1,721,047 research outputs found
A Comparative Study of the Robustness of Frequency-Domain Connectivity Measures to Finite Data Length
No full textIn this work we use numerical simulation to investigate how the temporal length of the data affects the reliability of the estimates of brain connectivity from EEG time-series. We assume that the neural sources follow a stable MultiVariate AutoRegressive model, and consider three connectivity metrics: imaginary part of coherency (IC), generalized partial directed coherence (gPDC) and frequency-domain granger causality (fGC). In order to assess the statistical significance of the estimated values, we use the surrogate data test by generating phase-randomized and autoregressive surrogate data. We first consider the ideal case where we know the source time courses exactly. Here we show how, expectedly, even exact knowledge of the source time courses is not sufficient to provide reliable estimates of the connectivity when the number of samples gets small; however, while gPDC and fGC tend to provide a larger number of false positives, the IC becomes less sensitive to the presence of connectivity. Then we proceed with more realistic simulations, where the source time courses are estimated using eLORETA, and the EEG signal is affected by biological noise of increasing intensity. Using the ideal case as a reference, we show that the impact of biological noise on IC estimates is qualitatively different from the impact on gPDC and fGC
Bispectral pairwise interacting source analysis for identifying systems of cross-frequency interacting brain sources from electroencephalographic or magnetoencephalographic signals
Full text linkBrain cognitive functions arise through the coordinated activity of several brain regions, which actually form complex dynamical systems operating at multiple frequencies. These systems often consist of interacting subsystems, whose characterization is of importance for a complete understanding of the brain interaction processes. To address this issue, we present a technique, namely the bispectral pairwise interacting source analysis (biPISA), for analyzing systems of cross-frequency interacting brain sources when multichannel electroencephalographic (EEG) or magnetoencephalographic (MEG) data are available. Specifically, the biPISA makes it possible to identify one or many subsystems of cross-frequency interacting sources by decomposing the antisymmetric components of the cross-bispectra between EEG or MEG signals, based on the assumption that interactions are pairwise. Thanks to the properties of the antisymmetric components of the cross-bispectra, biPISA is also robust to spurious interactions arising from mixing artifacts, i.e., volume conduction or field spread, which always affect EEG or MEG functional connectivity estimates. This method is an extension of the pairwise interacting source analysis (PISA), which was originally introduced for investigating interactions at the same frequency, to the study of cross-frequency interactions. The effectiveness of this approach is demonstrated in simulations for up to three interacting source pairs and for real MEG recordings of spontaneous brain activity. Simulations show that the performances of biPISA in estimating the phase difference between the interacting sources are affected by the increasing level of noise rather than by the number of the interacting subsystems. The analysis of real MEG data reveals an interaction between two pairs of sources of central mu and beta rhythms, localizing in the proximity of the left and right central sulci
Impact of the reference choice on scalp EEG connectivity estimation
Full text linkObjective. Several scalp EEG functional connectivity studies, mostly clinical, seem to overlook the reference electrode impact. The subsequent interpretation of brain connectivity is thus often biased by the choice of a non-neutral reference. This study aims at systematically investigating these effects. Approach. As EEG reference, we examined the vertex electrode (Cz), the digitally linked mastoids (DLM), the average reference (AVE), and the reference electrode standardization technique (REST). As a connectivity metric, we used the imaginary part of the coherency. We tested simulated and real data (eyes-open resting state) by evaluating the influence of electrode density, the effect of head model accuracy in the REST transformation, and the impact on the characterization of the topology of functional networks from graph analysis. Main results. Simulations demonstrated that REST significantly reduced the distortion of connectivity patterns when compared to AVE, Cz, and DLM references. Moreover, the availability of high-density EEG systems and an accurate knowledge of the head model are crucial elements to improve REST performance, with the individual realistic head model being preferable to the standard realistic head model. For real data, a systematic change of the spatial pattern of functional connectivity depending on the chosen reference was also observed. The distortion of connectivity patterns was larger for the Cz reference, and progressively decreased when using the DLM, the AVE, and the REST. Strikingly, we also showed that network attributes derived from graph analysis, i.e. node degree and local efficiency, are significantly influenced by the EEG reference choice. Significance. Overall, this study highlights that significant differences arise in scalp EEG functional connectivity and graph network properties, in dependence on the chosen reference. We hope that our study will convey the message that caution should be used when interpreting and comparing results obtained from different laboratories using different reference schemes. © 2016 IOP Publishing Ltd
