Search results for "Autor"

Estimating brain connectivity when few data points are available: Perspectives and limitations

2017

Methods based on the use of multivariate autoregressive modeling (MVAR) have proved to be an accurate and flexible tool for the estimation of brain functional connectivity. The multivariate approach, however, implies the use of a model whose complexity (in terms of number of parameters) increases quadratically with the number of signals included in the problem. This can often lead to an underdetermined problem and to the condition of multicollinearity. The aim of this paper is to introduce and test an approach based on Ridge Regression combined with a modified version of the statistics usually adopted for these methods, to broaden the estimation of brain connectivity to those conditions in …

Pre- and post-ictal brain activity characterization using combined source decomposition and connectivity estimation in epileptic children

2019

In this research, the study of functional connectivity between sources of electroencephalogram (EEG) activity assessed for different classes (well before seizure, preictal and post-ictal) was performed. EEG recordings were acquired from 12 subjects with focal epilepsy. Then, ten common spatial patterns (CSP) were obtained for EEG segments describing 95% of Riemannian distance between pairs of classes, followed by estimation of multivariate autoregressive (MVAR) models’ coefficients. The MVAR models were further used to extract coherence as a functional connectivity measures. Our results show that the coherence between CSP sources differs between baseline and pre-ictal segments: it has the l…

Testing different methodologies for Granger causality estimation: A simulation study

2021

Granger causality (GC) is a method for determining whether and how two time series exert causal influences one over the other. As it is easy to implement through vector autoregressive (VAR) models and can be generalized to the multivariate case, GC has spread in many different areas of research such as neuroscience and network physiology. In its basic formulation, the computation of GC involves two different regressions, taking respectively into account the whole past history of the investigated multivariate time series (full model) and the past of all time series except the putatively causal time series (restricted model). However, the restricted model cannot be represented through a finit…

Vector Autoregressive Fractionally Integrated Models to Assess Multiscale Complexity in Cardiovascular and Respiratory Time Series

2020

Cardiovascular variability is the result of the activity of several physiological control mechanisms, which involve different variables and operate across multiple time scales encompassing short term dynamics and long range correlations. This study presents a new approach to assess the multiscale complexity of multivariate time series, based on linear parametric models incorporating autoregressive coefficients and fractional integration. The approach extends to the multivariate case recent works introducing a linear parametric representation of multiscale entropy, and is exploited to assess the complexity of cardiovascular and respiratory time series in healthy subjects studied during postu…

Competid malditos!

1998

Surrogate Data Analysis for Assessing the Significance of the Coherence Function

2004

In cardiovascular variability analysis, the significance of the coupling between two time series is commonly assessed by setting a threshold level in the coherence function. While traditionally used statistical tests consider only the parameters of the adopted estimator, the required zero-coherence level may be affected by some features of the observed series. In this study, three procedures, based on the generation of surrogate series sharing given properties with the original but being structurally uncoupled, were considered: independent identically distributed (IID), Fourier transform (FT), and autoregressive (AR). IID surrogates maintained the distribution of the original series, while …

Brāļu Koenu filmu kinematogrāfiskā stila iezīmes

2015

Šī bakalaura darba mērķis ir noskaidrot kādas ir brāļu Ītana un Džoela Koenu (Ethan and Joel Coen) autoriskās un režisoriskās iezīmes; kas ir tās stila iezīmes, kas atšķir šos brāļus no citiem pasaules slaveniem režisoriem. Brāļi Koeni ir slavens Holivudas režisoru/scenāristu tandēms, kritiķi un fani raksturo šos autorus kā vienus no ietekmīgākajiem šīs paaudzes režisoriem, kuru filmas atšķirās ar izteiktu stilu režijā un naratīvā. Šī darba mērķis ir analizēt Koenu filmas, lai noteiktu šīs stila iezīmes. Pētījuma autors analizēs vairākas populāras Koenu filmas izmantojot semiotisko un naratīva analīzi, lai noteiktu filmu stila iezīmes

Inclusion of Instantaneous Influences in the Spectral Decomposition of Causality: Application to the Control Mechanisms of Heart Rate Variability

2021

Heart rate variability is the result of several physiological regulation mechanisms, including cardiovascular and cardiorespiratory interactions. Since instantaneous influences occurring within the same cardiac beat are commonplace in this regulation, their inclusion is mandatory to get a realistic model of physiological causal interactions. Here we exploit a recently proposed framework for the spectral decomposition of causal influences between autoregressive processes [2] and generalize it by introducing instantaneous couplings in the vector autoregressive model (VAR). We show the effectiveness of the proposed approach on a toy model, and on real data consisting of heart period (RR), syst…

Model-Based Transfer Entropy Analysis of Brain-Body Interactions with Penalized regression techniques

2020

The human body can be seen as a functional network depicting the dynamical interactions between different organ systems. This exchange of information is often evaluated with information-theoretic approaches which comprise the use of vector autoregressive (VAR) and state space (SS) models, normally identified with the Ordinary Least Squares (OLS). However, the number of time series to be included in the model is strictly related to the length of data recorded thus limiting the use of the classical approach. In this work, a new method based on penalized regressions, the so-called LASSO, was compared with OLS on physiological time-series extracted from 18 subjects during different stress condi…

Alternatīvie nodokļu maksāšanas režīmi Latvijā

2021

2021. gada 1. janvārī stājās spēkā jauni grozījumi Mikrouzņēmuma nodokļa likumā, kas paredz būtisku nodokļa likmes celšanu, izmaiņas patentmaksājumos un citos nodokļos, kas ietekmēs uzņēmējdarbības vidi Latvijā un īpaši - mazos uzņēmumus. Maģistra darba mērķis ir izpētīt Latvijas Republikas nodokļu likumdošanā paredzētos alternatīvos nodokļu maksāšanas režīmus; to izmaiņas, kas stājas spēkā ar 01.01.2021., un izvērtēt nodokļu izmaiņu iespējamo ietekmi uz maziem uzņēmumiem, sniegt priekšlikumus Latvijas Republikas nodokļu sistēmas uzlabošanai. Pētījumā tika noskaidrots, ka pēc 2022. gada 1. janvāra izmaiņu stāšanās spēkā Latvijā uzņēmumiem vairs nebūs pieejams neviens alternatīvo nodokļu mak…