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Background: Most cases of toe walking in children are idiopathic. We used pathology-specific neuromusculoskeletal predictive simulations to identify potential underlying neural and muscular mechanisms contributing to idiopathic toe walking. Methods: A musculotendon contracture was added to the ankle plantarflexors of a generic musculoskeletal model to represent a pathology-specific contracture model, matching the reduced ankle dorsiflexion range-of-motion in a cohort of children with idiopathic toe walking. This model was employed in a forward dynamic simulation controlled by reflexes and supraspinal drive, governed by a multi-objective cost function to predict gait patterns with the contracture model. We validated the predicted gait using experimental gait data from children with idiopathic toe walking with ankle contracture, by calculating the root mean square errors averaged over all biomechanical variables. Findings: A predictive simulation with the pathology-specific model with contracture approached experimental ITW data (root mean square error = 1.37SD). Gastrocnemius activation was doubled from typical gait simulations, but lacked a peak in early stance as present in electromyography. This synthesised idiopathic toe walking was more costly for all cost function criteria than typical gait simulation. Also, it employed a different neural control strategy, with increased length- and velocity-based reflex gains to the plantarflexors in early stance and swing than typical gait simulations. Interpretation: The simulations provide insights into how a musculotendon contracture combined with altered neural control could contribute to idiopathic toe walking. Insights into these neuromuscular mechanisms could guide future computational and experimental studies to gain improved insight into the cause of idiopathic toe walking., Biomechatronics & Human-Machine Control

The inspiratory muscles, such as the diaphragm, receive descending neural inputs from the medulla and sensorimotor cortex. In response to increased respiratory demand or in the presence of respiratory impairment, the neural control of the inspiratory muscles adapts to meet ventilatory requirements. This thesis addresses the neural control of inspiration in health, healthy ageing and chronic tetraplegia. In the first two chapters of results, single motor unit electromyographic recordings of the costal diaphragm were performed in healthy people aged 23-80 years (Chapter 2) and in chronic tetraplegia (Chapter 3) during quiet breathing. The findings show that diaphragm motor unit discharge frequencies during quiet breathing do not change in healthy ageing but are increased in chronic tetraplegia. Diaphragm motor unit action potentials are larger in size in both healthy ageing and chronic tetraplegia, although more so in the latter group, which suggests motor unit remodelling. The difference between the two groups reflects the greater severity of respiratory motor impairment in chronic tetraplegia. Furthermore, ageing-related changes in diaphragm motor unit size were observed in middle age. The sensorimotor cortex is recruited during quiet breathing in certain conditions of respiratory impairment but not in healthy, younger people. In Chapter 4, electroencephalographic recordings were made from participants with chronic tetraplegia during quiet breathing. The results show that the sensorimotor cortex is not recruited which suggests that other sources of neural control, likely the medulla, generate the increase in diaphragm motor unit output during quiet breathing. In Chapter 5, electromyographic recordings were made from healthy people to investigate the simultaneous control of the costal and crural portions of the diaphragm with increased drive to breathe. Here, regardless of whether the source of increased drive is voluntary or involuntary, the costal portion of the di

Few studies have investigated the kinematic aspects of the body centre of mass motion, that is, its three-dimensional path during strides and their changes with child development. This study aimed to describe the three-dimensional path of the centre of mass in children while walking in order to disentangle the effect of age from that of absolute forward speed and body size and to define preliminary pediatric normative values. The three-dimensional path of the centre of mass during walking was compared across healthy children 5-6- years (n = 6), 7-8 years (n = 6), 9-10 years (n = 5), and 11-13 years of age (n = 5) and healthy adults (23-48 years, n = 6). Participants walked on a force-sensing treadmill at various speeds, and height normalization of speed was conducted with the dimensionless Froude number. The total length and maximal lateral, vertical, and forward displacements of the centre of mass path were calculated from the ground reaction forces during complete strides and were scaled to the participant's height. The centre of mass path showed a curved figure-of-eight shape. Once adjusted for speed and participants' height, as age increased, there was a decrease in the three-dimensional parameters and in the lateral displacement, with values approaching those of adults. At each step, lateral redirection of the centre of mass requires brisk transient muscle power output. The base of support becomes relatively narrower with increasing age. Skilled shortening of the lateral displacement of the centre of mass may therefore decrease the risk of falling sideways. The three-dimensional path of the centre of mass may represent maturation of neural control of gait during growth.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially w

Few studies have investigated the kinematic aspects of the body centre of mass motion, that is, its three-dimensional path during strides and their changes with child development. This study aimed to describe the three-dimensional path of the centre of mass in children while walking in order to disentangle the effect of age from that of absolute forward speed and body size and to define preliminary pediatric normative values. The three-dimensional path of the centre of mass during walking was compared across healthy children 5-6- years (n = 6), 7-8 years (n = 6), 9-10 years (n = 5), and 11-13 years of age (n = 5) and healthy adults (23-48 years, n = 6). Participants walked on a force-sensing treadmill at various speeds, and height normalization of speed was conducted with the dimensionless Froude number. The total length and maximal lateral, vertical, and forward displacements of the centre of mass path were calculated from the ground reaction forces during complete strides and were scaled to the participant's height. The centre of mass path showed a curved figure-of-eight shape. Once adjusted for speed and participants' height, as age increased, there was a decrease in the three-dimensional parameters and in the lateral displacement, with values approaching those of adults. At each step, lateral redirection of the centre of mass requires brisk transient muscle power output. The base of support becomes relatively narrower with increasing age. Skilled shortening of the lateral displacement of the centre of mass may therefore decrease the risk of falling sideways. The three-dimensional path of the centre of mass may represent maturation of neural control of gait during growth.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially w

Investigation into regulation of heart rate (HR) and blood pressure (BP) is addressed under the phrase "neural control of the circulation during exercise." In this chapter, regulation of HR and BP is reviewed both during static and dynamic exercise. An effort is made to evaluate the importance of the central nervous system (central command) versus influence from the exercising muscles (the exercise pressor reflex). The need to obtain more flow-related variables is also emphasized.

