Papers by Stiliyan Kalitzin
Springer eBooks, Apr 7, 2008
The harmonic N=3 superspace with the even part M4×[SU(3)/U(1)×U(1)] is used to build up an uncons... more The harmonic N=3 superspace with the even part M4×[SU(3)/U(1)×U(1)] is used to build up an unconstrained off-shell superfield formulation of N=3 super Yang-Mills theory. It is defined in an analytic subspace of this N=3 superspace and is described by three analytic gauge connections entering into the harmonic derivatives. Jumping over the “N=3 barrier” becomes possible due to the presence of
Oxford University Press eBooks, Nov 1, 2017
Early seizure-prediction paradigms were based on detecting electroencephalographic (EEG) features... more Early seizure-prediction paradigms were based on detecting electroencephalographic (EEG) features, but recent approaches are based on dynamic systems theory. Methods that attempted to detect predictive features during the preictal period proved difficult to validate in practice. Brain systems can display bistability (both normal and epileptic states can coexist), and the transitions between states may be initiated by external or internal dynamic factors. In the former case prediction is impossible, but in the latter case prediction is conceivable, leading to the hypothesis that as seizure onset approaches, the excitability of the underlying neuronal networks tends to increase. This assumption is being explored using not only the ongoing EEG but also active probes, applying appropriate stimuli to brain areas to estimate the excitability of the neuronal populations. Experimental results support this assumption, suggesting that it may be possible to develop paradigms to estimate the risk of an impending transition to an epileptic state.
Springer eBooks, 1997
Scale space approach provides a tool for studying a given image at all scales simultaneously. Fea... more Scale space approach provides a tool for studying a given image at all scales simultaneously. Features that can be detected at large scales can provide clues for tracing more detailed information at fine scales. For this ideology to be constructive, one needs to investigate which local properties (or local operators) are appropriate for quantifying the desired features and how these properties are changing from scale to scale. In various applications (Kass et al., 1987; Koenderink, 1990), specially those concerned with oriented structures, singular points are of particular interest. Singular points, or simply singularities below, are those points in a grayscale image, where the gradient vector field vanishes (Lindeberg, 1992; Johansen, 1994). Examples of such points in two dimensional images are extrema, saddle points, “monkey” saddles etc. Singular points can be characterized by their order. The order of a singular point is the lowest non-vanishing power in the Taylor expansion of the image field L(x 1, x 2, ..., x d ) around this point. Obviously the order must be greater than 1, since the gradient vector L i = ∂L(x 1, x 2, ..., x d ) is equal to zero in this point.
Journal of Neural Engineering, Jul 6, 2011
In previous studies we showed that autonomous absence seizure generation and termination can be e... more In previous studies we showed that autonomous absence seizure generation and termination can be explained by realistic neuronal models eliciting bi-stable dynamics. In these models epileptic seizures are triggered either by external stimuli (reflex epilepsies) or by internal fluctuations. This scenario predicts exponential distributions of the duration of the seizures and of the inter-ictal intervals. These predictions were validated in rat models of absence epilepsy, as well as in a few human cases. Nonetheless, deviations from the predictions with respect to seizure duration distributions remained unexplained. The objective of the present work is to implement a simple but realistic computational model of a neuronal network including synaptic plasticity and ionic current dynamics and to explore the dynamics of the model with special emphasis on the distributions of seizure and inter-ictal period durations. We use as a basis our lumped model of cortical neuronal circuits. Here we introduce 'activity dependent' parameters, namely post-synaptic voltage-dependent plasticity, as well as a voltage-dependent hyperpolarization-activated current driven by slow and fast activation conductances. We examine the distributions of the durations of the seizure-like model activity and the normal activity, described respectively by the limit cycle and the steady state in the dynamics. We use a parametric γ-distribution fit as a quantifier. Our results show that autonomous, activity-dependent membrane processes can account for experimentally obtained statistical distributions of seizure durations, which were not explainable using the previous model. The activity-dependent membrane processes that display the strongest effect in accounting for these distributions are the hyperpolarization-dependent cationic (I(h)) current and the GABAa plastic dynamics. Plastic synapses (NMDA-type) in the interneuron population show only a minor effect. The inter-ictal statistics retain their consistency with the experimental data and the previous model.
