Sequential Activation of Human Oculomotor Centers During Planning of Visually-Guided Eye Movements: A Combined fMRI-MEG Study

We used magneto-encephalography (MEG) to measure visually evoked activity in healthy volunteers performing saccadic eye movements to visual targets. The neuromagnetic activity was analyzed from regions of cortical activation identified in separate functional magnetic resonance imaging (fMRI) studies. The latency of visual responses significantly increased from the Middle Temporal region (MT+) to the Intraparietal Sulcus (IPS) to the Frontal Eye Field (FEF), and their amplitude was greater in the hemisphere contralateral to the visual target. Trial-to-trial variability of oculomotor reaction times correlated with visual response latency across cortical areas. These results support a feedforward recruitment of oculomotor cortical centers by visual information, and a model in which behavioral variability depends on variability at different neural stages of processing

Resonant gravitational wave antennas for stochastic background measurements

The sensitivity of a resonant gravitational wave (GW) antenna is calculated in terms of spectral density and frequency bandwidth. For a quantum-limited detector the bandwidth might reach values greater than 100 Hz, with a sensitivity to bursts of . The spectral amplitude sensitivity for the Nautilus detector has been measured to be and its target value is . Using two near-Nautilus detectors the GW stochastic background can be measured with a sensitivity, with respect to the critical density, of a few for an integration time of one year, as shown by simulations

Concurrent brain responses to separate auditory and visual targets.

In the attentional blink, a target event (T1) strongly interferes with perception of a second target (T2) presented within a few hundred milliseconds. Concurrently, the brain's electromagnetic response to the second target is suppressed, especially a late negative-positive EEG complex including the traditional P3 wave. An influential theory proposes that conscious perception requires access to a distributed, frontoparietal global workspace, explaining the attentional blink by strong mutual inhibition between concurrent workspace representations. Often, however, the attentional blink is reduced or eliminated for targets in different sensory modalities, suggesting a limit to such global inhibition. Using functional magnetic resonance imaging, we confirm that visual and auditory targets produce similar, distributed patterns of frontoparietal activity. In an attentional blink EEG/MEG design, however, an auditory T1 and visual T2 are identified without mutual interference, with largely preserved electromagnetic responses to T2. The results suggest parallel brain responses to target events in different sensory modalities

Disclosing large-scale directed functional connections in MEG with the multivariate phase slope index.

Abstract The phase slope index (PSI) is a method to disclose the direction of frequency-specific neural interactions from magnetoencephalographic (MEG) time series. A fundamental property of PSI is that of vanishing for linear mixing of independent neural sources. This property allows PSI to cope with the artificial instantaneous connectivity among MEG sensors or brain sources induced by the field spread. Nevertheless, PSI is limited by being a bivariate estimator of directionality as opposite to the multidimensional nature of brain activity as revealed by MEG. The purpose of this work is to provide a multivariate generalization of PSI. We termed this measure as the multivariate phase slope index (MPSI). In order to test the ability of MPSI in estimating the directionality, and to compare the MPSI results to those obtained by bivariate PSI approaches based on maximizing imaginary part of coherency and on canonical correlation analysis, we used extensive simulations. We proved that MPSI achieves the highest performance and that in a large number of simulated cases, the bivariate methods, as opposed to MPSI, do not detect a statistically significant directionality. Finally, we applied MPSI to assess seed-based directed functional connectivity in the alpha band from resting state MEG data of 61 subjects from the Human Connectome Project. The obtained results highlight a directed functional coupling in the alpha band between the primary visual cortex and several key regions of well-known resting state networks, e.g. dorsal attention network and fronto-parietal network

Mindfulness meditation styles differently modulate source-level MEG microstate dynamics and complexity