Single finger force tasks lead to unintended activation of the non-instructed fingers, commonly referred to as enslaving. Both neural and mechanical factors have been associated with this absence of finger individuality. This study investigates the amplitude modulation of both intrinsic and extrinsic finger muscles during single finger isometric force tasks. Twelve participants performed single finger flexion presses at 20% of maximum voluntary contraction, while simultaneously the electromyographic activity of several intrinsic and extrinsic muscles associated with all four fingers was recorded using 8 electrode pairs in the hand and two 30-electrode grids on the lower arm. The forces exerted by each of the fingers, in both flexion and extension direction, were recorded with individual force sensors. This study shows distinct activation patterns in intrinsic and extrinsic hand muscles. Intrinsic muscles exhibited individuation, where the agonistic and antagonistic muscles associated with the instructed fingers showed the highest activation. This activation in both agonistic and antagonistic muscles appears to facilitate finger stabilisation during the isometric force task. Extrinsic muscles show an activation independent from instructed finger in both agonistic and antagonistic muscles, which appears to be associated with stabilisation of the wrist, with an additional finger-dependent modulation only present in the agonistic extrinsic muscles. These results indicate distinct muscle patterns in intrinsic and extrinsic hand muscles during single finger isometric force pressing. We conclude that the finger specific activation of intrinsic muscles is not sufficient to fully counteract enslaving caused by the broad activation of the extrinsic muscles.

The central nervous system in humans continuously controls the speed of walking by modulating muscle activities. The underlying mechanisms of this control process are not well understood. Recent studies have probed the neural control of walking using sensory and mechanical perturbations. It has been suggested that transient responses to perturbations show patterns in the modulation of muscle activations not previously observed. This dissertation aims to systematically investigate differences in modulations of muscle activations between transient responses and steady-state walking. Three studies were designed to explore these modulations using visual and mechanical perturbations. The first study compared the qualitative patterns from transient responses to visual perturbations to those observed during steady-state walking. Small changes in the average muscle activations between two steady-state speeds were compared to small transient changes due to perturbations. We demonstrated that the decrease in the plantarflexor activity during transient responses that potentially contributed to an increase in speed was unique to these responses and not reproducible in steady-state walking conditions. The second study quantified the effects of average walking speed on transient responses to visual perturbations and compared these effects to steady-state walking conditions. A scaling effect on the amplitude of responses was shown across different treadmill speeds. Finally, in the last study, we explored characteristics of transient responses to mechanical perturbations of the treadmill. We examined the effects of perturbations at two different amplitudes on both kinematics and muscle activations. The responses of the neurofeedback to kinematic deviations were quantified and it was shown that the local limit cycle approximation was reasonable to describe the system. Together these studies shed light on how modulations of muscle activity are utilized by the nervous system to regula

Single finger force tasks lead to unintended activation of the non-instructed fingers, commonly referred to as enslaving. Both neural and mechanical factors have been associated with this absence of finger individuality. This study investigates the amplitude modulation of both intrinsic and extrinsic finger muscles during single finger isometric force tasks. Twelve participants performed single finger flexion presses at 20% of maximum voluntary contraction, while simultaneously the electromyographic activity of several intrinsic and extrinsic muscles associated with all four fingers was recorded using 8 electrode pairs in the hand and two 30-electrode grids on the lower arm. The forces exerted by each of the fingers, in both flexion and extension direction, were recorded with individual force sensors. This study shows distinct activation patterns in intrinsic and extrinsic hand muscles. Intrinsic muscles exhibited individuation, where the agonistic and antagonistic muscles associated with the instructed fingers showed the highest activation. This activation in both agonistic and antagonistic muscles appears to facilitate finger stabilisation during the isometric force task. Extrinsic muscles show an activation independent from instructed finger in both agonistic and antagonistic muscles, which appears to be associated with stabilisation of the wrist, with an additional finger-dependent modulation only present in the agonistic extrinsic muscles. These results indicate distinct muscle patterns in intrinsic and extrinsic hand muscles during single finger isometric force pressing. We conclude that the finger specific activation of intrinsic muscles is not sufficient to fully counteract enslaving caused by the broad activation of the extrinsic muscles.

Reinforcement learning (RL)-based brain machine interfaces (BMIs) enable the user to learn from the environment through interactions to complete the task without desired signals, which is promising for clinical applications. Previous studies exploited Q-learning techniques to discriminate neural states into simple directional actions providing the trial initial timing. However, the movements in BMI applications can be quite complicated, and the action timing explicitly shows the intention when to move. The rich actions and the corresponding neural states form a large state-action space, imposing generalization difficulty on Q-learning. In this paper, we propose to adopt attention-gated reinforcement learning (AGREL) as a new learning scheme for BMIs to adaptively decode high-dimensional neural activities into seven distinct movements (directional moves, holdings and resting) due to the efficient weight-updating. We apply AGREL on neural data recorded from M1 of a monkey to directly predict a seven-action set in a time sequence to reconstruct the trajectory of a center-out task. Compared to Q-learning techniques, AGREL could improve the target acquisition rate to 90.16% in average with faster convergence and more stability to follow neural activity over multiple days, indicating the potential to achieve better online decoding performance for more complicated BMI tasks. © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.

