Neural control of the heart: developmental changes in ionic conductances in mammalian intrinsic cardiac neurons

The expression and properties of ionic channels were investigated in dissociated neurons from neonatal and adult rat intracardiac ganglia. Changes in the hyperpolarization-activated and ATP-sensitive K+ conductances during postnatal development and their role in neuronal excitability were examined. The hyperpolarization-activated nonselective cation current, I-h, was observed in all neurons studied and displayed slow time-dependent rectification. An inwardly rectifying K+ current, I-K(I), was present in a population of neurons from adult but not neonatal rats and was sensitive to block by extracellular Ba2+. Using the perforated-patch recording configuration, an ATP-sensitive K+ (K-ATP) conductance was identified in greater than or equal to 50% of intracardiac neurons from adult rats. Levcromakalim evoked membrane hyperpolarization, which was inhibited by the sulphonylurea drugs. glibenclamide and tolbutamide. Exposure to hypoxic conditions also activated a membrane current similar to that induced by levcromakalim and was inhibited by glibenclamide. Changes in the complement of ion channels during postnatal development may underlie observed differences in the function of intracardiac ganglion neurons during maturation. Furthermore, activation of hyperpolarization-activated and KATP channels in mammalian intracardiac neurons may play a role in neural regulation of the mature heart and cardiac function during ischaemia-reperfusion. (C) 2002 Elsevier Science B.V All rights reserved.

Neural control of an autonomous robot

This article aims to apply the concepts associated with artificial neural networks (ANN) in the control of an autonomous robot system that is intended to be used in competitions of robots. The robot was tested in several arbitrary paths in order to verify its effectiveness. The results show that the robot performed the tasks with success. Moreover, in the case of arbitrary paths the ANN control outperforms other methodologies, such as fuzzy logic control (FLC).

Neural control of vascular reactions: impact of emotion and attention.

This study investigated the neural regions involved in blood pressure reactions to negative stimuli and their possible modulation by attention. Twenty-four healthy human subjects (11 females; age = 24.75 ± 2.49 years) participated in an affective perceptual load task that manipulated attention to negative/neutral distractor pictures. fMRI data were collected simultaneously with continuous recording of peripheral arterial blood pressure. A parametric modulation analysis examined the impact of attention and emotion on the relation between neural activation and blood pressure reactivity during the task. When attention was available for processing the distractor pictures, negative pictures resulted in behavioral interference, neural activation in brain regions previously related to emotion, a transient decrease of blood pressure, and a positive correlation between blood pressure response and activation in a network including prefrontal and parietal regions, the amygdala, caudate, and mid-brain. These effects were modulated by attention; behavioral and neural responses to highly negative distractor pictures (compared with neutral pictures) were smaller or diminished, as was the negative blood pressure response when the central task involved high perceptual load. Furthermore, comparing high and low load revealed enhanced activation in frontoparietal regions implicated in attention control. Our results fit theories emphasizing the role of attention in the control of behavioral and neural reactions to irrelevant emotional distracting information. Our findings furthermore extend the function of attention to the control of autonomous reactions associated with negative emotions by showing altered blood pressure reactions to emotional stimuli, the latter being of potential clinical relevance.

A proposed neural control for the trajectory tracking of a nonholonomic mobile robot with disturbances

In this paper, a trajectory tracking control problem for a nonholonomic mobile robot by the integration of a kinematic neural controller (KNC) and a torque neural controller (TNC) is proposed, where both the kinematic and dynamic models contains disturbances. The KNC is a variable structure controller (VSC) based on the sliding mode control theory (SMC), and applied to compensate the kinematic disturbances. The TNC is a inertia-based controller constituted of a dynamic neural controller (DNC) and a robust neural compensator (RNC), and applied to compensate the mobile robot dynamics, and bounded unknown disturbances. Stability analysis with basis on Lyapunov method and simulations results are provided to show the effectiveness of the proposed approach. © 2012 Springer-Verlag.

