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Objective: Auditory-driven gamma synchrony (GS) is linked to the function of a specific cortical circuit based on a parvalbumin+ and pyramidal neuron loop. This circuit is impaired in neuropsychiatric conditions (i.e. schizophrenia, Alzheimer's disease, stroke etc.) and its relevance in clinical practice is increasingly being recognized. Auditory stimulation at a typical gamma frequency of 40 Hz can be applied as a 'stress test' of excitation/inhibition (E/I) of the entire cerebral cortex, to drive GS and record it with magnetoencephalography (MEG) or high-density electroencephalography (EEG). However, these two techniques are costly and not widely available. Therefore, we assessed whether a single EEG electrode is sufficient to provide an accurate estimate of the auditory-driven GS level of the entire cortical surface while expecting the highest correspondence in the auditory and somatosensory cortices., Methods: We measured simultaneous EEG-MEG in 29 healthy subjects, utilizing 3 EEG electrodes (C4, F4, O2) and a full MEG setup. Recordings were performed during binaural exposure to auditory gamma stimulation and during silence. We compared GS measurement of each of the three EEG electrodes separately against full MEG mapping. Time-resolved phase locking value (PLVt) was computed between EEG signals and cortex reconstructed MEG signals., Results: During auditory stimulation, but not at rest, EEG captures a significant amount of GS, especially from both auditory cortices and motor-premotor regions. This was especially true for frontal (C4) and central electrodes (F4)., Discussion and Conclusions: While hd-EEG and MEG are necessary for accurate spatial mapping of GS at rest and during auditory stimulation, a single EEG channel is sufficient to detect the global level of GS. These results have great translational potential for mapping GS in standard clinical settings., Competing Interests: Declaration of competing interest The authors have no conflict of interest to disclose., (Copyright © 2024. Published by Elsevier Inc.)

Magnetoencephalography and electroencephalography (M/EEG) seed-based connectivity analysis requires the extraction of measures from regions of interest (ROI). M/EEG ROI-derived source activity can be treated in different ways. It is possible, for instance, to average each ROI's time series prior to calculating connectivity measures. Alternatively, one can compute connectivity maps for each element of the ROI prior to dimensionality reduction to obtain a single map. The impact of these different strategies on connectivity results is still unclear. Here, we address this question within a large MEG resting state cohort (N=113) and within simulated data. We consider 68 ROIs (Desikan-Kiliany atlas), two measures of connectivity (phase locking value-PLV, and its imaginary counterpart- ciPLV), and three frequency bands (theta 4-8 Hz, alpha 9-12 Hz, beta 15-30 Hz). We compare four extraction methods: (i) mean, or (ii) PCA of the activity within the seed or ROI before computing connectivity, map of the (iii) average, or (iv) maximum connectivity after computing connectivity for each element of the seed. Hierarchical clustering is then applied to compare connectivity outputs across multiple strategies, followed by direct contrasts across extraction methods. Finally, the results are validated by using a set of realistic simulations. We show that ROI-based connectivity maps vary remarkably across strategies in terms of connectivity magnitude and spatial distribution. Dimensionality reduction procedures conducted after computing connectivity are more similar to each-other, while PCA before approach is the most dissimilar to other approaches. Although differences across methods are consistent across frequency bands, they are influenced by the connectivity metric and ROI size. Greater differences were observed for ciPLV than PLV, and in larger ROIs. Realistic simulations confirmed that after aggregation procedures are generally more accurate but have lower specificity (higher rate of false positive connections). Though computationally demanding, after dimensionality reduction strategies should be preferred when higher sensitivity is desired. Given the remarkable differences across aggregation procedures, caution is warranted in comparing results across studies applying different methods., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this manuscript., (Copyright © 2023. Published by Elsevier Inc.)