Raising of problem. Rotary kiln clinkers are widely used in many industrial plants for the production of cement. Clinker manufacturing process requires the large consumption of energy. Getting the quality of final product is possible by controlling and regulating the set of process parameters. It largely depends on the professional level of the operator and possible unmistakable solutions. Many industrial plants in which operation are the rotary kilns are still using outdated equipment that does not match to modern requirements of process control clinker. The question of improving the quality indicators is still extremely important. To improve the process of clinker burning is possible through the using of control systems with fuzzy logic controllers or modern neyrosystem control.Analysis of the literature. Currently, there is a lot of literature and scientific works in the field of automated control systems of the clinker burning process. Significant contribution to the development of control systems and intensify the process of firing have made by such scholars: V. K. Сlass [4], P. V. Besedin [1], M. A. Verdiyan [8]. In the works of these scholars are presented methods for creating control systems clinker, improving quality indicators in relation to one of the options or providing use of fuzzy logic control and neural network with one control circuit for the burning process. The analysis of the literature demonstrates that the neural control systems are the promising way to improving the clinker burning process and require further development.The purpose and objectives. The aim of the study is to find opportunities to improve the quality of the firing of the finished material (clinker) while reducing power consumption, improving the work conditions of the operator at the plant, reducing the total time of the clinker burning through the creation of automated control system with neural controller, based on the reference model and its immediate setting. Conclusions., Постановка проблемы. Вращающиеся печи для обжига клинкера широко используются на многих промышленных предприятиях по производству цемента. Процесс изготовления клинкера требует больших затрат энергии. Получение конечного продукта с высокими качественными показателями возможно путем контроля и регулирования заданных технологических параметров. В значительной степени это зависит от профессионального уровня оператора и возможного принятия им безошибочных решений. Многие предприятия, в эксплуатации которых находятся вращающиеся печи, все еще используют устаревшее оборудование, которое не соответствует современным требованиям управления технологическими процессами обжига клинкера. Вопрос улучшения качественных показателей, все еще, является крайне актуальным. Усовершенствовать технологический процесс обжига клинкера возможно путем применения систем управления с контроллерами нечеткой логики, или современных нейросистем управления.Анализ литературы. На сегодняшний день известно много литературных источников и научных работ в области разработки автоматизированных систем управления процессом обжига клинкера. Значительный вклад в создание систем управления и интенсификации процесса обжига внесли такие ученые: В. К. Класен [4], П. В. Беседин [1], М. А. Вердиян [8]. В работах этих ученых представлены методы создания систем управления обжигом клинкера, улучшающие качественные показатели в отношении одного из параметров или обеспечивающие использование нечеткой логики управления или нейросети с регулировкой одного контура процесса обжига. Анализ литературных источников показывает, что нейронные системы управления являются перспективным направлением совершенствования технологического процесса обжига клинкера и требуют дальнейшего развития.Цель и задачи. Целью исследования является поиск возможных путей улучшения качества обжига готового материала (клинкера) с одновременным снижением энергозатрат, улучшением условий работы оператора на предприятии, снижением общего времени обжига, Постановка проблеми. Обертові печі для випалу клінкеру широко використовуються на багатьох промислових підприємствах із виробництва цементу. Процес виготовлення клінкеру вимагає великих затрат енергії. Отримання кінцевого продукту з високими якісними показниками можливе шляхом контролю і регулювання заданих технологічних параметрів. В значній мірі це залежить від професійного рівня оператора та прийняття ним безпомилкових рішень. Багато підприємств, у яких в експлуатації знаходяться обертові печі, все ще використовують застаріле обладнання, яке не відповідає сучасним вимогам управління технологічними процесами випалу клінкеру. Питання покращення якісних показників, наразі є вкрай актуальним. Удосконалити технологічний процес випалу клінкеру можливо шляхом застосування систем керування з контролерами нечіткої логіки, або сучасних нейросистем керування.Аналіз літератури. На сьогоднішній день відомо багато літературних джерел та наукових праць у галузі розробки автоматизованих систем керування процесом випалу клінкеру. Значний вклад у створення систем керування та інтенсифікації процесу випалу внесли учені: В. К. Класен [4], П.В. Беседин [1], М. А. Вердіян [8]. У роботах цих науковців представлені методи створення систем керування випалом клінкеру, що покращують якісні показники відносно одного якогось параметру або забезпечують використання нечіткої логіки управління чи нейромережі з регулюванням одного контуру процесу обпалу. Аналіз літературних джерел показує, що нейронні системи управління є перспективним напрямком удосконалення технологічного процесу обпалу клінкеру і потребують подальшого розвитку.Мета та завдання. Метою дослідження є пошук можливих шляхів покращення якості випалу готового матеріалу (клінкеру) з одночасним зниженням енерговитрат, поліпшенням умов роботи оператора на підприємстві, зниженням загального часу випалу клінкеру шляхом створення автоматизованої системи керування з нейронним регулятором на основі еталонної моделі та безпосереднім її

Reinforcement learning (RL)-based brain machine interfaces (BMIs) enable the user to learn from the environment through interactions to complete the task without desired signals, which is promising for clinical applications. Previous studies exploited Q-learning techniques to discriminate neural states into simple directional actions providing the trial initial timing. However, the movements in BMI applications can be quite complicated, and the action timing explicitly shows the intention when to move. The rich actions and the corresponding neural states form a large state-action space, imposing generalization difficulty on Q-learning. In this paper, we propose to adopt attention-gated reinforcement learning (AGREL) as a new learning scheme for BMIs to adaptively decode high-dimensional neural activities into seven distinct movements (directional moves, holdings and resting) due to the efficient weight-updating. We apply AGREL on neural data recorded from M1 of a monkey to directly predict a seven-action set in a time sequence to reconstruct the trajectory of a center-out task. Compared to Q-learning techniques, AGREL could improve the target acquisition rate to 90.16% in average with faster convergence and more stability to follow neural activity over multiple days, indicating the potential to achieve better online decoding performance for more complicated BMI tasks. © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.

