Gradient induced artifacts in simultaneous EEG-fMRI: Effect of synchronization on spiral and EPI k-space trajectories

Enhanced electroencephalography effective connectivity in frontal low-gamma band correlates of emotional regulation after mindfulness training

Practicing mindfulness, focusing attention on the internal and external experiences occurring in the present moment with open and nonjudgement stance, can lead to the development of emotional regulation skills. Yet, the effective connectivity of brain regions during mindfulness has been largely unexplored. Studies have shown that mindfulness practice promotes functional connectivity in practitioners, potentially due to improved emotional regulation abilities and increased connectivity in the lateral prefrontal areas. To examine the changes in effective connectivity due to mindfulness training, we analyzed electroencephalogram (EEG) signals taken before and after mindfulness training, focusing on training-related effective connectivity changes in the frontal area. The mindfulness training group participated in an 8-week mindfulness-based stress reduction (MBSR) program. The control group did not take part. Regardless of the specific mindfulness practice used, low-gamma band effective connectivity increased globally after the mindfulness training. High-beta band effective connectivity increased globally only during Breathing. Moreover, relatively higher outgoing effective connectivity strength was seen during Resting and Breathing and Body-scan. By analyzing the changes in outgoing and incoming connectivity edges, both F7 and F8 exhibited strong parietal connectivity during Resting and Breathing. Multiple regression analysis revealed that the changes in effective connectivity of the right lateral prefrontal area predicted mindfulness and emotional regulation abilities. These results partially support the theory that the lateral prefrontal areas have top-down modulatory control, as these areas have high outflow effective connectivity, implying that mindfulness training cultivates better emotional regulation.

Mindfulness Training Associated With Resting-State Electroencephalograms Dynamics in Novice Practitioners via Mindful Breathing and Body-Scan

Objectives: Mindfulness-based stress reduction has been proven to improve mental health and quality of life. This study examined how mindfulness training and various types of mindfulness practices altered brain activity. Methods: Specifically, the spectral powers of scalp electroencephalography of the mindfulness-based stress reduction (MBSR) group (n=17) who underwent an 8-week MBSR training-including mindful breathing and body-scan-were evaluated and compared with those of the waitlist controls (n=14). Results: Empirical results indicated that the post-intervention effect of MBSR significantly elevated the resting-state beta powers and reduced resting-state delta powers in both practices; such changes were not observed in the waitlist control. Compared with mindful breathing, body-scanning resulted in an overall decline in electroencephalograms (EEG) spectral powers at both delta and low-gamma bands among trained participants. Conclusion: Together with our preliminary data of expert mediators, the aforementioned spectral changes were salient after intervention, but mitigated along with expertise. Additionally, after receiving training, the MBSR group's mindfulness and emotion regulation levels improved significantly, which were correlated with the EEG spectral changes in the theta, alpha, and low-beta bands. The results supported that MBSR might function as a unique internal processing tool that involves increased vigilant capability and induces alterations similar to other cognitive training.

Silent zero TE MR neuroimaging: Current state-of-the-art and future directions

Magnetic Resonance Imaging (MRI) scanners produce loud acoustic noise originating from vibrational Lorentz forces induced by rapidly changing currents in the magnetic field gradient coils. Using zero echo time (ZTE) MRI pulse sequences, gradient switching can be reduced to a minimum, which enables near silent operation.Besides silent MRI, ZTE offers further interesting characteristics, including a nominal echo time of TE = 0 (thus capturing short-lived signals from MR tissues which are otherwise MR-invisible), 3D radial sampling (providing motion robustness), and ultra-short repetition times (providing fast and efficient scanning).In this work we describe the main concepts behind ZTE imaging with a focus on conceptual understanding of the imaging sequences, relevant acquisition parameters, commonly observed image artefacts, and image contrasts. We will further describe a range of methods for anatomical and functional neuroimaging, together with recommendations for successful implementation.

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

Simultaneous EEG‐fMRI allows multiparametric 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), Moiré 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 multichannel, 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.

