36 research outputs found
Neural synchronization within and between regions of the motor system
Full text linkDaffertshofer, A. [Promotor]Beek, P.J. [Promotor
Interactive visualization of event logs for cybersecurity
Full text linkHidden cyber threats revealed with new visualization software Eventpa
Resting-state oscillatory activity in children born small for gestational age: an MEG study
No full textGrowth restriction in utero during a period that is critical for normal growth of the brain, has previously been associated with deviations in cognitive abilities and brain anatomical and functional changes. We measured magnetoencephalography (MEG) in 4- to 7-year-old children to test if children born small for gestational age (SGA) show deviations in resting-state brain oscillatory activity. Children born SGA with postnatally spontaneous catch-up growth [SGA+; six boys, seven girls; mean age 6.3 year (SD= 0.9)] and children born appropriate for gestational age [AGA; seven boys, three girls; mean age 6.0 year (SD = 1.2)] participated in a resting-state MEG study. We calculated absolute and relative power spectra and used non-parametric statistics to test for group differences. SGA+ and AGA born children showed no significant differences in absolute and relative power except for reduced absolute gamma band power in SGA children. At the time of MEG investigation, SGA+ children showed significantly lower head circumference (HC) and a trend toward lower IQ, however there was no association of HC or IQ with absolute or relative power. Except for reduced absolute gamma band power, our findings suggest normal brain activity patterns at school age in a group of children born SGA in which spontaneous catch-up growth of bodily length after birth occurred. Although previous findings suggest that being born SGA alters brain oscillatory activity early in neonatal life, we show that these neonatal alterations do not persist at early school age when spontaneous postnatal catch-up growth occurs after birth. © 2013 Boersma, de Bie, Oost-rom, van Dijk, Hillebrand, van Wijk, Delemarre-van de Waal and Stam
On the influence of amplitude on the connectivity between phases
Full text linkIn recent studies, functional connectivities have been reported to display characteristics of complex networks that have been suggested to concur with those of the underlying structural, i.e. anatomical, networks. Do functional networks always agree with structural ones? In all generality, this question can be answered with no: for instance, a fully synchronized state would imply isotropic homogeneous functional connections irrespective of the ‘real’ underlying structure. A proper inference of structure from function and vice versa requires more than a sole focus on phase synchronization. We show that functional connectivity critically depends on amplitude variations, which implies that, in general, phase patterns should be analyzed in conjunction with the corresponding amplitude. We discuss this issue by comparing the phase synchronization patterns of interconnected Wilson-Cowan models vis-à-vis Kuramoto networks of phase oscillators. For the interconnected Wilson-Cowan models we derive analytically how connectivity between phases explicitly depends on the generating oscillators’ amplitudes. In consequence, the link between neurophysiological studies and computational models always requires the incorporation of the amplitude dynamics. Supplementing synchronization characteristics by amplitude patterns, as captured by, e.g., spectral power in M/EEG recordings, will certainly aid our understanding of the relation between structural and functional organizations in neural networks at large
A role of beta oscillatory synchrony in biasing response competition?
No full textBeta-range oscillatory activity measured over the motor cortex and beta synchrony between cortex and spinal cord can be up- or downregulated in anticipation of a postural challenge or the initiation of movement. Based on these properties of beta activity in the preparation for future events, the present investigation addressed whether simultaneous up- and downregulation of beta activity might act as an online mechanism to suppress and select competing responses. Measures of local and long-range beta synchrony were obtained from electroencephalographic and electromyographic signals recorded during a cued choice reaction task. Analyses focused on task-related changes in beta synchrony during a 2-s delay period between cue and response signal. Analyzed separately, none of the beta measures (spectral power, corticospinal coherence, corticospinal phase synchronization) showed simultaneous up- and downregulation over opposite hemispheres controlling the competing responses. However, the combined pattern of beta measures showed beta power desynchronization associated with selection of a response and increased corticospinal coherence and phase synchronization associated with suppression of a response. These results indicate that concurrent up- and downregulation of different components of beta oscillatory activity is likely to have a functional role in response selection, resembling attentional modulation of alpha activity in visual selection
Corticomuscular and bilateral EMG coherence reflect distinct aspects of neural synchronization
No full textUsing electroencephalography (EEG) and electromyography (EMG), corticomuscular and bilateral motor unit synchronization have been found in different frequency bands and under different task conditions. These different types of long-range synchrony are hypothesized to originate from distinct mechanisms. We tested this by comparing time-resolved EEG-EMG and EMG-EMG coherence in a bilateral precision-grip task. Bilateral EMG activity was synchronized between 7 and 13 Hz for about 1 s when force output from both hands changed from an increasing to a stable force production. In contrast, EEG-EMG coherence was statistically significant between 15 and 30 Hz during stable force production. The disparities in their time-frequency profiles accord with the existence of distinct underlying processes for corticomuscular and bilateral motor unit synchronization. In addition, the absence of synchronization between cortical activity and common spinal input at 10 Hz renders a cortical source unlikely. © 2009 Elsevier Ireland Ltd. All rights reserved
Eventpad : a visual analytics approach to network intrusion detection and reverse engineering
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Nonlinear coupling between occipital and motor cortex during motor imagery: A dynamic causal modeling study
No full textWe demonstrate the capacity of dynamic causal modeling to characterize the nonlinear coupling among cortical sources that underlie time-frequency modulations in MEG data. Our experimental task involved the mental rotation of hand drawings that ten subjects used to decide if it was a right or left hand. Reaction times were shorter when the stimuli were presented with a small rotation angle (fast responses) compared to a large rotation angle (slow responses). The grand-averaged data showed that in both cases performance was accompanied by a marked increase in gamma activity in occipital areas and a concomitant decrease in alpha and beta power in occipital and motor regions. Modeling directed (cross) frequency interactions between the two regions revealed that after the stimulus induced a gamma increase and beta decrease in occipital regions, interactions with the motor area served to attenuate these modulations. The difference between fast and slow behavioral responses was manifest as an altered coupling strength in both forward and backward connections, which led to a less pronounced attenuation for more difficult (slow reaction time) trials. This was mediated by a (backwards) beta to gamma coupling from motor till occipital sources, whereas other interactions were mainly within the same frequency. Results are consistent with the theory of predictive coding and suggest that during motor imagery, the influence of motor areas on activity in occipital cortex co-determines performance. Our study illustrates the benefit of modeling experimental responses in terms of a generative model that can disentangle the contributions of intra-areal vis-à-vis inter-areal connections to time-frequency modulations during task performance. © 2013 Elsevier Inc