Author Posting. © The Author(s), 2013. This is the author's version of the work. It is posted here by permission of Company of Biologists for personal use, not for redistribution. The definitive version was published in Journal of Experimental Biology 217 (2014):850-858, doi:10.1242/​jeb.091884., Squids display impressive changes in body coloration that are afforded by two types of dynamic skin elements: structural iridophores (which produce iridescence) and pigmented chromatophores. Both color elements are neurally controlled, but nothing is known about the iridescence circuit, or the environmental cues, that elicit iridescence expression. To tackle this knowledge gap, we performed denervation, electrical stimulation and behavioral experiments using the long-fin squid, Doryteuthis pealeii. We show that while the pigmentary and iridescence circuits originate in the brain, they are wired differently in the periphery: (i) the iridescence signals are routed through a peripheral center called the stellate ganglion and (ii) the iridescence motorneurons likely originate within this ganglion (as revealed by nerve fluorescence dye fills). Cutting the inputs to the stellate ganglion that descend from the brain shifts highly reflective iridophores into a transparent state. Taken together, these findings suggest that although brain commands are necessary for expression of iridescence, integration with peripheral information in the stellate ganglion could modulate the final output. We also demonstrate that squids change their iridescence brightness in response to environmental luminance; such changes are robust but slow (minutes to hours). The squid's ability to alter its iridescence levels may improve camouflage under different lighting intensities., This research was supported by the ONR Basic Research Challenge grant no. N00014-10-1-0989 and by the AFOSR grant FA9950090346., 2015-03-15

The role of sensory feedback is a central question in understanding vertebrate locomotion. Sensory feedback related to movement of the body and its interaction with the environment is known to have profound effects on the central pattern generator (CPG), the neural circuit responsible for generating the basic locomotor pattern. Conversely, the CPG controls muscle activation, leading to changes in body configurations as it interacts with the environment. We take two approaches to understanding the role of sensory feedback in locomotion: a control-theory approach and a CPG-based approach. In the control theory approach, we have developed a general method of computing the optimal local feedback control law given a model of the plant (the mapping from muscle activation to movement) and a cost rate function that penalizes muscle activation and rewards speed through the environment. The first step in this method is to the compute the optimal steady-state swimming pattern. In the CPG-based approach, we have investigated the role of sensory feedback in a simple closed-loop model in which a CPG produces a pattern of muscle activation which is modified by sensory feedback related to body curvature.

This thesis examines aspects of the neural control of breathing after spinal cord injury (SCI). Spinal injury at cervical and thoracic levels disrupts the function of respiratory muscles, with serious consequences for health. Chapter One describes the respiratory muscles and their neural control. Chapter Two shows the effect of six weeks stimulated cough training in 15 people with high-level SCI. All had weak expiratory muscles and a compromised cough. Electrical stimulation (50 Hz) was applied through surface electrodes on the thoraco-abdominal wall during a voluntary cough. Stimulation acutely improved cough and six weeks of stimulated cough training further improved abdominal (Pga) and thoracic (Poes) pressures by 25% and 36% respectively, and expiratory cough flow (PEFcough) by 16%. Lung function also improved after training. Chapter Three shows the effect of stimulus intensity on expiratory pressure, flow and volume, during a voluntary cough with added stimulation. PEFcough reached a plateau at ~210 mA. Peak values for Pga, Poes and PEFcough were 83 cm H2O, 66 cm H2O and 4 l/s, respectively. The plateau in PEFcough indicates dynamic airway compression occurred. This may help to produce a more effective cough. Chapter Four examines whether the reflex response to loading of the scalene muscles by brief airway occlusion was present in people with high-level SCI above C6. Two of 14 subjects had an early inhibitory reflex. A subsequent excitatory response occurred in five subjects. The median onset and peak latencies were longer than in able-bodied subjects, but the amplitude of the responses was similar. The low incidence of the reflex in people with high-level SCI suggests an important role for ascending signals arising from the intercostal muscle afferents in the genesis of the reflex. Chapter Five describes a new short-latency inhibitory reflex which occurs bilaterally in the scalene muscles in response to single stimuli to the 8th and 10th intercostal nerves in

Squids display impressive changes in body coloration that are afforded by two types of dynamic skin elements: structural iridophores (which produce iridescence) and pigmented chromatophores. Both color elements are neurally controlled, but nothing is known about the iridescence circuit, or the environmental cues, that elicit iridescence expression. To tackle this knowledge gap, we performed denervation, electrical stimulation and behavioral experiments using the long-fin squid, Doryteuthis pealeii. We show that while the pigmentary and iridescence circuits originate in the brain, they are wired differently in the periphery: (i) the iridescence signals are routed through a peripheral center called the stellate ganglion and (ii) the iridescence motorneurons likely originate within this ganglion (as revealed by nerve fluorescence dye fills). Cutting the inputs to the stellate ganglion that descend from the brain shifts highly reflective iridophores into a transparent state. Taken together, these findings suggest that although brain commands are necessary for expression of iridescence, integration with peripheral information in the stellate ganglion could modulate the final output. We also demonstrate that squids change their iridescence brightness in response to environmental luminance; such changes are robust but slow (minutes to hours). The squid's ability to alter its iridescence levels may improve camouflage under different lighting intensities.