Classical and Quantum Gravity, Sep 1, 1987
ABSTRACT
Journal of physics, Dec 1, 1985
Page 1. Harmonic superspaces of extended supersymmetry. I. The calculus of harmonic variables Thi... more Page 1. Harmonic superspaces of extended supersymmetry. I. The calculus of harmonic variables This article has been downloaded from IOPscience. Please scroll down to see the full text article. 1985 J. Phys. A: Math. Gen. 18 3433 ...
Physics Letters B, Feb 1, 1985
The harmonic N = 3 superspace with the even part M4 X [SU(3)/U(l) X U(l)] is used to build up an ... more The harmonic N = 3 superspace with the even part M4 X [SU(3)/U(l) X U(l)] is used to build up an unconstrained offshell superfield formulation of N= 3 super Yang-Mills theory. It is defined in an analytic subspace of this N = 3 superspace and is described by three analytic gauge connections entering into the harmonic derivatives. Jumping over the 'N = 3 barrier" becomes possible due to the presence of an infinite set of auxiliary fields.
We present a method to detect vessels in images of the retina. Instead of relying on pixel classi... more We present a method to detect vessels in images of the retina. Instead of relying on pixel classification, as many detection algorithms do, we propose a more natural representation for elongated structures, such as vessels. This new representation consists of primitives called affine convex sets. On these convex sets we apply the classification step. The reason for choosing this approach is twofold: (1) By using a dedicated representation of image structures, one can exploit prior knowledge. (2) A method based on pixel classification is often computationally unattractive. The method can also be applied to other image structures, if an appropriate representation for the structures is chosen. The method was tested on fundus reflection images. We obtained an accuracy of 0.897, a sensitivity of 0.700 and a specificity of 0.923.
Nuclear Physics B, Nov 1, 1992
A certain class of cellular automata in 1 space + 1 time dimension is shown to be closely related... more A certain class of cellular automata in 1 space + 1 time dimension is shown to be closely related to quantum field theories containing Dirac fermions. In the massless case this relation can be studied analytically, while the introduction of Dirac mass requires numerical simulations. We show that in the last case the cellular automaton describes the corresponding field theory only approximately.
A phenomenological neural network model with bi-stable oscillatory units is used to model up- and... more A phenomenological neural network model with bi-stable oscillatory units is used to model up- and down-states. These states have been observed in vivo in biological neuronal systems and feature oscillatory, limit cycle type of behavior in the up-states. A network is formed by a set of interconnected units. Two different types of network layouts are considered in this work: networks with hierarchical connections and hubs and networks with random connections. The phase coherence between the different units is analyzed and compared to the connectivity distance between nodes. In addition the connectivity degree of a node is associated to the average phase coherence with all other units. The results show that we may be able to identify the set of hubs in a network based on the phase coherence estimates between the different nodes. If the network is very dense or randomly connected, the underlying network structure, however, can not be derived uniquely from the phase coherence.
Clinical Neurophysiology, Oct 1, 2014
IEEE Transactions on Pattern Analysis and Machine Intelligence, Jul 1, 2005
A method is presented that uses grouping to improve local classification of image primitives. The... more A method is presented that uses grouping to improve local classification of image primitives. The grouping process is based upon a spin-glass system, where the image primitives are treated as possessing a spin. The system is subject to an energy functional consisting of a local and a bilocal part, allowing interaction between the image primitives. Instead of defining the state of lowest energy as the grouping result, the mean state of the system is taken. In this way, instabilities caused by multiple minima in the energy are being avoided. The means of the spins are taken as the a posteriori probabilities for the grouping result. In the paper, it is shown how the energy functional can be learned from example data. The energy functional is defined in such a way that, in case of no interactions between the elements, the means of the spins equal the a priori local probabilities. The grouping process enables the fusion of the a priori local and bilocal probabilities into the a posteriori probabilities. The method is illustrated both on grouping of line elements in synthetic images and on vessel detection in retinal fundus images.
Physics Letters B, Mar 1, 1991
We propose actions from which the self-dual Yang-Mills and Einstein equations in four dimensions ... more We propose actions from which the self-dual Yang-Mills and Einstein equations in four dimensions follow by straightforward variation. This off-shell formulation essentially involves harmonic variables. After reformulation in harmonic space, the selfduality constraints can be derived from actions with the help of Lagrange multipliers. The latter turn out not to describe additional degrees of freedom. The off-shell theories obtained can be quantized in a standard way.