BackgroundThe investigation of mindfulness meditation practice, classically divided into focused attention meditation (FAM), and open monitoring meditation (OMM) styles, has seen a long tradition of theoretical, affective, neurophysiological and clinical studies. In particular, the high temporal resolution of magnetoencephalography (MEG) or electroencephalography (EEG) has been exploited to fill the gap between the personal experience of meditation practice and its neural correlates. Mounting evidence, in fact, shows that human brain activity is highly dynamic, transiting between different brain states (microstates). In this study, we aimed at exploring MEG microstates at source-level during FAM, OMM and in the resting state, as well as the complexity and criticality of dynamic transitions between microstates.MethodsTen right-handed Theravada Buddhist monks with a meditative expertise of minimum 2,265 h participated in the experiment. MEG data were acquired during a randomized block design task (6 min FAM, 6 min OMM, with each meditative block preceded and followed by 3 min resting state). Source reconstruction was performed using eLORETA on individual cortical space, and then parcellated according to the Human Connect Project atlas. Microstate analysis was then applied to parcel level signals in order to derive microstate topographies and indices. In addition, from microstate sequences, the Hurst exponent and the Lempel-Ziv complexity (LZC) were computed.ResultsOur results show that the coverage and occurrence of specific microstates are modulated either by being in a meditative state or by performing a specific meditation style. Hurst exponent values in both meditation conditions are reduced with respect to the value observed during rest, LZC shows significant differences between OMM, FAM, and REST, with a progressive increase from REST to FAM to OMM.DiscussionImportantly, we report changes in brain criticality indices during meditation and between meditation styles, in line with a state-like effect of meditation on cognitive performance. In line with previous reports, we suggest that the change in cognitive state experienced in meditation is paralleled by a shift with respect to critical points in brain dynamics

Being an agent or an observer: Different spectral dynamics revealed by MEG

Several neuroimaging studies reported that a common set of regions is recruited during action observation and execution and it has been proposed that the modulation of the μ rhythm, in terms of oscillations in the alpha and beta bands might represent the electrophysiological correlate of the underlying brain mechanisms. However, the specific functional role of these bands within the μ rhythm is still unclear. Here, we used magnetoencephalography (MEG) to analyze the spectral and temporal properties of the alpha and beta bands in healthy subjects during an action observation and execution task. We associated the modulation of the alpha and beta power to a broad action observation network comprising several parieto-frontal areas previously detected in fMRI studies. Of note, we observed a dissociation between alpha and beta bands with a slow-down of beta oscillations compared to alpha during action observation. We hypothesize that this segregation is linked to a different sequence of information processing and we interpret these modulations in terms of internal models (forward and inverse). In fact, these processes showed opposite temporal sequences of occurrence: anterior-posterior during action (both in alpha and beta bands) and roughly posterior-anterior during observation (in the alpha band). The observed differentiation between alpha and beta suggests that these two bands might pursue different functions in the action observation and execution processes

Analysing linear multivariate pattern transformations in neuroimaging data.

Most connectivity metrics in neuroimaging research reduce multivariate activity patterns in regions-of-interests (ROIs) to one dimension, which leads to a loss of information. Importantly, it prevents us from investigating the transformations between patterns in different ROIs. Here, we applied linear estimation theory in order to robustly estimate the linear transformations between multivariate fMRI patterns with a cross-validated ridge regression approach. We used three functional connectivity metrics that describe different features of these voxel-by-voxel mappings: goodness-of-fit, sparsity and pattern deformation. The goodness-of-fit describes the degree to which the patterns in an input region can be described as a linear transformation of patterns in an output region. The sparsity metric, which relies on a Monte Carlo procedure, was introduced in order to test whether the transformation mostly consists of one-to-one mappings between voxels in different regions. Furthermore, we defined a metric for pattern deformation, i.e. the degree to which the transformation rotates or rescales the input patterns. As a proof of concept, we applied these metrics to an event-related fMRI data set consisting of four subjects that has been used in previous studies. We focused on the transformations from early visual cortex (EVC) to inferior temporal cortex (ITC), fusiform face area (FFA) and parahippocampal place area (PPA). Our results suggest that the estimated linear mappings explain a significant amount of response variance in the three output ROIs. The transformation from EVC to ITC shows the highest goodness-of-fit, and those from EVC to FFA and PPA show the expected preference for faces and places as well as animate and inanimate objects, respectively. The pattern transformations are sparse, but sparsity is lower than would have been expected for one-to-one mappings, thus suggesting the presence of one-to-few voxel mappings. The mappings are also characterised by different levels of pattern deformations, thus indicating that the transformations differentially amplify or dampen certain dimensions of the input patterns. While our results are only based on a small number of subjects, they show that our pattern transformation metrics can describe novel aspects of multivariate functional connectivity in neuroimaging data.This work was funded by a British Academy Postdoctoral Fellowship (PS140117) to MM, by the Medical Research Council UK (SUAG/058 G101400) to OH, and conducted under the framework of the Departments of Excellence 2018–2022 initiative of the Italian Ministry of Education, University and Research for the Department of Neuroscience, Imaging and Clinical Sciences (DNISC) of the University of Chieti-Pescara

Human alpha rhythms during visual delayed choice reaction time tasks: A magnetoencephalography study, Human Brain Mapping 2005;24(3):184–192

The original article to which this Erratum refers was published in the March 2005 issue of Human Brain MappingHuman Brain Mapping (2005) 24(3) 184–192