Data-Driven Network Dynamical Model of Rat Brains During Acute Ictogenesis.

Epilepsy is one of the most common neurological disorders worldwide. Recent findings suggest that the brain is a complex system composed of a network of neurons, and seizure is considered an emergent property resulting from its interactions. Based on this perspective, network physiology has emerged as a promising approach to explore how brain areas coordinate, synchronize and integrate their dynamics, both under perfect health and critical illness conditions.

Entropy: From Thermodynamics to Information Processing.

Entropy is a concept that emerged in the 19th century. It used to be associated with heat harnessed by a thermal machine to perform work during the Industrial Revolution. However, there was an unprecedented scientific revolution in the 20th century due to one of its most essential innovations, i.

Survival analysis of nonperiodic stimulation (NPS) performance.

Electrical Stimulation (ES) of the nervous system is a promising alternative to treat refractory epilepsy. Recent developments in the area have led to a novel method involving a non-standard form of electrical stimulation with randomized inter-pulse intervals called non-periodic stimulation (NPS). Although it is an interesting approach, there is limited statistical proof to confirm its effectiveness.

Dependence between cognitive impairment and metabolic syndrome applied to a Brazilian elderly dataset.

Globally, the proportion of elderly individuals in the population has increased substantially in the last few decades. However, the risk factors that should be managed in advance to ensure a natural process of mental decline due to aging remain unknown. In this study, a dataset consisting of a Brazilian elderly sample was modelled using a Bayesian Network (BN) approach to uncover connections between cognitive performance measures and potential influence factors.

Trunk biomechanics and its association with hip and knee kinematics in patients with and without patellofemoral pain.

Patellofemoral pain (PFP) is a common lower extremity condition observed in sports clinics. Recently, it has been suggested that trunk motion could affect hip and knee biomechanics in the frontal plane. Thus, the purpose of the study was compare trunk kinematics, strength and muscle activation between people with PFP and healthy participants.

Frontal plane biomechanics in males and females with and without patellofemoral pain.

Purpose: The study's purpose was to compare trunk, pelvis, hip, and knee frontal plane biomechanics in males and females with and without patellofemoral pain syndrome (PFPS) during stepping.

Methods: Eighty recreational athletes were equally divided into four groups: female PFPS, female controls, male PFPS, and male controls. Trunk, pelvis, hip, and knee frontal plane kinematics and activation of the gluteus medius were evaluated at 15°, 30°, 45°, and 60° of knee flexion during the downward and upward phases of the stepping task.

Modeling associations between genetic markers using Bayesian networks.

Motivation: Understanding the patterns of association between polymorphisms at different loci in a population (linkage disequilibrium, LD) is of fundamental importance in various genetic studies. Many coefficients were proposed for measuring the degree of LD, but they provide only a static view of the current LD structure. Generative models (GMs) were proposed to go beyond these measures, giving not only a description of the actual LD structure but also a tool to help understanding the process that generated such structure.

Eccentric hip muscle function in females with and without patellofemoral pain syndrome.

Context: Patellofemoral pain syndrome (PFPS) is a common knee condition in athletes. Recently, researchers have indicated that factors proximal to the knee, including hip muscle weakness and motor control impairment, contribute to the development of PFPS. However, no investigators have evaluated eccentric hip muscle function in people with PFPS.

Fuzzy cluster stability analysis with missing values using resampling.

Exploratory data analysis is often necessary to evaluate potential hypotheses for subsequent studies such as grouping the data in clusters. In real data sets the occurrence of incompleteness is very common. We propose a method that tolerates missing values for fuzzy clustering using resampling (bootstrapping) and cluster stability analysis.

The effect of additional strengthening of hip abductor and lateral rotator muscles in patellofemoral pain syndrome: a randomized controlled pilot study.

Objectives: To study the effect of additional strengthening of hip abductor and lateral rotator muscles in a strengthening quadriceps exercise rehabilitation programme for patients with the patellofemoral pain syndrome.

Design: Randomized controlled pilot trial.

Setting: Clinical setting with home programme.

Wavelet time-frequency analysis and least squares support vector machines for the identification of voice disorders.

This work describes a novel algorithm to identify laryngeal pathologies, by the digital analysis of the voice. It is based on Daubechies' discrete wavelet transform (DWT-db), linear prediction coefficients (LPC), and least squares support vector machines (LS-SVM). Wavelets with different support-sizes and three LS-SVM kernels are compared.