1,797 research outputs found
Discovering a junction tree behind a Markov network by a greedy algorithm
In an earlier paper we introduced a special kind of k-width junction tree,
called k-th order t-cherry junction tree in order to approximate a joint
probability distribution. The approximation is the best if the Kullback-Leibler
divergence between the true joint probability distribution and the
approximating one is minimal. Finding the best approximating k-width junction
tree is NP-complete if k>2. In our earlier paper we also proved that the best
approximating k-width junction tree can be embedded into a k-th order t-cherry
junction tree. We introduce a greedy algorithm resulting very good
approximations in reasonable computing time.
In this paper we prove that if the Markov network underlying fullfills some
requirements then our greedy algorithm is able to find the true probability
distribution or its best approximation in the family of the k-th order t-cherry
tree probability distributions. Our algorithm uses just the k-th order marginal
probability distributions as input.
We compare the results of the greedy algorithm proposed in this paper with
the greedy algorithm proposed by Malvestuto in 1991.Comment: The paper was presented at VOCAL 2010 in Veszprem, Hungar
Defecting or not defecting: how to "read" human behavior during cooperative games by EEG measurements
Understanding the neural mechanisms responsible for human social interactions
is difficult, since the brain activities of two or more individuals have to be
examined simultaneously and correlated with the observed social patterns. We
introduce the concept of hyper-brain network, a connectivity pattern
representing at once the information flow among the cortical regions of a
single brain as well as the relations among the areas of two distinct brains.
Graph analysis of hyper-brain networks constructed from the EEG scanning of 26
couples of individuals playing the Iterated Prisoner's Dilemma reveals the
possibility to predict non-cooperative interactions during the decision-making
phase. The hyper-brain networks of two-defector couples have significantly less
inter-brain links and overall higher modularity - i.e. the tendency to form two
separate subgraphs - than couples playing cooperative or tit-for-tat
strategies. The decision to defect can be "read" in advance by evaluating the
changes of connectivity pattern in the hyper-brain network
Diminution of Voltage Threshold Plays a Key Role in Determining Recruitment of Oculomotor Nucleus Motoneurons during Postnatal Development
The size principle dictates the orderly recruitment of motoneurons (Mns). This principle assumes that Mns of different sizes have a similar voltage threshold, cell size being the crucial property in determining neuronal recruitment. Thus, smaller neurons have higher membrane resistance and require a lower depolarizing current to reach spike threshold. However, the cell size contribution to recruitment in Mns during postnatal development remains unknown. To investigate this subject, rat oculomotor nucleus Mns were intracellularly labeled and their electrophysiological properties recorded in a brain slice preparation. Mns were divided into 2 age groups: neonatal (1–7 postnatal days, n = 14) and adult (20–30 postnatal days, n = 10). The increase in size of Mns led to a decrease in input resistance with a strong linear relationship in both age groups. A well-fitted inverse correlation was also found between input resistance and rheobase in both age groups. However, input resistance versus rheobase did not correlate when data from neonatal and adult Mns were combined in a single group. This lack of correlation is due to the fact that decrease in input resistance of developing Mns did not lead to an increase in rheobase. Indeed, a diminution in rheobase was found, and it was accompanied by an unexpected decrease in voltage threshold. Additionally, the decrease in rheobase co-varied with decrease in voltage threshold in developing Mns. These data support that the size principle governs the recruitment order in neonatal Mns and is maintained in adult Mns of the oculomotor nucleus; but during postnatal development the crucial property in determining recruitment order in these Mns was not the modifications of cell size-input resistance but of voltage threshold
Effect of Long-Term Hormone Therapy on Telomere Length in Postmenopausal Women
Telomeres undergo attrition with each cell division, and telomere length is associated with age-related diseases and mortality in the elderly. Estrogen can influence the attrition of telomeres by diverse mechanisms. This is a retrospective case control study that investigated the influence of long-term hormone therapy (HT) on telomere length in postmenopausal women. We recruited 130 postmenopausal women from 55 to 69 years of age for this study, and divided them into two groups. The first group included 65 women who had been on estrogen and progesterone therapy for more than five years (HT group). The other group was composed of 65 women matched in age to the HT group who had never had HT (non-HT group). The relative ratios of telomere length of study subjects to a reference DNA from a healthy young female were measured using quantitative PCR. Plasma levels of lipid profiles, total antioxidant status (TAS), C-reactive proteins (CRP), fasting glucose levels, and estradiol levels were measured. Age at menopause, vitamin use, and exercise, alcohol, and cigarette smoking histories were also assessed in a questionnaire. Mean duration (± SD) of HT was 8.4 ± 2.3 years. Prevalence of vitamin use and regular exercise were higher in the HT group than in the non-HT group (p<0.01). Relative telomere length ratios in the HT group were significantly greater than those in the non-HT group (p<0.01). HT was significantly correlated with the relative telomere length ratio in multivariate analysis when potential confounding variables were controlled for (p<0.05). In conclusion, telomere lengths were longer in postmenopausal women who had a history of long-term HT than in postmenopausal women without HT. Long-term HT in postmenopausal women may alleviate telomere attrition
Preclinical models of endometriosis and interstitial cystitis/bladder pain syndrome: an Innovative Medicines Initiative-PainCare initiative to improve their value for translational research in pelvic pain
