0000000000751585
AUTHOR
Jose R. Magdalena
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 rep…
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…
Application of Neural Networks in Animal Science
Stock breeding has been one of the most important sources of food and labour throughout human history. Every advance in this field has always led to important and beneficial impacts on human society. These innovations have mainly taken place in machines or genetics, but data analysis has been somewhat ignored. Most of the published works in data analysis use linear models, and there are few works in the literature that use non-linear methods for data processing in stock breeding where these methods have proven to obtain better results and performance than linear, classical methods. This chapter demonstrates the use of non-linear methods by presenting two practical applications: milk yield p…