INFLUENCE OF 24-HOUR SLEEP DEPRIVATION ON CARDIOVASCULAR AND NEURAL CONTROL AT REST AND DURING ACUTE STRESS IN HUMANS

Recent epidemiological studies report a consistent association between short sleep and incidence of hypertension, as well as short sleep and cardiovascular disease-related mortality. While the association between short sleep and hypertension appears to be stronger in women than men, the mechanisms underlying the relations between sleep deprivation, stress, risks of cardiovascular diseases, and sex remain unclear. We conducted two studies to investigate the underlying neural mechanisms of these relations. In study 1, we examined sympathetic neural and blood pressure responses to experimentally-induced sleep deprivation in men and women. We further investigated the influence of sleep deprivation on cardiovascular reactivity to acute stress. In study 2, we examined the neural and cardiovascular function throughout the ovarian cycle in sleep deprived women. Twenty-eight young healthy subjects (14men and 14 women) were tested twice in study 1, once after normal sleep (NS) and once after 24-h total sleep deprivation (TSD). We measured the blood pressure, heart rate (HR), muscle sympathetic nerve activity (MSNA) and forearm blood flow (FBF) during 10min baseline, 5min of mental stress (MS) and 2 min cold pressor test (CPT). We demonstrated that TSD increased resting arterial blood pressure to a similar extent in both men and women, but MSNA decreased only in men following TSD. This MSNA response was associated with altered baroreflex function in women and divergent testosterone responses to TSD between men and women. Regarding TSD and cardiovascular reactivity, TSD elicited augmented HR reactivity and delayed recovery during both MS and CPT in men and women, and responses between sexes were not statistically different. Fourteen young healthy women participated in study 2. Subjects were tested twice, once during their early follicular (EF) phase after TSD, once during their mid-luteal (ML) phase after TSD. Blood pressure, HR, MSNA, and FBF were recorded during 10min baseline, 5 min MS, and 2 min CPT. We observed an augmented resting supine blood pressure during EF compared to ML in sleep deprived women. In contrast, resting MSNA, as well as cardiovascular responses to stressors, were similar between EF and ML after TSD. In conclusion, we observed sex differences in MSNA responses to TSD that demonstrate reductions of MSNA in men, but not women. TSD elicited augmented HR reactivity and delayed HR recovery to acute stressors similarly in men and women. We also reported an augmented supine blood pressure during EF compared to ML in sleep deprived women. These novel findings provide new and valuable mechanistic insight regarding the complex and poorly understood relations among sleep deprivation, sex, stress, and risk of cardiovascular disease.

Neural control of a batch distillation

The purpose of the work reported here was to investigate the application of neural control to a common industrial process. The chosen problem was the control of a batch distillation. In the first phase towards deployment, a complex software simulation of the process was controlled. Initially, the plant was modelled with a neural emulator. The neural emulator was used to train a neural controller using the backpropagation through time algorithm. A high accuracy was achieved with the emulator after a large number of training epochs. The controller converged more rapidly, but its performance varied more widely over its operating range. However, the controlled system was relatively robust to changes in ambient conditions.

Neural Control of Chaos and Aplications

Signal processing is an important topic in technological research today. In the areas of nonlinear dynamics search, the endeavor to control or order chaos is an issue that has received increasing attention over the last few years. Increasing interest in neural networks composed of simple processing elements (neurons) has led to widespread use of such networks to control dynamic systems learning. This paper presents backpropagation-based neural network architecture that can be used as a controller to stabilize unsteady periodic orbits. It also presents a neural network-based method for transferring the dynamics among attractors, leading to more efficient system control. The procedure can be applied to every point of the basin, no matter how far away from the attractor they are. Finally, this paper shows how two mixed chaotic signals can be controlled using a backpropagation neural network as a filter to separate and control both signals at the same time. The neural network provides more effective control, overcoming the problems that arise with control feedback methods. Control is more effective because it can be applied to the system at any point, even if it is moving away from the target state, which prevents waiting times. Also control can be applied even if there is little information about the system and remains stable longer even in the presence of random dynamic noise.

Application of multivariable control using artificial neural networks in a debutanizer distillation column

LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

Neural network enhanced self tuning adaptive control application for non-linear control of dynamic systems

The main theme of research of this project concerns the study of neutral networks to control uncertain and non-linear control systems. This involves the control of continuous time, discrete time, hybrid and stochastic systems with input, state or output constraints by ensuring good performances. A great part of this project is devoted to the opening of frontiers between several mathematical and engineering approaches in order to tackle complex but very common non-linear control problems. The objectives are: 1. Design and develop procedures for neutral network enhanced self-tuning adaptive non-linear control systems; 2. To design, as a general procedure, neural network generalised minimum variance self-tuning controller for non-linear dynamic plants (Integration of neural network mapping with generalised minimum variance self-tuning controller strategies); 3. To develop a software package to evaluate control system performances using Matlab, Simulink and Neural Network toolbox. An adaptive control algorithm utilising a recurrent network as a model of a partial unknown non-linear plant with unmeasurable state is proposed. Appropriately, it appears that structured recurrent neural networks can provide conveniently parameterised dynamic models for many non-linear systems for use in adaptive control. Properties of static neural networks, which enabled successful design of stable adaptive control in the state feedback case, are also identified. A survey of the existing results is presented which puts them in a systematic framework showing their relation to classical self-tuning adaptive control application of neural control to a SISO/MIMO control. Simulation results demonstrate that the self-tuning design methods may be practically applicable to a reasonably large class of unknown linear and non-linear dynamic control systems.

