Using video on the Internet has become a common practice, but the television-like ‘passive viewer’ approach misses the benefits of the interactive nature of the Internet. The technological limitations of television can be overridden by the Internet. Having multiple sources of input does not mean they should be merged into one editor-controlled flat output. Treating streams as objects, it is possible to make viewers editors for their screens whenever they want, or let them watch a pre-edited version. Active streams are distributed to viewers to gain control over the scene layout. Recorded scenes can be remastered whenever needed and represented in different views simultaneously. For lectures and conference recordings, inline slide browsing is also possible. This approach was successfully tested in the Viditory.net project for the broadcasting and recording of conferences with multi-camera shots and remote speakers. Despite the Adobe Flash platform becoming obsolete, it is possible to implement similar capabilities on modern platforms and by using modern technologies.
Although schizophrenia was previously associated with affected spatial neuronal synchronization, surprisingly little is known about the temporal dynamics of neuronal oscillations in this disease. However, given that the coordination of neuronal processes in time represents an essential aspect of practically all cognitive operations, it might be strongly affected in patients with schizophrenia. In the present study we aimed at quantifying long-range temporal correlations (LRTC) in patients (18 with schizophrenia; 3 with schizoaffective disorder) and 28 healthy control subjects matched for age and gender. Ongoing neuronal oscillations were recorded with multi-channel EEG at rest condition. LRTC in the range 5-50s were analyzed with Detrended Fluctuation Analysis. The amplitude of neuronal oscillations in alpha and beta frequency ranges did not differ between patients and control subjects. However, LRTC were strongly attenuated in patients with schizophrenia in both alpha and beta frequency ranges. Moreover, the cross-frequency correlation between LRTC belonging to alpha and beta oscillations was stronger for patients than healthy controls, indicating that similar neurophysiological processes affect neuronal dynamics in both frequency ranges. We believe that the attenuation of LRTC is most likely due to the increased variability in neuronal activity, which was previously hypothesized to underlie an excessive switching between the neuronal states in patients with schizophrenia. Attenuated LRTC might allow for more random associations between neuronal activations, which in turn might relate to the occurrence of thought disorders in schizophrenia.
We present a novel method for the extraction of neuronal components showing cross-frequency phase synchronization.
In general the method can be applied for the detection of phase interactions between components with frequencies f1 and f2, where f2 ≈ rf1 and r is some integer. We refer to the method as cross-frequency decomposition (CFD), which consists of the following steps: (a) extraction of f1-oscillations with the spatio-spectral decomposition algorithm (SSD); (b) frequency modification of the f1-oscillations obtained with SSD; and (c) finding f2-oscillations synchronous with f1-oscillations using least-squares estimation.
Our simulations showed that CFD was capable of recovering interacting components even when the signal-to-noise ratio was as low as 0.01. An application of CFD to the real EEG data demonstrated that cross-frequency phase synchronization between alpha and beta oscillations can originate from the same or remote neuronal populations.
CFD allows a compact representation of the sets of interacting components. The application of CFD to EEG data allows differentiating cross-frequency synchronization arising due to genuine neurophysiological interactions from interactions occurring due to quasi-sinusoidal waveform of neuronal oscillations.
CFD is a method capable of extracting cross-frequency coupled neuronal oscillations even in the presence of strong noise.
Copyright © 2011 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.
We consider a minimal action of a finitely generated semigroup by homeomorphisms of the circle, and show that the collection of translation numbers of individual elements completely determines the set of generators (up to a common continuous change of coordinates). One of the main tools used in the proof is the synchronization properties of random dynamics of circle homeomorphisms: Antonov’s theorem and its corollaries.