Métodos numéricos para resolução de equações diferenciais ordinárias lineares baseados em interpolação por spline

In this work we have elaborated a spline-based method of solution of inicial value problems involving ordinary differential equations, with emphasis on linear equations. The method can be seen as an alternative for the traditional solvers such as Runge-Kutta, and avoids root calculations in the linear time invariant case. The method is then applied on a central problem of control theory, namely, the step response problem for linear EDOs with possibly varying coefficients, where root calculations do not apply. We have implemented an efficient algorithm which uses exclusively matrix-vector operations. The working interval (till the settling time) was determined through a calculation of the least stable mode using a modified power method. Several variants of the method have been compared by simulation. For general linear problems with fine grid, the proposed method compares favorably with the Euler method. In the time invariant case, where the alternative is root calculation, we have indications that the proposed method is competitive for equations of sifficiently high order.

Detecting cell assemblies in large neuronal populations

Recent progress in the technology for single unit recordings has given the neuroscientific community theopportunity to record the spiking activity of large neuronal populations. At the same pace, statistical andmathematical tools were developed to deal with high-dimensional datasets typical of such recordings.A major line of research investigates the functional role of subsets of neurons with significant co-firingbehavior: the Hebbian cell assemblies. Here we review three linear methods for the detection of cellassemblies in large neuronal populations that rely on principal and independent component analysis.Based on their performance in spike train simulations, we propose a modified framework that incorpo-rates multiple features of these previous methods. We apply the new framework to actual single unitrecordings and show the existence of cell assemblies in the rat hippocampus, which typically oscillate attheta frequencies and couple to different phases of the underlying field rhythm

Distúrbios do sono em pacientes com transtorno depressivo

To evaluate sleep disorder complaints in outpatients with depressive disorder from a general hospital. Methods: An observational, cross-sectional study was carried out with a study sample composed of 70 patients (44 women and 26 men) with diagnosis of depressive disorder, according to the DSM-IV criteria. The patients were interviewed and evaluated by the Identification Questionnaire, the Sleep Habits Questionnaire and the Beck Depression Inventory (BDI). Results: In this study, 50 (71.3%) patients had recurrence of sleep disorder complaints. Mean BDI score was 35.83+8.85, with significant differences between patients with (38.50+8.70) and without (29.60+7.80) recurrence (p<0.05) and among patients with 1, 2, 3 and >3 episodes (p<0.05). In this study, 49 (70%) patients had insomnia and 21 (30%) had subjective excessive sleepiness. Significant differences were observed between the mean duration in months of the sleep disorders (7.16+2.10) and the depressive disorder (6.12+1.90) (p<0.05). Discussion: In the study sample, recurrence of sleep disorder complaints was high and significantly associated with severe depression. Insomnia was prevalent and the mean duration of sleep disorders was higher in relation to depressive disorder

Interações físicas e psicossociais em mulheres com fibromialgia

Fibromyalgia (FM) is a non-inflammatory rheumatic syndrome of unknown etiology, with symptoms of diffuse musculoskeletal pain and presence of specific anatomic sites called tender points. The symptoms are often associated with fatigue, sleep disturbances, morning stiffness, alterations in pain perception, anxiety and depression. Fibromyalgia exhibits a correlation between physical and behavioral symptoms, which have a negative influence on the quality of life of patients. Emotional skills are important factors since they are related to subjective well-being, personal productivity, social interaction and interpersonal relationships. We aim to describe the physical and psychosocial interactions in women with FM, showing the association between perceived social support and affect with symptoms of pain, functionality and mood. We will also describe a body representation of pain in women with FM. Data were collected over 3 years and the sample size ranged between studies. This is an exploratory cross-sectional study conducted with a convenience sample of 63 women with FM and 42 healthy women as a control group (CT), aged 20-76 years, recruited through spontaneous demand at Onofre Lopes University Hospital (HUOL) and the Clinical School of Physiotherapy of Universidade Potiguar (UNP). The Fibromyalgia Impact Questionnaire (FIQ), Beck Depression Inventory (BDI), Social Support Scale (MOS), Hamilton Anxiety Scale and Scale of Positive and Negative Affect Schedule (PANAS), in addition to pressure algometry were used. For data analysis, we used parametric and non-parametric tests and a general linear model with adjustment variables and analysis of variance. A significant difference was found between pain threshold and tolerance, functionality, depression, anxiety, social support, and positive and negative affect between the groups. Affective states and social support were associated with anxiety, depression and functionality. A body was drawn representing pain with higher incidences in trapeze, supraspinatus and second ribs. The reason for studying sensory aspects, affective behavior and social support in FM patients opens perspectives for scientific and clinical research of this syndrome. Women with chronic pain such as FM appear to have altered mood states, less social support and affective dysfunctions, influencing the other symptoms of the syndrome

Detecting cell assemblies in large neuronal populations

Recent progress in the technology for single unit recordings has given the neuroscientific community theopportunity to record the spiking activity of large neuronal populations. At the same pace, statistical andmathematical tools were developed to deal with high-dimensional datasets typical of such recordings.A major line of research investigates the functional role of subsets of neurons with significant co-firingbehavior: the Hebbian cell assemblies. Here we review three linear methods for the detection of cellassemblies in large neuronal populations that rely on principal and independent component analysis.Based on their performance in spike train simulations, we propose a modified framework that incorpo-rates multiple features of these previous methods. We apply the new framework to actual single unitrecordings and show the existence of cell assemblies in the rat hippocampus, which typically oscillate attheta frequencies and couple to different phases of the underlying field rhythm