arXiv subjects

Miroslaw Latka

Publications and source records attributed to Miroslaw Latka.

9 recordsLinked to original sources

arXiv2017

Signatures of Parkinson's disease in complexity of low-frequency fluctuations of postural sway velocity

Posturography is routinely used to qualitatively assess one of the cardinal symptoms of Parkinson's disease -- postural instability. While most measures of balance control are derived from displacement of the center of pressure there is evidence that such control is more likely to be velocity-based. We performed static posturographic tests (eyes open and eyes closed) during quiet standing in narrow stance for n=30 patients with Parkinson's disease (PDP) in the ON state and compared the results with those of n=30 age-matched senior controls (HSC) and n=60 young controls (HYC). We used differentiator filters to generate time series of low-frequency fluctuations of sway velocity and calculated their Lempel-Ziv complexity (LZC). With eyes closed, the mediolateral LZC of HSC 0.21 (0.02) was significantly higher than those of HYC 0.19 (0.02) and PDP 0.18 (002). Thus aging and PD have opposite effects on mediolateral LZC which strongly differentiates between HSC and PDP (92% sensitivity and 87% specificity).

q-bio.NC↗

arXiv2017

Alpha Wavelet Power as a Biomarker of Antidepressant Treatment Response in Bipolar Depression

There is mounting evidence of a link between the properties of electroencephalograms (EEGs) of depressive patients and the outcome of pharmacotherapy. The goal of this study was to develop an EEG biomarker of antidepressant treatment response which would require only a single EEG measurement. We recorded resting, 21-channel EEG in 17 inpatients suffering from bipolar depression in eyes closed and eyes open conditions. The EEG measurement was performed at the end of the short washout period which followed previously unsuccessful pharmacotherapy. We calculated the normalized wavelet power of alpha rhythm using two referential montages and an average reference montage. In particular, in the occipital (O1, O2, Oz) channels the wavelet power of responders was up to 84% higher than that of nonresponders. Using a novel classification algorithm we were able to correctly predict the outcome of treatment with 90% sensitivity and 100% specificity. The proposed biomarker requires only a single EEG measurement and consequently is intrinsically different from biomarkers which exploit the changes in prefrontal EEG induced by pharmacotherapy over a given time.

q-bio.NC↗

arXiv2017

Asymmetry of short-term control of spatio-temporal gait parameters during treadmill walking

Optimization of energy cost determines average values of spatio-temporal gait parameters such as step duration, step length or step speed. However, during walking, humans need to adapt these parameters at every step to respond to exogenous and/or endogenic perturbations. While some neurological mechanisms that trigger these responses are known, our understanding of the fundamental principles governing step-by-step adaptation remains elusive. We determined the gait parameters of 20 healthy subjects with right-foot preference during treadmill walking at speeds of 1.1, 1.4 and 1.7 m/s. We found that when the value of the gait parameter was conspicuously greater (smaller) than the mean value, it was either followed immediately by a smaller (greater) value of the contralateral leg (interleg control), or the deviation from the mean value decreased during the next movement of ipsilateral leg (intraleg control). The selection of step duration and the selection of step length during such transient control events were performed in unique ways. We quantified the symmetry of short-term control of gait parameters and observed the significant dominance of the right leg in short-term control of all three parameters at higher speeds (1.4 and 1.7 m/s).

physics.bio-ph↗

arXiv2010

Time and ensemble averaging in time series analysis

In many applications expectation values are calculated by partitioning a single experimental time series into an ensemble of data segments of equal length. Such single trajectory ensemble (STE) is a counterpart to a multiple trajectory ensemble (MTE) used whenever independent measurements or realizations of a stochastic process are available. The equivalence of STE and MTE for stationary systems was postulated by Wang and Uhlenbeck in their classic paper on Brownian motion (Rev. Mod. Phys. 17, 323 (1945)) but surprisingly has not yet been proved. Using the stationary and ergodic paradigm of statistical physics -- the Ornstein-Uhlenbeck (OU) Langevin equation, we revisit Wang and Uhlenbeck's postulate. In particular, we find that the variance of the solution of this equation is different for these two ensembles. While the variance calculated using the MTE quantifies the spreading of independent trajectories originating from the same initial point, the variance for STE measures the spreading of two correlated random walkers. Thus, STE and MTE refer to two completely different dynamical processes. Guided by this interpretation, we introduce a novel algorithm of partitioning a single trajectory into a phenomenological ensemble, which we name a threshold trajectory ensemble (TTE), that for an ergodic system is equivalent to MTE. We find that in the cohort of healthy volunteers, the ratio of STE and TTE asymptotic variances of stage 4 sleep electroencephalogram is equal to 1.96 \pm 0.04 which is in agreement with the theoretically predicted value of 2.

physics.data-an↗

arXiv2004

Phase synchronization in cerebral hemodynamics

A healthy human brain is perfused with blood flowing laminarly through cerebral vessels, providing brain tissue with substrates such as oxygen and glucose. Under normal conditions, cerebral blood flow is controlled by autoregulation as well as metabolic, chemical and neurogenic regulation. Physiological complexity of these mechanisms invariably leads to a question as to what are the relations between the statistical properties of arterial and intracranial pressure fluctuations. To shed new light on cerebral hemodynamics, we employ a complex continuous wavelet transform to determine the instantaneous phase difference between the arterial blood pressure (ABP) and intracranial pressure (ICP) in patients with traumatic brain injuries or spontaneous cerebral hemorrhage. For patients with mild to moderate injury, the phase difference slowly evolves in time. However, severe neurological injury with elevated ICP are herein associated with synchronization of arterial and intracranial pressure. We use Shannon entropy to quantify the stability of ABP-ICP phase difference and discuss the clinical applicability of such measure to assessment of cerebrovascular reactivity and autoregulation integrity.

q-bio.OT↗

arXiv2003

Deterministic uncertainty

Equations of motion with delays naturally emerge in the analysis of complex biological control systems which are organized around biochemically mediated feedback interactions. We study the properties of a Mackey-Glass-type nonlinear map with delay -- the deterministic part of the stochastic cerebral blood flow map (CBFM) recently introduced to elucidate the scaling properties of cerebral hemodynamics. We point out the existence of deterministic and nondeterministic subspaces in the reconstructed phase space of delay-difference equations and discuss the problem of detection of nonlinearities in time series generated by such dynamical systems.

nlin.CD↗

arXiv2003

Wavelet analysis of epileptic spikes

Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous, pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.

physics.bio-ph↗

arXiv2003

Fractal Rigidity in Migraine

We study the middle cerebral artery blood flow velocity (MCAfv) in humans using transcranial Doppler ultrasonography (TCD). Scaling properties of time series of the axial flow velocity averaged over a cardiac beat interval may be characterized by two exponents. The short time scaling exponent (STSE) determines the statistical properties of fluctuations of blood flow velocities in short-time intervals while the Hurst exponent describes the long-term fractal properties. In many migraineurs the value of the STSE is significantly reduced and may approach that of the Hurst exponent. This change in dynamical properties reflects the significant loss of short-term adaptability and the overall hyperexcitability of the underlying cerebral blood flow control system. We call this effect fractal rigidity.

physics.bio-ph↗

arXiv2002

The Loss of Multifractality in Migraines

We study the middle cerebral artery blood flow velocity (MCAfv) in humans using transcranial Doppler ultrasonography (TCD). The time series of the axial flow velocity averaged over a cardiac beat interval is found to exhibit clear multifractal properties for healthy subjects. We observe a loss of multifractality for subjects with migraine.

physics.bio-ph↗