Application of multivariable control using artificial neural networks in a debutanizer distillation column

LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

Application of multivariable control using artificial neural networks in a debutanizer distillation column

LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

Control of heart rate during thermoregulation in the heliothermic lizard Pogona barbata: importance of cholinergic and adrenergic mechanisms

During thermo regulation in the bearded dragon Pogona barbata, heart rate when heating is significantly faster than when cooling at any given body temperature (heart rate hysteresis), resulting in faster rates of heating than cooling. However, the mechanisms that control heart rate during heating and cooling are unknown. The aim of this study was to test the hypothesis that changes in cholinergic and adrenergic tone on the heart are responsible for the heart rate hysteresis during heating and cooling in P. barbata. Heating and cooling trials were conducted before and after the administration of atropine, a muscarinic antagonist, and sotalol, a beta-adrenergic antagonist. Cholinergic and beta-adrenergic blockade did not abolish the heart rate hysteresis, as the heart rate during heating was significantly faster than during cooling in all cases. Adrenergic tone was extremely high (92.3%) at the commencement of heating, and decreased to 30.7% at the end of the cooling period. Moreover, in four lizards there was an instantaneous drop in heart rate (up to 15 beats min(-1)) as the heat source was switched off, and this drop in heart rate coincided with either a drop in beta-adrenergic tone or an increase in cholinergic tone. Rates of heating were significantly faster during the cholinergic blockade, and least with a combined cholinergic and beta-adrenergic blockade. The results showed that cholinergic and beta-adrenergic systems are not the only control mechanisms acting on the heart during heating and cooling, but they do have a significant effect on heart rate and on rates of heating and cooling.

Brain glucose sensing and neural regulation of insulin and glucagon secretion.

Glucose homeostasis requires the tight regulation of glucose utilization by liver, muscle and white or brown fat, and glucose production and release in the blood by liver. The major goal of maintaining glycemia at ∼ 5 mM is to ensure a sufficient flux of glucose to the brain, which depends mostly on this nutrient as a source of metabolic energy. This homeostatic process is controlled by hormones, mainly glucagon and insulin, and by autonomic nervous activities that control the metabolic state of liver, muscle and fat tissue but also the secretory activity of the endocrine pancreas. Activation or inhibition of the sympathetic or parasympathetic branches of the autonomic nervous systems are controlled by glucose-excited or glucose-inhibited neurons located at different anatomical sites, mainly in the brainstem and the hypothalamus. Activation of these neurons by hyper- or hypoglycemia represents a critical aspect of the control of glucose homeostasis, and loss of glucose sensing by these cells as well as by pancreatic β-cells is a hallmark of type 2 diabetes. In this article, aspects of the brain-endocrine pancreas axis are reviewed, highlighting the importance of central glucose sensing in the control of counterregulation to hypoglycemia but also mentioning the role of the neural control in β-cell mass and function. Overall, the conclusions of these studies is that impaired glucose homeostasis, such as associated with type 2 diabetes, but also defective counterregulation to hypoglycemia, may be caused by initial defects in glucose sensing.

Prosthesis grasp reflex via peripheral nerve control: an in vitro study

Here we present an economical and versatile platform for developing motor control and sensory feedback of a prosthetic hand via in vitro mammalian peripheral nerve activity. In this study, closed-loop control of the grasp function of the prosthetic hand was achieved by stimulation of a peripheral nerve preparation in response to slip sensor data from a robotic hand, forming a rudimentary reflex action. The single degree of freedom grasp was triggered by single unit activity from motor and sensory fibers as a result of stimulation. The work presented here provides a novel, reproducible, economic, and robust platform for experimenting with neural control of prosthetic devices before attempting in vivo implementation.

An adaptive system based on artificial neural networks for NPK fluid fertilizer application

The application process of fluid fertilizers through variable rates implemented by classical techniques with feedback and conventional equipments can be inefficient or unstable. This paper proposes an open-loop control system based on artificial neural network of the type multilayer perceptron for the identification and control of the fertilizer flow rate. The network training is made by the algorithm of Levenberg-Marquardt with training data obtained from measurements. Preliminary results indicate a fast, stable and low cost control system for precision fanning. Copyright (C) 2000 IFAC.