This thesis addresses the neural control of the human inspiratory muscles. Single motor unit and multiunit electromyographic recordings are made from inspiratory and limb muscles to investigate the organisation of inspiratory motoneurone output and strategies by which motoneurone output is optimised. In the first two chapters, the output of parasternal intercostal motor units in respiratory and non-respiratory ‘tasks’ are described. The results show that across parasternal intercostal spaces, there is a decreasing rostrocaudal gradient of motor unit output in targeted voluntary breaths, such that inspiratory activity is greatest and earliest in cranial interspaces. This topographic recruitment is similar to quiet breaths and the majority of motor units are active in both voluntary and quiet breaths. In a non-respiratory voluntary task, rotation of the trunk (Chapter 3), common motor units are also active, but inspiratory motor unit output on both sides of the chest wall is altered by unilateral rotation. Multiple descending drives to the respiratory muscles may be organised and integrated at the spinal cord such that the same motoneurones are depolarised but their output depends on the task(s) performed. The strategy of motor unit recruitment in two inspiratory muscles is examined in Chapter 4. The profiles of activation of an obligatory inspiratory muscle, scalenes, and an accessory muscle, sternocleidomastoid, are not altered by lung volume or task (isovolumetric ‘static’ versus ‘dynamic’ task). Rather than the activation of these muscles being dependent on afferent signals of lung volume, they are recruited according to their relative mechanical advantage for inspiration. These results suggest that neural drive to these muscles has an element that is ‘preset’. The final study investigates neural and mechanical behaviour in the first dorsal interosseous muscle. The results show that there is coupling between neural drive and

[EN] A Generalized Predictive Control scheme (GPC) is developed, based on a neural model of the process, and then applied on a laboratory neutralization reactor. The neural model, which is obtained previously by identification, is linearized at each iteration of the control algorithm. Hence, the learning capacity of the neural networks and the computer efficiency of the GPC are combined, producing a system with the advantages of a predictive controller extended to non-linear systems, that shows good precision and transient response performance., [ES] Se desarrolla una estrategia de control inteligente basada en redes neuronales, para procesos no-lineales, y se implanta en un reactor de neutralización de laboratorio. El esquema de control se basa en el denominado Control Predictivo Generalizado (GPC), pero utiliza un modelo neuronal del reactor, obtenido previamente por identificación. El uso de las redes neuronales se justifica debido a su estructura no lineal y a su paralelismo masivo, similar al de sus contrapartes biológicas, y a su capacidad de aprender a reproducir el comportamiento de la planta a partir de datos de operación. El modelo neuronal se linealiza en cada iteración del algoritmo de control, consiguiéndose un sistema de control con las ventajas del GPC pero extendido a sistemas no lineales, que se comporta con precisión y rapidez ante perturbaciones.

[EN] A Generalized Predictive Control scheme (GPC) is developed, based on a neural model of the process, and then applied on a laboratory neutralization reactor. The neural model, which is obtained previously by identification, is linearized at each iteration of the control algorithm. Hence, the learning capacity of the neural networks and the computer efficiency of the GPC are combined, producing a system with the advantages of a predictive controller extended to non-linear systems, that shows good precision and transient response performance., [ES] Se desarrolla una estrategia de control inteligente basada en redes neuronales, para procesos no-lineales, y se implanta en un reactor de neutralización de laboratorio. El esquema de control se basa en el denominado Control Predictivo Generalizado (GPC), pero utiliza un modelo neuronal del reactor, obtenido previamente por identificación. El uso de las redes neuronales se justifica debido a su estructura no lineal y a su paralelismo masivo, similar al de sus contrapartes biológicas, y a su capacidad de aprender a reproducir el comportamiento de la planta a partir de datos de operación. El modelo neuronal se linealiza en cada iteración del algoritmo de control, consiguiéndose un sistema de control con las ventajas del GPC pero extendido a sistemas no lineales, que se comporta con precisión y rapidez ante perturbaciones.

[EN] A Generalized Predictive Control scheme (GPC) is developed, based on a neural model of the process, and then applied on a laboratory neutralization reactor. The neural model, which is obtained previously by identification, is linearized at each iteration of the control algorithm. Hence, the learning capacity of the neural networks and the computer efficiency of the GPC are combined, producing a system with the advantages of a predictive controller extended to non-linear systems, that shows good precision and transient response performance., [ES] Se desarrolla una estrategia de control inteligente basada en redes neuronales, para procesos no-lineales, y se implanta en un reactor de neutralización de laboratorio. El esquema de control se basa en el denominado Control Predictivo Generalizado (GPC), pero utiliza un modelo neuronal del reactor, obtenido previamente por identificación. El uso de las redes neuronales se justifica debido a su estructura no lineal y a su paralelismo masivo, similar al de sus contrapartes biológicas, y a su capacidad de aprender a reproducir el comportamiento de la planta a partir de datos de operación. El modelo neuronal se linealiza en cada iteración del algoritmo de control, consiguiéndose un sistema de control con las ventajas del GPC pero extendido a sistemas no lineales, que se comporta con precisión y rapidez ante perturbaciones.

