1,721,104 research outputs found
Choice of multivariate autoregressive model order affecting real network functional connectivity estimate
No full textOBJECTIVE: A realistic simulation exploiting real cortical sources identified from non-invasive extra-cranial recordings in healthy subjects has been considered in order to select the most robust procedure for choosing the correct order of multivariate autoregressive (MVAR) models. Different signal-to-noise ratios filter settings and sampling rates were also tested on the estimate of functional connectivity among the network nodes, in simulated and real cases. METHODS: Starting from magnetoencephalographic recordings, cortical sources in primary sensorimotor areas of the hand were obtained by functional source separation (FSS). Different criteria for the choice of the model order were compared in the simulated network constructed through one of the FSS-extracted sources and its noise-added delayed copies. In two real cases, a validation of the model order (not known a priori) choice was obtained by comparing the time-frequency properties as depicted by classical non-parametric and MVAR methods at rest, during isometric contraction (stationary states) and while dynamically responding to a sensory stimulation (transient state). For completeness, the whole set of MVAR functional connectivity measures was taken into account, to assess the most suitable for our network description. RESULTS: That the use of an incorrect model order distorts network functional connectivity estimate was documented both in the realistic simulation and in the two real cases. The Minimal Description Length and Schwartz Bayesian Criterion were selected as the most robust for MVAR model order choice. Partial directed coherence (PDC) was the most suitable method for time-frequency connectivity estimate in the simulated as well as in the real cases, both in stationary and transient states. Moreover, the results of MVAR-based connectivity estimate depend on filter setting in the real case. CONCLUSIONS: The most robust procedure for choosing the correct MVAR model order was provided. The adjunctive comparison of MVAR to classical methods is recommended to validate the choice in the real case. SIGNIFICANCE: Correct MVAR model order choice and band filtering play an important role for the correct network connectivity estimate
EEG microstates associated with intra- and inter-subject alpha variability
Full text linkVariation of the magnitude of posterior alpha rhythm (8–12 Hz) has functional and behavioural effects in sensory processing and cognitive performances. Electrical brain activity, as revealed by electroencephalography (EEG), can be represented by a sequence of microstates of about 40–120 ms duration, in which distributed neural pools are synchronously active and generate stable spatial potential topographies on the scalp. Microstate dynamics may reflect transitions between global states characterized by selective inhibition of specific intra-cortical regions, mediated by alpha activity. We investigated the intra-subject and inter-subject relationship between microstate features and alpha band. High-density EEG signals were acquired in 29 healthy subjects during ten minutes of eyes closed rest. Individual EEG signal epochs were classified into four groups depending on the amount of occipital alpha power, and microstate metrics (duration, coverage and frequency of occurrence) were calculated and compared across groups. Correlations between alpha power and microstate metrics between individuals were also performed. To assess if microstate parameter variations are specific for the alpha band, the same analysis was also performed for theta and beta bands, as well as for global field power. We observed an increase in the metrics of microstate, previously associated to the visual system, with the level of intra-subject amplitude alpha oscillations, together with lower coverage of microstate associated with executive attention network and a higher frequency of microstate associated with task negative network. Other modulation effects of broad-band EEG power level on microstate metrics were observed. These effects are not specific for the alpha band, since they can equally be attributed to fluctuations in other frequency bands. We can interpret our results as a regulation mechanism mediated by posterior alpha level, dynamically interacting with other frequency bands, responsible for the switching between active areas
rTMS affects EEG microstates dynamic during evoked activity