Classical and Quantum Gravity, Sep 1, 1990
Classical and Quantum Gravity, May 5, 1991
ABSTRACT
Physics Letters B, Sep 1, 1983
We prove the equivalence between the D-dimensional scalar quantum field theory and the correspond... more We prove the equivalence between the D-dimensional scalar quantum field theory and the corresponding D + 1 (with fictitious time) stochastically quantized field theory. The superdiagram technique is used within perturbation theory. The independence of the Green's functions on the fictitious time is shown.
Journal of Biomechanics, May 1, 2019
Elderly people and people with epilepsy may need assistance after falling, but may be unable to s... more Elderly people and people with epilepsy may need assistance after falling, but may be unable to summon help due to injuries or impairment of consciousness. Several wearable fall detection devices have been developed, but these are not used by all people at risk. We present an automated analysis algorithm for remote detection of high impact falls, based on a physical model of a fall, aiming at universality and robustness. Candidate events are automatically detected and event features are used as classifier input. The algorithm uses vertical velocity and acceleration features from optical flow outputs, corrected for distance from the camera using moving object size estimation. A sound amplitude feature is used to increase detector specificity. We tested the performance and robustness of our trained algorithm using acted data from a public database and real life data with falls resulting from epilepsy and with daily life activities. Applying the trained algorithm to the acted dataset resulted in 90% sensitivity for detection of falls, with 92% specificity. In the real life data, six/nine falls were detected with a specificity of 99.7%; there is a plausible explanation for not detecting each of the falls missed. These results reflect the algorithm's robustness and confirms the feasibility of detecting falls using this algorithm.
Springer series in cognitive and neural systems, 2019
An overview of the pathophysiology of absence seizures is given, focusing on computational modell... more An overview of the pathophysiology of absence seizures is given, focusing on computational modelling where recent neurophysiological experimental evidence is incorporated. The main question addressed is what is the dynamical process by which the same brain can produce sustained bursts of synchronous spike-and-wave discharges (SWDs) and normal, largely desynchronized brain activity, i.e. to display bistability. This generic concept, tested on an updated neural mass computational model of absence seizures, predicts certain properties of the probability distributions of inter-ictal intervals and of the durations of ictal events. A critical analysis of the distributions predicted by the model and those found in reality led to adjustments of the model with respect to the control of the duration of ictal events. Another prediction derived from the bistable dynamics, the possibility of aborting absence seizures by means of counter-controlled electrical stimulation, is also discussed in the light of current experimental studies. Finally the most recent update of the model was carried out to account for the particular properties of the cortical “driver” of SWDs, and the underlying putative role of the persistent Na+ current of cortical neurons in this process.
Brain Stimulation, Nov 1, 2016
Background. Neurological disorders are often characterized by an excessive and prolonged imbalanc... more Background. Neurological disorders are often characterized by an excessive and prolonged imbalance between neural excitatory and inhibitory processes. A ubiquitous finding among these disorders is the disrupted function of inhibitory GABAergic interneurons. Objective. The objective is to propose a novel stimulation procedure able to evaluate the efficacy of inhibition imposed by GABAergic interneurons onto pyramidal cells from evoked responses observed in local field potentials (LFPs). Methods. Using a computational modeling approach combined with in vivo and in vitro electrophysiological recordings, we analyzed the impact of electrical extracellular local bipolar stimulation (ELBS) on brain tissue. We implemented the ELBS effects in a neuronal population model in which we can tune the excitationinhibition ratio and we investigated stimulation-related parameters. Computer simulations led to sharp predictions regarding: i) the shape of evoked responses as observed in local field potentials, ii) the type of cells (pyramidal neurons and interneurons) contributing to these field responses and iii) the optimal tuning of stimulation parameters (intensity and frequency) to evoke meaningful responses. These predictions were tested in vivo (mouse). Neurobiological mechanisms were assessed in vitro (hippocampal slices). Results. Appropriately-tuned ELBS allows for preferential activation of GABAergic interneurons. A quantitative Neural Network Excitability Index (NNEI) is proposed. It is computed from stimulation-induced responses as reflected in local field potentials. NNEI was used in four patients with focal epilepsy. Results show that it can readily reveal hyperexcitable brain regions. Conclusion. Well-tuned ELBS and NNEI can be used to locally probe brain regions and quantify the (hyper)excitability of the underlying brain tissue.
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Papers by Stiliyan Kalitzin