Functional localization of the sensory hand area with respect to the motor central gyrus knob
No full textThe aim of this work was to investigate the topography of the primary sensory hand cortex with magnetoencephalography in order to define the functional anatomy of this area in healthy humans. Previous studies denoted an inverted Ohm or an horizontal epsilon shaped knob on the pre-central gyrus as a landmark for the motor hand area; therefore a systematic difference between the orientation of the source for thumb with respect to little finger should be observed. We found this systematic difference, but the direction of the sources activated during thumb and little finger stimulation did not converge, as would be expected if only the Ohm convexity is activated: in fact our results suggest that thumb sensory area also extends to the area lateral to this convexity
Impact of SQUIDs on functional imaging in neuroscience
No full textThis paper provides an overview on the basic principles and applications of magnetoencephalography (MEG), a technique that requires the use of many SQUIDs and thus represents one of the most important applications of superconducting electronics. Since the development of the first SQUID magnetometers, it was clear that these devices could be used to measure the ultra-low magnetic signals associated with the bioelectric activity of the neurons of the human brain. Forty years on from the first measurement of magnetic alpha rhythm by David Cohen, MEG has become a fundamental tool for the investigation of brain functions. The simple localization of cerebral sources activated by sensory stimulation performed in the early years has been successively expanded to the identification of the sequence of neuronal pool activations, thus decrypting information of the hierarchy underlying cerebral processing. This goal has been achieved thanks to the development of complex instrumentation, namely whole head MEG systems, allowing simultaneous measurement of magnetic fields all over the scalp with an exquisite time resolution. The latest trends in MEG, such as the study of brain networks, i. e. how the brain organizes itself in a coherent and stable way, are discussed. These sound applications together with the latest technological developments aimed at implementing systems able to record MEG signals and magnetic resonance imaging (MRI) of the head with the same set-up pave the way to high performance systems for brain functional investigation in the healthy and the sick population
Non-linear Analysis of Scalp EEG by Using Bispectra: The Effect of the Reference Choice
Full text linkMagnetoencephalography in the study of brain dynamics
Full text linkTo progress toward understanding of the mechanisms
underlying the functional organization of the human brain, either a bottom-up or a top-down approach may be adopted. The former starts from the study of the detailed
functioning of a small number of neuronal assemblies, while the latter tries to decode brain functioning by considering the brain as a whole. This review discusses the top-down approach and the use of magnetoencephalography (MEG) to describe global brain properties. The main idea behind this approach is that the concurrence of several areas is required for the brain to instantiate a specific behavior/functioning. A central issue is therefore the
study of brain functional connectivity and the concept of
brain networks as ensembles of distant brain areas that
preferentially exchange information. Importantly, the human brain is a dynamic device, and MEG is ideally suited to investigate phenomena on behaviorally relevant timescales, also offering the possibility of capturing
behaviorally-related brain connectivity dynamics
Conditioning transcutaneous electrical nerve stimulation induces delayed gating effects on cortical response: A magnetoencephalographic study
No full textThe present study was undertaken to investigate after-effects of 7 Hz non-painful prolonged stimulation of the median nerve on somatosensory- evoked fields (SEFs). The working hypothesis that conditioning peripheral stimulations might produce delayed interfering (“gating”) effects on the response of somatosensory cortex to test stimuli was evaluated. In the control condition, electrical thumb stimulation induced SEFs in ten subjects. In the experimental protocol, a conditioning median nerve stimulation at wrist preceded 6 electrical thumb stimulations. Equivalent current dipoles fitting SEFs modeled responses of contralateral primary area (SI) and bilateral secondary somatosensory areas (SII) following control and experimental conditions. Compared to the control condition, conditioning stimulation induced no amplitude modulation of SI response at the initial stimulus-related peak (20 ms). In contrast, later response from SI (35 ms) and response from SII were significantly weakened in amplitude. Gradual but fast recovery towards control amplitude levels was observed for the response from SI-P35, while a slightly slower cycle was featured from SII. These findings point to a delayed “gating” effect on the synchronization of somatosensory cortex after peripheral conditioning stimulations. This effect was found to be more lasting in SII area, as a possible reflection of its integrative role in sensory processin
A neuromagnetic normative data set for hemispheric sensory hand cortical representations and their interhemispheric differences
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