Neurophysiological experiments in walking cats have shown that a number of neural control mechanisms are involved in regulating the movements of the hind legs during locomotion. It is experimentally hard to isolate individual mechanisms without disrupting the natural walking pattern and we therefore introduce a different approach where we use a model to identify what control is necessary to maintain stability in the musculo-skeletal system. We developed a computer simulation model of the cat hind legs in which the movements of each leg are produced by eight limb muscles whose activations follow a centrally generated pattern with no proprioceptive feedback. All linear transfer functions, from each muscle activation to each joint angle, were identified using the response of the joint angle to an impulse in the muscle activation at 65 postures of the leg covering the entire step cycle. We analyzed the sensitivity and stability of each muscle action on the joint angles by studying the gain and pole plots of these transfer functions. We found that the actions of most of the hindlimb muscles display inherent stability during stepping, even without the involvement of any proprioceptive feedback mechanisms, and that those musculo-skeletal systems are acting in a critically damped manner, enabling them to react quickly without unnecessary oscillations. We also found that during the late swing, the activity of the posterior biceps/semitendinosus (PB/ST) muscles causes the joints to be unstable. In addition, vastus lateralis (VL), tibialis anterior (TA) and sartorius (SAT) muscle-joint systems were found to be unstable during the late stance phase, and we conclude that those muscles require neuronal feedback to maintain stable stepping, especially during late swing and late stance phases. Moreover, we could see a clear distinction in the pole distribution (along the step cycle) for the systems related to the ankle joint from that of the other two joints, hip or knee. A similar, QC 20100525 QC 20111109

Locomotion is one of the most important behaviours and requires interaction between sensors at various levels of the nervous system and the limb muscles of an animal. The basic neural rhythm for locomotion in mammals has been shown to arise from local neural networks residing in the spinal cord and these networks are known as central pattern generators (CPGs). However, during the locomotion, these centres are constantly interacting with the sensory feedback signals coming from muscles, joints and peripheral skin receptors in order to adapt the stepping to varying environmental conditions. Conceptual models of mammalian locomotion have been constructed using mathematical models of locomotor subsystems based on the abundance of neurophysiological evidence obtained primarily in the cat. Several aspects of locomotor control using the cat as an animal model have been investigated employing computer simulations and here we use the same approach to address number of questions or/and hypotheses related to rhythmic locomotion in quadrupeds. Some of the involve questions are, role of mechanical linkage during deafferented walking, finding inherent stabilities/instabilities of muscle-joint interactions during normal walking, estimating phase dependent controlability of muscle action over joints. This thesis presents the basics of a biologically realistic model of mammalian locomotion and summarises methodological approaches in modelling quadruped locomotor subsystems such as CPGs, limb muscles and sensory pathways. In the first appended article, we extensively discuss the construction details of the three-dimensional computer simulator for the study of the hind leg neuro-musculo-skeletal-control system and its interactions during normal walking of the cat. The simulator with the walking model is programmed in Python scripting language with other supported open source libraries such as Open Dynamics Engine (ODE) for simulating body dynamics and OpenGL for three dimensional graphi, QC 20101111

Locomotion is one of the most important behaviours and requires interaction between sensors at various levels of the nervous system and the limb muscles of an animal. The basic neural rhythm for locomotion in mammals has been shown to arise from local neural networks residing in the spinal cord and these networks are known as central pattern generators (CPGs). However, during the locomotion, these centres are constantly interacting with the sensory feedback signals coming from muscles, joints and peripheral skin receptors in order to adapt the stepping to varying environmental conditions. Conceptual models of mammalian locomotion have been constructed using mathematical models of locomotor subsystems based on the abundance of neurophysiological evidence obtained primarily in the cat. Several aspects of locomotor control using the cat as an animal model have been investigated employing computer simulations and here we use the same approach to address number of questions or/and hypotheses related to rhythmic locomotion in quadrupeds. Some of the involve questions are, role of mechanical linkage during deafferented walking, finding inherent stabilities/instabilities of muscle-joint interactions during normal walking, estimating phase dependent controlability of muscle action over joints. This thesis presents the basics of a biologically realistic model of mammalian locomotion and summarises methodological approaches in modelling quadruped locomotor subsystems such as CPGs, limb muscles and sensory pathways. In the first appended article, we extensively discuss the construction details of the three-dimensional computer simulator for the study of the hind leg neuro-musculo-skeletal-control system and its interactions during normal walking of the cat. The simulator with the walking model is programmed in Python scripting language with other supported open source libraries such as Open Dynamics Engine (ODE) for simulating body dynamics and OpenGL for three dimensional graphi, QC 20101111

Locomotion is one of the most important behaviours and requires interaction between sensors at various levels of the nervous system and the limb muscles of an animal. The basic neural rhythm for locomotion in mammals has been shown to arise from local neural networks residing in the spinal cord and these networks are known as central pattern generators (CPGs). However, during the locomotion, these centres are constantly interacting with the sensory feedback signals coming from muscles, joints and peripheral skin receptors in order to adapt the stepping to varying environmental conditions. Conceptual models of mammalian locomotion have been constructed using mathematical models of locomotor subsystems based on the abundance of neurophysiological evidence obtained primarily in the cat. Several aspects of locomotor control using the cat as an animal model have been investigated employing computer simulations and here we use the same approach to address number of questions or/and hypotheses related to rhythmic locomotion in quadrupeds. Some of the involve questions are, role of mechanical linkage during deafferented walking, finding inherent stabilities/instabilities of muscle-joint interactions during normal walking, estimating phase dependent controlability of muscle action over joints. This thesis presents the basics of a biologically realistic model of mammalian locomotion and summarises methodological approaches in modelling quadruped locomotor subsystems such as CPGs, limb muscles and sensory pathways. In the first appended article, we extensively discuss the construction details of the three-dimensional computer simulator for the study of the hind leg neuro-musculo-skeletal-control system and its interactions during normal walking of the cat. The simulator with the walking model is programmed in Python scripting language with other supported open source libraries such as Open Dynamics Engine (ODE) for simulating body dynamics and OpenGL for three dimensional graphi, QC 20101111

