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Biomedical subjects

S Stramaglia

Publications and source records attributed to S Stramaglia.

11 recordsLinked to original sources
PubMed2005

The measure of randomness by leave-one-out prediction error in the analysis of EEG after laser painful stimulation in healthy subjects and migraine patients.

OBJECTIVE: We aimed to perform a quantitative analysis of event-related modulation of EEG activity, resulting from a not-warned and a warned paradigm of painful laser stimulation, in migraine patients and controls, by the use of a novel analysis, based upon a parametric approach to measure predictability of short and noisy time series. METHODS: Ten migraine patients were evaluated during the not-symptomatic phase and compared to seven age and sex matched controls. The dorsum of the right hand and the right supraorbital zone were stimulated by a painful CO(2) laser, in presence or in absence of a visual warning stimulus. An analysis time of 1s after the stimulus was submitted to a time-frequency analysis by a complex Morlet wavelet and to a cross-correlation analysis, in order to detect the development of EEG changes and the most activated cortical regions. A parametric approach to measure predictability of short and noisy time series was applied, where time series were modeled by leave-one-out (LOO) error. RESULTS: The averaged laser-evoked potentials features were similar between the two groups in the alerted and not alerted condition. A strong reset of the beta rhythms after the painful stimuli was seen for three groups of electrodes along the midline in patients and controls: the predictability of the series induced by the laser stimulus changed very differently in controls and patients. The separation was more evident after the warning signal, leading to a separation with P-values of 0.0046 for both the hand and the face. DISCUSSION: As painful stimulus causes organization of the local activity in cortex, EEG series become more predictable after stimulation. This phenomenon was less evident in migraine, as a sign of an inadequate cortical reactivity to pain. SIGNIFICANCE: The LOO method enabled to show in migraine subtle changes in the cortical response to pain.

Adult↗
PubMed2005

Leave-one-out prediction error of systolic arterial pressure time series under paced breathing.

In this paper, we consider systolic arterial pressure time series from healthy subjects and chronic heart failure patients, undergoing paced respiration, and show that different physiological states and pathological conditions may be characterized in terms of predictability of time series signals from the underlying biological system. We model time series by the regularized least-squares approach and quantify predictability by the leave-one-out error. We find that the entrainment mechanism connected to paced breath, that renders the arterial blood pressure signal more regular and thus more predictable, is less effective in patients, and this effect correlates with the seriousness of the heart failure. Using a Gaussian kernel, so that all orders of nonlinearity are taken into account, the leave-one-out error separates controls from patients (probability less than 10(-7)), and alive patients from patients for whom cardiac death occurred (probability less than 0.01).

Algorithms↗
PubMed2004

Steady-state visual evoked potentials and phase synchronization in migraine patients.

We investigate phase synchronization in EEG recordings from migraine patients. We use the analytic signal technique, based on the Hilbert transform, and find that migraine brains are characterized by enhanced alpha band phase synchronization in the presence of visual stimuli. Our findings show that migraine patients have an overactive regulatory mechanism that renders them more sensitive to external stimuli.

Adult↗
PubMed2004

Phase shifts of synchronized oscillators and the systolic-diastolic blood pressure relation.

We study the phase-synchronization properties of systolic and diastolic arterial pressure in healthy subjects. We find that delays in the oscillatory components of the time series depend on the frequency bands that are considered, in particular we find a change of sign in the phase shift going from the very low frequency band to the high frequency band. This behavior should reflect a collective behavior of a system of nonlinear interacting elementary oscillators. We prove that some models describing such systems, e.g., the Winfree and the Kuramoto models, offer a clue to this phenomenon. For these theoretical models there is a linear relationship between phase shifts and the difference of natural frequencies of oscillators and a change of sign in the phase shift naturally emerges.

Biological Clocks↗
PubMed2004

Visually evoked phase synchronisation changes of alpha rhythm in migraine. Correlations with clinical features.

We investigate phase synchronisation in EEG recordings from migraine patients. We use the analytic signal technique, based on the Hilbert transform, and find that migraine brains are characterised by enhanced alpha band phase synchronisation in the presence of visual stimuli. In migraine, the brain synchronises to the idling rhythm of the visual areas under certain photic stimulations; hypersynchronisation of the alpha rhythm may suggest a state of cortical hypoexcitability during the interictal phase of migraine.

Adult↗
PubMed2001

Diluted neural networks with adapting and correlated synapses.

We consider the dynamics of diluted neural networks with clipped and adapting synapses. Unlike previous studies, the learning rate is kept constant as the connectivity tends to infinity: the synapses evolve on a time scale intermediate between the quenched and annealing limits and all orders of synaptic correlations must be taken into account. The dynamics is solved by mean-field theory, the order parameter for synapses being a function. We describe the effects, in the double dynamics, due to synaptic correlations.

Biophysical Phenomena↗
PubMed2000

Clustering data by inhomogeneous chaotic map lattices.

A new approach to clustering, based on the physical properties of inhomogeneous coupled chaotic maps, is presented. A chaotic map is assigned to each data point and short range couplings are introduced. The stationary regime of the system corresponds to a macroscopic attractor independent of the initial conditions. The mutual information between pairs of maps serves to partition the data set in clusters, without prior assumptions about the structure of the underlying distribution of the data. Experiments on simulated and real data sets show the effectiveness of the proposed algorithm.

Journal Article↗
PubMed1999

Multiscale analysis of blood pressure signals.

We describe the multiresolution wavelet analysis of blood pressure waves in vasovagal syncope-affected patients compared with those in healthy people, using Haar and Gaussian bases. A comparison between scale-dependent and scale-independent measures discriminating the two classes of subjects is made. What emerges is a sort of equivalence between these two methodological approaches, that is, both methods reach the same statistical significance of separation between the two classes.

Biophysical Phenomena↗
PubMed1999

Chaos in neural networks with a nonmonotonic transfer function.

Time evolution of diluted neural networks with a nonmonotonic transfer function is analytically described by flow equations for macroscopic variables. The macroscopic dynamics shows a rich variety of behaviors: fixed-point, periodicity, and chaos. We examine in detail the structure of the strange attractor and in particular we study the main features of the stable and unstable manifolds, the hyperbolicity of the attractor, and the existence of homoclinic intersections. We also discuss the problem of the robustness of the chaos and we prove that in the present model chaotic behavior is fragile (chaotic regions are densely intercalated with periodicity windows), according to a recently discussed conjecture. Finally we perform an analysis of the microscopic behavior and in particular we examine the occurrence of damage spreading by studying the time evolution of two almost identical initial configurations. We show that for any choice of the parameters the two initial states remain microscopically distinct.

Models, Theoretical↗
PubMed1999

Phase ordering in chaotic map lattices with conserved dynamics.

Dynamical scaling in a two-dimensional lattice model of chaotic maps, in contact with a thermal bath at temperature T, is numerically studied. The model here proposed is equivalent to a conserved Ising model with couplings that fluctuate over the same time scale as spin moves. When coupling fluctuations and thermal fluctuations are both important, this model does not belong to the class of universality of a Langevin equation known as model B; the scaling exponents are continuously varying with T and depend on the map used. The universal behavior of model B is recovered when thermal fluctuations are dominant.

Journal Article↗