epilepsy associated with the organization of clinically relevant divisions of pathological cortex., (Copyright © 2017 Elsevier Inc. All rights reserved.)

The aim of this study was to investigate the neural substrate underlying quality of life (QoL) and to demonstrate the microstructural abnormalities associated with impaired QoL in a large sample of patients with schizophrenia, using magnetisation transfer imaging. A total of 81 right-handed men with a diagnosis of schizophrenia and 25 age- and sex-similar healthy controls were included and underwent a 3T MRI with magnetization transfer ratio (MTR) to detect microstructural abnormalities. Compared with healthy controls, patients with schizophrenia had grey matter (GM) decreased MTR values in the temporal lobe (BA21, BA37 and BA38), the bilateral insula, the occipital lobe (BA17, BA18 and BA19) and the cerebellum. Patients with impaired QoL had lower GM MTR values relative to patients with preserved QoL in the bilateral temporal pole (BA38), the bilateral insula, the secondary visual cortex (BA18), the vermis and the cerebellum. Significant correlations between MTR values and QoL scores (p < 0.005) were observed in the GM of patients in the right temporal pole (BA38), the bilateral insula, the vermis and the right cerebellum. Our study shows that QoL impairment in patients with schizophrenia is related to the microstructural changes in an extensive network, suggesting that QoL is a bio-psychosocial marker.

The impact of the hemisphere affected by impairment in models of network disease is not fully understood. Among such models, focal epilepsies are characterised by recurrent seizures generated in epileptogenic areas also responsible for wider network dysfunction between seizures. Previous work focusing on functional connectivity within circumscribed networks suggests a divergence of network integrity and compensatory capacity between epilepsies as a function of the laterality of seizure onset. We evaluated the ability of complex network theory to reveal changes in focal epilepsy in global and nodal parameters using graph theoretical analysis of functional connectivity data obtained with resting-state fMRI. Graphs of functional connectivity networks were derived from 19 right and 13 left focal epilepsy patients and 15 controls. Topological metrics (degree, local efficiency, global efficiency and modularity) were computed for a whole-brain, atlas-defined network. We also calculated a hub disruption index for each graph metric, measuring the capacity of the brain network to demonstrate increased connectivity in some nodes for decreased connectivity in others. Our data demonstrate that the patient group as a whole is characterised by network-wide pattern of reorganization, even while global parameters fail to distinguish between groups. Furthermore, multiple metrics indicate that epilepsies with differently lateralized epileptic networks are asymmetric in their burden on functional brain networks; with left epilepsy patients being characterised by reduced efficiency and modularity, while in right epilepsy patients we provide the first evidence that functional brain networks are characterised by enhanced connectivity and efficiency at some nodes whereas reduced in others., (Copyright © 2015 Elsevier Inc. All rights reserved.)