Hyperammonemia alters the mismatch negativity in the auditory evoked potential by altering functional connectivity and neurotransmission.

Minimal hepatic encephalopathy (MHE) is a neuropsychiatric syndrome produced by central nervous system dysfunction subsequent to liver disease. Hyperammonemia and inflammation act synergistically to alter neurotransmission, leading to the cognitive and motor alterations in MHE, which are reproduced in rat models of chronic hyperammonemia. Patients with MHE show altered functional connectivity in different neural networks and a reduced response in the cognitive potential mismatch negativity (MMN), which correlates with attention deficits. The mechanisms by which MMN is altered in MHE remain unknown. The objectives of this work are as follows: To assess if rats with chronic hyperammonemia reproduce the reduced response in the MMN found in patients with MHE. Analyze the functional connectivity between the areas (CA1 area of the dorsal hippocampus, prelimbic cortex, primary auditory cortex, and central inferior colliculus) involved in the generation of the MMN and its possible alterations in hyperammonemia. Granger causality analysis has been applied to detect the net flow of information between the population neuronal activities recorded from a local field potential approach. Analyze if altered MMN response in hyperammonemia is associated with alterations in glutamatergic and GABAergic neurotransmission. Extracellular levels of the neurotransmitters and/or membrane expression of their receptors have been analyzed after the tissue isolation of the four target sites. The results show that rats with chronic hyperammonemia show reduced MMN response in hippocampus, mimicking the reduced MMN response of patients with MHE. This is associated with altered functional connectivity between the areas involved in the generation of the MMN. Hyperammonemia also alters membrane expression of glutamate and GABA receptors in hippocampus and reduces the changes in extracellular GABA and glutamate induced by the MMN paradigm of auditory stimulus in hippocampus of control rats. The changes in glutamatergic and GABAergic neurotransmission and in functional connectivity between the brain areas analyzed would contribute to the impairment of the MMN response in rats with hyperammonemia and, likely, also in patients with MHE.

BELM: Bayesian extreme learning machine.

The theory of extreme learning machine (ELM) has become very popular on the last few years. ELM is a new approach for learning the parameters of the hidden layers of a multilayer neural network (as the multilayer perceptron or the radial basis function neural network). Its main advantage is the lower computational cost, which is especially relevant when dealing with many patterns defined in a high-dimensional space. This brief proposes a bayesian approach to ELM, which presents some advantages over other approaches: it allows the introduction of a priori knowledge; obtains the confidence intervals (CIs) without the need of applying methods that are computationally intensive, e.g., bootstrap; and presents high generalization capabilities. Bayesian ELM is benchmarked against classical ELM in several artificial and real datasets that are widely used for the evaluation of machine learning algorithms. Achieved results show that the proposed approach produces a competitive accuracy with some additional advantages, namely, automatic production of CIs, reduction of probability of model overfitting, and use of a priori knowledge.

The use of neural networks for predicting the result of endoscopic treatment for vesico-ureteric reflux.

OBJECTIVE: To create an artificial neural network (ANN) to aid in predicting the results of endoscopic treatment for vesico-ureteric reflux (VUR). MATERIALS AND METHODS: During 1999-2001 we used endoscopic treatment in 261 ureteric units with VUR of all grades and causes. An ANN based on multilayer perceptron architecture was created using an 11 x 6 x 1 structure, taking the following as variables: the cause and grade of VUR, the patient's age and sex, the type of implanted substance and its volume, the number of treatments, the affected ureter, the endoscopic findings, and the type of cystography used. In all, 174 cases were used as training samples for the ANN and 87 to validate it. We calculated the sensitivity, specificity, positive (PPV) and negative predictive values (NPV), and the success rate (%) of the system. RESULTS: In the training group the ANN gave a sensitivity of 86.4%, a specificity of 89.5%, a PPV of 76% and NPV of 94%, with a success rate of 88.6%. In the same training group logistic regression (LR) gave respective values of 68.2%, 58.8%, 39%, 82.7% and 61.4%. In the validation group the respective values for the ANN were 71.4%, 81.6%, 58.8%, 88.6% and 78.9%, and in the same validation group the LR gave 64.4%, 50%, 32.1%, 79.2% and 53.9%. The Wilcoxon test confirmed the independence of both methods (P < 0.001). CONCLUSION: The ANN is an effective tool for assisting the urologist in indicating and applying endoscopic treatments for VUR.