Locomotion is one of the most important behaviours and requires interaction between sensors at various levels of the nervous system and the limb muscles of an animal. The basic neural rhythm for locomotion in mammals has been shown to arise from local neural networks residing in the spinal cord and these networks are known as central pattern generators (CPGs). However, during the locomotion, these centres are constantly interacting with the sensory feedback signals coming from muscles, joints and peripheral skin receptors in order to adapt the stepping to varying environmental conditions. Conceptual models of mammalian locomotion have been constructed using mathematical models of locomotor subsystems based on the abundance of neurophysiological evidence obtained primarily in the cat. Several aspects of locomotor control using the cat as an animal model have been investigated employing computer simulations and here we use the same approach to address number of questions or/and hypotheses related to rhythmic locomotion in quadrupeds. Some of the involve questions are, role of mechanical linkage during deafferented walking, finding inherent stabilities/instabilities of muscle-joint interactions during normal walking, estimating phase dependent controlability of muscle action over joints. This thesis presents the basics of a biologically realistic model of mammalian locomotion and summarises methodological approaches in modelling quadruped locomotor subsystems such as CPGs, limb muscles and sensory pathways. In the first appended article, we extensively discuss the construction details of the three-dimensional computer simulator for the study of the hind leg neuro-musculo-skeletal-control system and its interactions during normal walking of the cat. The simulator with the walking model is programmed in Python scripting language with other supported open source libraries such as Open Dynamics Engine (ODE) for simulating body dynamics and OpenGL for three dimensional graphi, QC 20101111

Locomotion is one of the most important behaviours and requires interaction between sensors at various levels of the nervous system and the limb muscles of an animal. The basic neural rhythm for locomotion in mammals has been shown to arise from local neural networks residing in the spinal cord and these networks are known as central pattern generators (CPGs). However, during the locomotion, these centres are constantly interacting with the sensory feedback signals coming from muscles, joints and peripheral skin receptors in order to adapt the stepping to varying environmental conditions. Conceptual models of mammalian locomotion have been constructed using mathematical models of locomotor subsystems based on the abundance of neurophysiological evidence obtained primarily in the cat. Several aspects of locomotor control using the cat as an animal model have been investigated employing computer simulations and here we use the same approach to address number of questions or/and hypotheses related to rhythmic locomotion in quadrupeds. Some of the involve questions are, role of mechanical linkage during deafferented walking, finding inherent stabilities/instabilities of muscle-joint interactions during normal walking, estimating phase dependent controlability of muscle action over joints. This thesis presents the basics of a biologically realistic model of mammalian locomotion and summarises methodological approaches in modelling quadruped locomotor subsystems such as CPGs, limb muscles and sensory pathways. In the first appended article, we extensively discuss the construction details of the three-dimensional computer simulator for the study of the hind leg neuro-musculo-skeletal-control system and its interactions during normal walking of the cat. The simulator with the walking model is programmed in Python scripting language with other supported open source libraries such as Open Dynamics Engine (ODE) for simulating body dynamics and OpenGL for three dimensional graphi, QC 20101111

Falls from heights (FFH) are one of the leading causes of fatalities in skilled labor divisions such as construction, mining, agriculture/forestry, and manufacturing. Previous research has established that localized muscle fatigue (LMF) increases center of mass (COM)- and center of pressure (COP)-based measures of quiet stance. This is important because these increases have been linked to elevated risk of falls, and workers in the construction industry frequently engage in fatiguing activities while working at heights. In addition, the rate of fatality due to an occupational fall increases exponentially with age. Improved methods of fall prevention may be obtained through increased understanding of factors that have a deleterious effect on balance and postural control such as LMF and aging. An initial study was conducted to investigate the effects of LMF and aging on balance recovery from a postural perturbation without stepping. Sagittal plane postural perturbations were administered to young and older groups of participants before and after exercises to fatigue the lumbar extensors or ankle plantar flexors. Measures of balance recovery were based on the COM and COP trajectories and the maximum perturbation that could be withstood without stepping. Balance recovery measures were consistent with an LMF-induced decrement to recover from perturbations without stepping. Aging was also associated with an impaired ability to recover from the perturbations. The second study in the series investigated the effects of aging and LMF on the neural control of upright stance during small postural perturbations. Small magnitude postural perturbations were administered to young and older groups before and after fatiguing exercises. A single degree of freedom (DOF) model of the human body was developed that accurately simulated the experimentally collected kinematics during recovery from the perturbations. The model was controlled by invariant feedback gains that operated on the ti