No full textElectrophysiological (EEG) correlates both at time (i.e., event-related potentials, ERP) and frequency (i.e., event-related desynchronization, ERD) domains have been shown to be modulated by external magnetic interference. Parallel studies reported a similar interference also for the EEG microstate at rest and in the period that anticipates a task. Here we investigated whether such interference was prolonged during the evoked activity in the framework of the semantic decision task. To this aim, rTMS was delivered over a core region of both the Default mode network and the language network (i.e., left angular gyrus, AG), previously associated to the current task, and as active control we stimulated the left IPS. When subjects received a non-active stimulation (i.e., Sham), in the period that follows the target onset (i.e., 2 sec after the rTMS) we found an interesting alternation of two dominant microstates (MS1, MS3), previously associated to the phonological network and the Cingulo-Opercular Network (CON), respectively. This dynamic was not altered when TMS was delivered over the left IPS. On the contrary, rTMS over left AG selectively suppressed the phonological-related microstate. These findings provide the first causal evidence of region specificity of the EEG microstates topography during the evoked activity corroborating the idea of a crucial role of AG in the semantic memory. Moreover, the present results might provide insight for understanding the neurophysiological correlates of language disorders e.g., aphasia as well as for planning non-invasive brain stimulation protocols for the rehabilitation
Acute Phase Neuronal Activity for the Prognosis of Stroke Recovery
Full text linkStrokes causing similar lesions and clinical states can be followed by diverse regains of neurological functions, indicating that the clinical recovery can depend on individual modulating factors. A promising line to disclose these factors, to finally open new therapeutic strategies, is to search for individual indices of recovery prognosis. Here, we pursued on strengthening the value of acute phase electrophysiological biomarkers for poststroke functional recovery in a wide group of patients. We enrolled 120 patients affected by a monohemispheric stroke within the middle cerebral artery territory (70 left and 50 right damages) and collected the NIH stroke scale (NIHSS) score in the acute phase (T0, median 4 days) and chronic follow-up (T1, median 6 months). At T0, we executed electrophysiological noninvasive assessment (19-channel electroencephalography (EEG) or 28 channels per side magnetoencephalography (MEG)) of brain activity at rest by means of band powers in the contra- and ipsilesional hemispheres (CLH, ILH) or the homologous area symmetry (HArS). Low-band (2-6 Hz) HArS entered the regression model for predicting the stabilized clinical state (p<0.001), with bilateral impairment correlated with a poor outcome. Present data strengthen the fact that low-band impairment of homologous ipsi- and contralesional hemispheric regions in the acute stroke indicate a negative prognosis of clinical recovery
An ICA approach to detect functionally different intra-regional neuronal signals in MEG data
No full textCerebral processing mainly relies on functional connectivity among involved regions. Neuro-imaging techniques able to assess these links with suitable time resolution are electro- and magneto-encephalography (EEG and MEG), even if it is difficult to localize recorded extra-cranial information, particularly within restricted areas, due to complexity of the 'inverse problem'. By means of Independent Component Analysis (ICA) a procedure 'blind' to position and biophysical properties of the generators, our aim in this work was to identify cerebral functionally different sources in a restricted area. MEG data of 5 subjects were collected performing a relax-movement motor task in 5 different days. ICA reliably extracted neural networks differently modulated during the task in the frequency range of interest. In conclusion, a procedure solely based on statistical properties of the signals, disregarding their spatial positions, was demonstrated able to discriminate functionally different neuronal pools activities in a very restricted cortical area. © Springer-Verlag Berlin Heidelberg 2005
Clinical Sensitivity of Fractal Neurodynamics.
No full textAmong the significant advances in the understanding of the organization of the neuronal networks that coordinate the body and brain, their complex nature is increasingly important, resulting from the interaction between the very large number of constituents strongly organized hierarchically and at the same time with “self-emerging.” This awareness drives us to identify the measures that best quantify the “complexity” that accompanies the continuous evolutionary dynamics of the brain. In this chapter, after an introductory section (Sect. 15.1), we examine how the Higuchi fractal dimension is able to perceive physiological processes (15.2), neurological (15.3) and psychiatric (15.4) disorders, and neuromodulation effects (15.5), giving a mention of other methods of measuring neuronal electrical activity in addition to electroencephalography, such as magnetoencephalography and functional magnetic resonance. Conscious that further progress will support a deeper understanding of the tempora..