Gradient Artefact Correction and Evaluation of the EEG Recorded Simultaneously with fMRI Data Using Optimised Moving-Average

Over the past years, coregistered EEG-fMRI has emerged as a powerful tool for neurocognitive research and correlated studies, mainly because of the possibility of integrating the high temporal resolution of the EEG with the high spatial resolution of fMRI. However, additional work remains to be done in order to improve the quality of the EEG signal recorded simultaneously with fMRI data, in particular regarding the occurrence of the gradient artefact. We devised and presented in this paper a novel approach for gradient artefact correction based upon optimised moving-average filtering (OMA). OMA makes use of the iterative application of a moving-average filter, which allows estimation and cancellation of the gradient artefact by integration. Additionally, OMA is capable of performing the attenuation of the periodic artefact activity without accurate information about MRI triggers. By using our proposed approach, it is possible to achieve a better balance than the slice-average subtraction as performed by the established AAS method, regarding EEG signal preservation together with effective suppression of the gradient artefact. Since the stochastic nature of the EEG signal complicates the assessment of EEG preservation after application of the gradient artefact correction, we also propose a simple and effective method to account for it.

CXCR2 Inhibition Combined with Sorafenib Improved Antitumor and Antiangiogenic Response in Preclinical Models of Ovarian Cancer

Antiangiogenic therapy is important for the treatment of gynecological cancer. However, the therapeutic benefit derived from these treatments is transient, predominantly due to the selective activation of compensatory proangiogenic pathways that lead to rapid development of resistance. We aimed to identify and target potential alternative signaling to anti-vascular endothelial growth factor (VEGF) therapy, with a view toward developing a combination of antiangiogenic agents to provide extended therapeutic benefits. We developed a preclinical in vivo phenotypic resistance model of ovarian cancer resistant to antiangiogenic therapy. We measured dynamic changes in secreted chemokines and angiogenic signaling in tumors and plasma in response to anti-VEGF treatment, as tumors advanced from the initial responsive phase to progressive disease. In tumors that progressed following sorafenib treatment, gene and protein expression levels of proangiogenic CXC chemokines and their receptors were significantly elevated, compared with responsive tumors. The chemokine (C-X-C motif) ligand 8 (CXCL8), also known as interleukin-8 (IL-8) increase was time-dependent and coincided with the dynamics of tumor progression. We used SB225002, a pharmacological inhibitor of chemokine (C-X-C motif) receptor 2 (CXCR2), to disrupt the CXC chemokine-mediated functions of ovarian cancer cells in in vitro assays of cell growth inhibition, spheroid formation, and cell migration. The combination of CXCR2 inhibitor with sorafenib led to a synergistic inhibition of cell growth in vitro, and further stabilized tumor progression following sorafenib in vivo. Our results suggest that CXCR2-mediated chemokines may represent an important compensatory pathway that promotes resistance to antiangiogenic therapy in ovarian cancer. Thus, simultaneous blockage of this proangiogenic cytokine pathway using CXCR2 inhibitors and the VEGF receptor (VEGFR) pathway could improve the outcomes of antiangiogenic therapy.

Altered brain rhythms and functional network disruptions involved in patients with generalized fixation-off epilepsy

Generalized Fixation-off Sensitivity (CGE-FoS) patients present abnormal EEG patterns when losing fixation. In the present work, we studied two CGE-FoS epileptic patients with simultaneous EEG-fMRI. We aim to identify brain areas that are specifically related to the pathology by identifying the brain networks that are related to the EEG brain altered rhythms. Three main analyses were performed: EEG standalone, where the voltage fluctuations in delta, alpha, and beta EEG bands were obtained; fMRI standalone, where resting-state fMRI ICA analyses for opened and closed eyes conditions were computed per subject; and, EEG-informed fMRI, where EEG delta, alpha and beta oscillations were used to analyze fMRI. Patient 1 showed EEG abnormalities for lower beta band EEG brain rhythm. Fluctuations of this rhythm were correlated with a brain network mainly composed by temporo-frontal areas only found in the closed eyes condition. Patient 2 presented alterations in all the EEG brain rhythms (delta, alpha, beta) under study when closing eyes. Several biologically relevant brain networks highly correlated (r > 0.7) to each other in the closed eyes condition were found. EEG-informed fMRI results in patient 2 showed hypersynchronized patterns in the fMRI correlation spatial maps. The obtained findings allow a differential diagnosis for each patient and different profiles with respect to healthy volunteers. The results suggest a different disruption in the functional brain networks of these patients that depends on their altered brain rhythms. This knowledge could be used to treat these patients by novel brain stimulation approaches targeting specific altered brain networks in each patient.