Objective: Gamma synchrony is a fundamental functional property of the cerebral cortex, impaired in multiple neuropsychiatric conditions (i.e. schizophrenia, Alzheimer's disease, stroke etc.). Auditory stimulation in the gamma range allows to drive gamma synchrony of the entire cortical mantle and to estimate the efficiency of the mechanisms sustaining it. As gamma synchrony depends strongly on the interplay between parvalbumin-positive interneurons and pyramidal neurons, we hypothesize an association between cortical thickness and gamma synchrony. To test this hypothesis, we employed a combined magnetoencephalography (MEG) - Magnetic Resonance Imaging (MRI) study., Methods: Cortical thickness was estimated from anatomical MRI scans. MEG measurements related to exposure of 40 Hz amplitude modulated tones were projected onto the cortical surface. Two measures of cortical synchrony were considered: (a) inter-trial phase consistency at 40 Hz, providing a vertex-wise estimation of gamma synchronization, and (b) phase-locking values between primary auditory cortices and whole cortical mantle, providing a measure of long-range cortical synchrony. A correlation between cortical thickness and synchronization measures was then calculated for 72 MRI-MEG scans., Results: Both inter-trial phase consistency and phase locking values showed a significant positive correlation with cortical thickness. For inter-trial phase consistency, clusters of strong associations were found in the temporal and frontal lobes, especially in the bilateral auditory and pre-motor cortices. Higher phase-locking values corresponded to higher cortical thickness in the frontal, temporal, occipital and parietal lobes., Discussion and Conclusions: In healthy subjects, a thicker cortex corresponds to higher gamma synchrony and connectivity in the primary auditory cortex and beyond, likely reflecting underlying cell density involved in gamma circuitries. This result hints towards an involvement of gamma synchrony together with underlying brain structure in brain areas for higher order cognitive functions. This study contributes to the understanding of inherent cortical functional and structural brain properties, which might in turn constitute the basis for the definition of useful biomarkers in patients showing aberrant gamma synchronization., Competing Interests: Declaration of Competing Interest The authors have no conflict of interest to disclose., (Copyright © 2022. Published by Elsevier Inc.)

Optimal contrast to noise ratio of the BOLD signal in neonatal and foetal fMRI has been hard to achieve because of the much longer T2(⁎) values in developing brain tissue in comparison to those in the mature adult brain. The conventional approach of optimizing fMRI sequences would suggest matching the echo time (TE) and the T2(⁎) of the neonatal and foetal brain. However, the use of a long echo time would typically increase the minimum repetition time (TR) resulting in inefficient sampling. Here we apply the concept of echo shifting to task based neonatal fMRI in order to achieve an improved contrast to noise ratio and efficient data sampling at the same time. Echo shifted EPI (es-EPI) is a modification of a standard 2D-EPI sequence which enables echo times longer than the time between consecutive excitations (TE>TS=TRNS, where NS is the number of acquired slices and TS the inter-slice repetition time). The proposed method was tested on neonatal subjects using a passive sensori-motor task paradigm. Dual echo EPI datasets with an identical readout structure to es-EPI were also acquired and used as control data to assess BOLD activation. From the results of the latter analysis, an average increase of 78±41% in contrast to noise ratio was observable when comparing late to short echoes. Furthermore, es-EPI allowed the acquisition of data with an identical contrast to the late echo, but more efficiently since a higher number of slices could be acquired in the same amount of time., (Copyright © 2015 Elsevier Inc. All rights reserved.)

There is growing interest in exploring fetal functional brain development, particularly with Resting State fMRI. However, during a typical fMRI acquisition, the womb moves due to maternal respiration and the fetus may perform large-scale and unpredictable movements. Conventional fMRI processing pipelines, which assume that brain movements are infrequent or at least small, are not suitable. Previous published studies have tackled this problem by adopting conventional methods and discarding as much as 40% or more of the acquired data. In this work, we developed and tested a processing framework for fetal Resting State fMRI, capable of correcting gross motion. The method comprises bias field and spin history corrections in the scanner frame of reference, combined with slice to volume registration and scattered data interpolation to place all data into a consistent anatomical space. The aim is to recover an ordered set of samples suitable for further analysis using standard tools such as Group Independent Component Analysis (Group ICA). We have tested the approach using simulations and in vivo data acquired at 1.5 T. After full motion correction, Group ICA performed on a population of 8 fetuses extracted 20 networks, 6 of which were identified as matching those previously observed in preterm babies., (Copyright © 2014 Elsevier Inc. All rights reserved.)