This paper presents a new method to control and guide mobile robots. In this case, to send different commands we have used electrooculography (EOG) techniques, so that, control is made by means of the ocular position (eye displacement into its orbit). A neural network is used to identify the inverse eye model, therefore the saccadic eye movements can be detected and know where user is looking. ...

When we search for a target in a crowded visual scene, we often use the distinguishing features of the target, such as color or shape, to guide our attention and eye movements. To investigate the neural mechanisms of feature-based attention, we simultaneously recorded neural responses in the frontal eye field (FEF) and area V4 while monkeys performed a visual search task. The responses of cells...

Inspired by the recent evolution of deep neural networks (DNNs) in machine learning, we explore their application to PL-related topics. This paper is the first step towards this goal; we propose a proofsynthesis method for the negation-free propositional logic in which we use a DNN to obtain a guide of proof search. The idea is to view the proof-synthesis problem as a translation from a proposi...

The neural "learning rules" governing the induction of plasticity in the cerebellum were analyzed by recording the patterns of neural activity in awake, behaving animals during stimuli that induce a form of cerebellum-dependent learning. We recorded the simple- and complex-spike responses of a broad sample of Purkinje cells in the floccular complex during a number of stimulus conditions that in...

This paper introduces a novel form of parametric synthesis that uses context embeddings produced by the bottleneck layer of a deep neural network to guide the selection of models in a rich-context HMM-based synthesiser. Rich-context synthesis – in which Gaussian distributions estimated from single linguistic contexts seen in the training data are used for synthesis, rather than more conventiona...

introduction: although logbook is a useful tool in learning and assessment of the student, its use in the education of undergraduate dentistry students is not well-established. the present study was conducted to assess the effect of logbook as a study guide and an effective method for assessment of the students in the fixed prosthesis course. methods: this quasi-experimental study was performed...

Discourse parsing is considered as one of the most challenging natural language processing (NLP) tasks. Implicit discourse relation classification is the bottleneck for discourse parsing. Without the guide of explicit discourse connectives, the relation of sentence pairs are very hard to be inferred. This paper proposes a stacking neural network model to solve the classification problem in whic...

In this chapter I will give a overview of the role of time delays in understanding neural systems. The main focus will be on models of neural systems in terms of delay differential equations. Later in this section, I will discuss how such models arise. The goal of the chapter is two-fold: (1) to give the reader an introduction and guide to some methods available for understanding the dynamics o...

This paper introduces an SLD-resolution technique based on deep learning. This technique enables neural networks to learn from old and successful resolution processes and to use learnt experiences to guide new resolution processes. An implementation of this technique is named SLDR-DL. It includes a Prolog library of deep feedforward neural networks and some essential functions of resolution. In...