Neuronal avalanches differ from wakefulness to deep sleep - evidence from intracranial depth recordings in humans

Neuronal activity differs between wakefulness and sleep states. In contrast, an attractor state, called self-organized critical (SOC), was proposed to govern brain dynamics because it allows for optimal information coding. But is the human brain SOC for each vigilance state despite the variations in neuronal dynamics? We characterized neuronal avalanches – spatiotemporal waves of enhanced activity - from dense intracranial depth recordings in humans. We showed that avalanche distributions closely follow a power law – the hallmark feature of SOC - for each vigilance state. However, avalanches clearly differ with vigilance states: slow wave sleep (SWS) shows large avalanches, wakefulness intermediate, and rapid eye movement (REM) sleep small ones. Our SOC model, together with the data, suggested first that the differences are mediated by global but tiny changes in synaptic strength, and second, that the changes with vigilance states reflect small deviations from criticality to the subcritical regime, implying that the human brain does not operate at criticality proper but close to SOC. Independent of criticality, the analysis confirms that SWS shows increased correlations between cortical areas, and reveals that REM sleep shows more fragmented cortical dynamics

Neuronal avalanches change from wakefulness to deep sleep - a study of intracranial depth recordings in humans

Neuronal dynamics differs between wakefulness and sleep stages, so does the cognitive state. In contrast, a single attractor state, called self-organized critical (SOC), has been proposed to govern human brain dynamics for its optimal information coding and processing capabilities. Here we address two open questions: First, does the human brain always operate in this computationally optimal state, even during deep sleep? Second, previous evidence for SOC was based on activity within single brain areas, however, the interaction between brain areas may be organized differently. Here we asked whether the interaction between brain areas is SOC. ..

A Robust Method for Detecting Interdependences: Application to Intracranially Recorded EEG

We present a measure for characterizing statistical relationships between two time sequences. In contrast to commonly used measures like cross-correlations, coherence and mutual information, the proposed measure is non-symmetric and provides information about the direction of interdependence. It is closely related to recent attempts to detect generalized synchronization. However, we do not assume a strict functional relationship between the two time sequences and try to define the measure so as to be robust against noise, and to detect also weak interdependences. We apply our measure to intracranially recorded electroencephalograms of patients suffering from severe epilepsies.Comment: 29 pages, 5 figures, paper accepted for publication in Physica

DYNAMIC MODEL WITH A NEW FORMULATION OF CORIOLIS/CENTRIFUGAL MATRIX FOR ROBOT MANIPULATORS

The paper presents a complete generalized procedure based on the Euler-Lagrange equations to build the matrix form of dynamic equations, called dynamic model, for robot manipulators. In addition, a new formulation of the Coriolis/centrifugal matrix is proposed. The link linear and angular velocities are formulated explicitly. Therefore, the translational and rotational Jacobian matrices can be derived straightforward from definition, which makes the calculation of the generalized inertia matrix more convenient. By using Kronecker product, a new Coriolis/centrifugal matrix formulation is set up directly in matrix-based manner and guarantees the skew symmetry property of robot dynamic equations. This important property is usually exploited for developing many control methodologies. The validation of the proposal formulation is confirmed through the symbolic solution and simulation of a typical robot manipulator

FATTY ACID COMPOSITION AND ANTIOXIDANT ACTIVITY OF CAMELLIA NINHII SEED OIL COLLECTED IN LAM DONG PROVINCE

The seed oil of Camellia ninhii was studied for the first time on its fatty acid composition by gas chromatography-mass spectrometry (GC-MS) and antioxidant activity by the DPPH method. The results show that unsaturated fatty acids account for the largest amount, especially oleic acid with 45.43% of the total sample analyzed. In addition, other fatty acids, palmitic, linoleic, pentadecanoic, and two aromatic acids, benzoic and cinnamic, were present. The sample of C. ninhii seed oil exhibited mild antioxidant activity against DPPH free radicals with IC50 = 0.94 mg/mL

Molecular identification of three Habenaria species from Binh Chau-Phuoc Buu Nature Reserve, Vietnam

The present provides molecular data for species of Habenaria diphylla (Nimmo) Dalzell, H. khasiana Hook.f. and H. rostellifera Rchb.f. collected from Binh Chau-Phuoc Buu Nature Reserve, Vietnam for the first time. Along with other DNA sequences from GenBank database, the phylogenetic trees for Habenaria species from Vietnam have been established

Social capital and job search success: The case of undergraduates in Ho Chi Minh City, Vietnam

The literature has proven the positive role of social capital on job search success, but the researchers' community has not been convinced completely because social capital is not always good. Moreover, only certain dimensions of the two latent variables were analyzed in the previous research though they are multidimensional. This paper approached the social capital and job search success multidimensionally by applying Partial Least Square - Structural Equation Model (PLS-SEM) to explore the path that social capital impacts on job search success. The primary data of 400 undergraduates in Ho Chi Minh City, Vietnam were used in the model. The results have confirmed the positive role of bonding social capital and general trust in acquired job quality, job search cost and job search convenience