Hilbert spectral analysis of EEG data reveals spectral dynamics associated with microstates
No full textBackground: This study addresses an ongoing debate, i.e. whether microstates have a relation to specific oscillations or frequency bands. The previous literature on this has been inconclusive. Due to stochastic calculation of microstates it is important to address this issue because instead of providing further insights, it might lead us to ambiguous interpretations. New Method: Here we propose a new method that allows to remove the time-frequency trade-off, which hampered previous works, using Empirical Mode Decomposition (EMD) and the AM-FM model. The method is applied to two resting-state EEG datasets. Results: First, our analysis confirmed that, indeed, when overlooking time-dependence in frequency domain, the results are inconclusive and consequently, highlighted the importance of preserving time-information in the spectral domain. Second, it is confirmed using synthetic data that the local peaks in global field potential (GFP) waveform are influenced by spectral powers present in composite signals. Based on synthetic results, it is inferred that in our dataset, an average frequency range of 10–15 Hz dominates the formation and the temporal dynamics of microstates. Third, it is shown that multiple overlapping patterns of synchronized activities described by a single meta-process in full band microstate studies can be identified using the proposed frequency-band subdivision. The results are consistent across both datasets. Conclusion: This study opens several new ventures to be explored in the future: e.g. analysis of temporally overlapping patterns described so far by single topographic patterns, which we show to be spectrally differentiable via band-wise topographic segmentation proposed in the present study
Inhibition of return in time-lapse: Brain Rhythms during grip force control for spatial attention
Full text linkThe inhibition of return (IoR) is the observable slowed response to a target at a cued position for cue-target intervals of longer than 300 ms; when there has been enough time to disengage from a previously-cued location, an inhibitory after-effect can be observed. Studies aimed at understanding whether mechanisms underlying IoR act at a perceptual/attentional or a later response-execution stage have offered divergent results. Though focusing on the brain's responses to cue-target intervals can offer significant information on the nature of IoR, few studies have investigated neural activity during this interval; these studies suggest the generation of inhibitory tags on the spatial coordinates of the previously attended position which, in turn, inhibit motor programming toward that position. As such, a cue-target task was administered in this study; the rhythmic activity of EEG signals on the entire cue-target interval was measured to determine whether IoR is referred to early or late response processing stages. A visually-guided force variation during isometric contraction, instead of a key press response, was required to reduce the effect of motor response initiation. Our results indicated the prominent involvement of the fronto-parietal and occipital cortical areas post-cue appearance, with a peculiar theta band modulation characterizing the posterior parietal cortex. Theta activity in this region was enhanced post-cue onset, decreased over time, and was enhanced again when a target appeared in an unexpected location rather than in a cued position. This suggests that the mechanism that generates IoR sequentially affects perceptual/attentional processing and motor preparation rather than response execution
fMRI-vs-MEG evaluation of post-stroke interhemispheric asymmetries in primary sensorimotor hand areas
No full textGrowing evidence emphasizes a positive role of brain ipsilesional (IL) reorganization in stroke patients with partial recovery. Ten patients affected by a monohemispheric stroke in the middle cerebral artery territory underwent functional magnetic resonance (fMRI) and magnetoencephalography (MEG) evaluation of the primary sensory (S1) activation via the same paradigm (median nerve galvanic stimulation). Four patients did not present S1 fMRI activation [Rossini, P.M., Altamura, C., Ferretti, A., Vernieri, F., Zappasodi, F., Caulo, M., Pizzella, V., Del Gratta, C., Romani, G.L., Tecchio, F., 2004. Does cerebrovascular disease affect the coupling between neuronal activity and local haemodynamics? Brain 127, 99-110], although inclusion criteria required bilateral identifiable MEG responses. Mean Euclidean distance between fMRI and MEG S1 activation Talairach coordinates was 10.1 ± 2.9 mm, with a 3D intra-class correlation (ICC) coefficient of 0.986. Interhemispheric asymmetries, evaluated by an MEG procedure independent of Talairach transformation, were outside or at the boundaries of reference ranges in 6 patients. In 3 of them, the IL activation presented medial or lateral shift with respect to the omega-shaped post-rolandic area while in the other 3, IL areas were outside the peri-rolandic region. In conclusion, despite dissociated intensity, the MEG and fMRI activations displayed good spatial consistency in stroke patients, thus confirming excessive interhemispheric asymmetries as a suitable indicator of unusual recruitments in the ipsilesional hemisphere, within or outside the peri-rolandic region. © 2006 Elsevier Inc. All rights reserved
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