Sex matters during adolescence: Testosterone-related cortical thickness maturation differs between boys and girls
Age-related changes in cortical thickness have been observed during adolescence, including thinning in frontal and parietal cortices, and thickening in the lateral temporal lobes. Studies have shown sex differences in hormone-related brain maturation when boys and girls are age-matched, however, because girls mature 1-2 years earlier than boys, these sex differences could be confounded by pubertal maturation. To address puberty effects directly, this study assessed sex differences in testosterone-related cortical maturation by studying 85 boys and girls in a narrow age range and matched on sexual maturity. We expected that testosterone-by-sex interactions on cortical thickness would be observed in brain regions known from the animal literature to be high in androgen receptors. We found sex differences in associations between circulating testosterone and thickness in left inferior parietal lobule, middle temporal gyrus, calcarine sulcus, and right lingual gyrus, all regions known to be high in androgen receptors. Visual areas increased with testosterone in boys, but decreased in girls. All other regions were more impacted by testosterone levels in girls than boys. The regional pattern of sex-by-testosterone interactions may have implications for understanding sex differences in behavior and adolescent-onset neuropsychiatric disorders. © 2012 Bramen et al
WWOX protein expression varies among ovarian carcinoma histotypes and correlates with less favorable outcome
BACKGROUND: The putative tumor suppressor WWOX gene spans the common chromosomal fragile site 16D (FRA16D) at chromosome area 16q23.3-24.1. This region is a frequent target for loss of heterozygosity and chromosomal rearrangement in ovarian, breast, hepatocellular, prostate carcinomas and other neoplasias. The goal of these studies was to evaluate WWOX protein expression levels in ovarian carcinomas to determine if they correlated with clinico-pathological parameters, thus providing additional support for WWOX functioning as a tumor suppressor. METHODS: We performed WWOX protein expression analyses by means of immunobloting and immunohistochemistry on normal ovaries and specific human ovarian carcinoma Tissue Microarrays (n = 444). Univariate analysis of clinical-pathological parameters based on WWOX staining was determined by χ(2 )test with Yates' correction. The basic significance level was fixed at p < 0.05. RESULTS: Immunoblotting analysis from normal ovarian samples demonstrated consistently strong WWOX expression while 37% ovarian carcinomas showed reduced or undetectable WWOX protein expression levels. The immunohistochemistry of normal human ovarian tissue sections confirmed strong WWOX expression in ovarian surface epithelial cells and in epithelial inclusion cysts within the cortex. Out of 444 ovarian carcinoma samples analyzed 30% of tumors showed lack of or barely detectable WWOX expression. The remaining ovarian carcinomas (70%) stained moderately to strongly positive for this protein. The two histotypes showing significant loss of WWOX expression were of the Mucinous (70%) and Clear Cell (42%) types. Reduced WWOX expression demonstrated a significant association with clinical Stage IV (FIGO) (p = 0.007), negative Progesterone Receptor (PR) status (p = 0.008) and shorter overall survival (p = 0.03). CONCLUSION: These data indicate that WWOX protein expression is highly variable among ovarian carcinoma histotypes. It was also observed that subsets of ovarian tumors demonstrated loss of WWOX expression and is potentially associated with patient outcome
The dynamics of neural fields on bounded domains: an interface approach for Dirichlet boundary conditions
Continuum neural field equations model the large scale spatio-temporal dynamics of interacting neurons on a cortical surface. They have been extensively studied, both analytically and numerically, on bounded as well as unbounded domains. Neural field models do not require the specification of boundary conditions. Relatively little attention has been paid to the imposition of neural activity on the boundary, or to its role in inducing patterned states. Here we redress this imbalance by studying neural field models of Amari type (posed on one- and two-dimensional bounded domains) with Dirichlet boundary conditions. The Amari model has a Heaviside nonlinearity that allows for a description of localised solutions of the neural field with an interface dynamics. We show how to generalise this reduced but exact description by deriving a normal velocity rule for an interface that encapsulates boundary effects. The linear stability analysis of localised states in the interface dynamics is used to understand how spatially extended patterns may develop in the absence and presence of boundary conditions. Theoretical results for pattern formation are shown to be in excellent agreement with simulations of the full neural field model. Furthermore, a numerical scheme for the interface dynamics is introduced and used to probe the way in which a Dirichlet boundary condition can limit the growth of labyrinthine structures
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Population based models of cortical drug response: insights from anaesthesia
A great explanatory gap lies between the molecular pharmacology of psychoactive agents and the neurophysiological changes they induce, as recorded by neuroimaging modalities. Causally relating the cellular actions of psychoactive compounds to their influence on population activity is experimentally challenging. Recent developments in the dynamical modelling of neural tissue have attempted to span this explanatory gap between microscopic targets and their macroscopic neurophysiological effects via a range of biologically plausible dynamical models of cortical tissue. Such theoretical models allow exploration of neural dynamics, in particular their modification by drug action. The ability to theoretically bridge scales is due to a biologically plausible averaging of cortical tissue properties. In the resulting macroscopic neural field, individual neurons need not be explicitly represented (as in neural networks). The following paper aims to provide a non-technical introduction to the mean field population modelling of drug action and its recent successes in modelling anaesthesia
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