Insect walking relies on a complex interaction between the environment, body segments, muscles and the nervous system. For the stick insect in particular, previous investigations have highlighted the role of specific sensory signals in the timing of activity of central neural networks driving the individual leg joints. The objective of the current study was to relate specific sensory and neuronal mechanisms, known from experiments on reduced preparations, to the generation of the natural sequence of events forming the step cycle in a single leg. We have done this by simulating a dynamic 3D-biomechanical model of the stick insect coupled to a reduced model of the neural control system, incorporating only the mechanisms under study. The neural system sends muscle activation levels to the biomechanical system, which in turn provides correctly timed propriosensory signals back to the neural model. The first simulations were designed to test if the currently known mechanisms would be sufficient to explain the coordinated activation of the different leg muscles in the middle leg. Two experimental situations were mimicked: restricted stepping where only the coxatrochanteral joint and the femur-tibia joint were free to move, and the unrestricted single leg movements on a friction-free surface. The first of these experimental situations is in fact similar to the preparation used in gathering much of the detailed knowledge on sensory and neuronal mechanisms. The simulations show that the mechanisms included can indeed account for the entire step cycle in both situations. The second aim was to test to what extent the same sensory and neuronal mechanisms would be adequate also for controlling the front and hind legs, despite the large differences in both leg morphology and kinematic patterns. The simulations show that front leg stepping can be generated by basically the same mechanisms while the hind leg control requires some reorganization. The simulations suggest that the inf, QC 20100525 QC 20111103

Examines the neural bases of visual and auditory processing for perception and sensorimotor control. Focuses on physiological and anatomical studies of the mammalian nervous system as well as behavioral studies of animals and humans. Studies visual pattern, color and depth perception, auditory responses and speech coding, and spatial localization. Offered alternate years.

Examines the neural bases of visual and auditory processing for perception and sensorimotor control. Focuses on physiological and anatomical studies of the mammalian nervous system as well as behavioral studies of animals and humans. Studies visual pattern, color and depth perception, auditory responses and speech coding, and spatial localization. Offered alternate years.

Examines the neural bases of visual and auditory processing for perception and sensorimotor control. Focuses on physiological and anatomical studies of the mammalian nervous system as well as behavioral studies of animals and humans. Studies visual pattern, color and depth perception, auditory responses and speech coding, and spatial localization. Offered alternate years.

Examines the neural bases of visual and auditory processing for perception and sensorimotor control. Focuses on physiological and anatomical studies of the mammalian nervous system as well as behavioral studies of animals and humans. Studies visual pattern, color and depth perception, auditory responses and speech coding, and spatial localization. Offered alternate years.

Adopting multi-parameter methods of interpreting pathological changes in the heart over time could improve clinical diagnosis of heart diseases. This study investigated the efficiency of parameters that express heart state variation and neural control. The investigators studied three kinds of parameters (global, local, and dynamic) using different methods to extract physiological and pathological information with animal models. Pathological notch on the QRS complex of electrocardiogram (ECG) is defined as a local parameter that is one of high-frequency components (HFCs). Poincare dispersed-dot plots (PDDP) are defined as nonlinear global parameters. Pathological notching information on the QRS complex is related to myocardial injuries. The authors have been working on man-made myocardial infarction models to simulate cardiac abnormalities. They have found that both myocardial injury methods could produce a good idiosyncratic relationship between the injury area model and man-made pathological conditions. A large number of repetitive experiments with 25 healthy dogs indicated that the thresholds for pathological notching are 84 microvolts in amplitude and 3.8 ms in width. The PDDP was a good parameter of heart nonlinear state and rate variability and has thresholds of about 26000 ms2 in area and 420 ms in long axis for human beings and 600 ms2 in area and 85 ms in long axis for dogs. Both parameters have shown to be sensitive in the early detection of cardiac pathology and also have dynamic characteristics. (2 figures, 9 references), Paper presented at the Annual Int'l Conference of the IEEE Engineering in Medicine and Biology Society (23rd) held in Istanbul, Turkey, on 25-28 Oct. 2001. See also ADM001351 for entire conference on cd-rom.

The performance report describes progress over the last 6 months in three areas: robots, physiology and modeling.

The performance report describes progress over the last 6 months on 3 areas; robotics, physiology and analysis of evolved neural circuits.

This chapter reviews current ideas on the neural control of eye and head movements, with special emphasis on the role of the superior colliculus. The problem of how gaze shifts are controlled has too many aspects to be grasped in a single model, and it is therefore not yet possible to develop a model that does justice to the complexity of the neural control system and which can account for its rich repertoire of capabilities. A more realistic approach is to concentrate on a few well-studied aspects of system behavior that can be isolated as challenges for a much more limited endeavour. The models discussed here concentrate on the role and the neural implementation of internal feedback, the transformation from topographically to temporally coded signals (and vice versa), the neural implementation of Listing's law, and the collicular role in the co-ordination of combined eye–head movements. Although each of these models concentrates on a particular set of aspects of the total problem and ignores others, taken together they can serve to illustrate how the signal processing at various levels in the saccadic control system can be viewed from different angles, and to clarify the issues surrounding the collicular role in the control of gaze. Before these models can be discussed, we will have to review earlier relevant models.

Ekman and Oster synthesize in this paper the studies on facial expressions of emotion. They start presenting observed data and unresolved issues of transcultural and evolutive studies. They focus then on a review of facial measurements made from different perspectives, some issues related to the accuracy of the data supplied by expression and on the facial feedback reports. Last part of the article presents an exposition about neural control and autonomous correlation of facial expression and closes its synthesis with a promising outlook at the contributions of future research work on this field to other psychology areas and mentioning several findings showing how the facial expression study may help to understand some practical aspects of social interaction, En este trabajo Ekman y Oster sintetizan los estudios acerca de las expresiones faciales de la emoción. Comienzan presentando los datos observados y las cuestiones pendientes de los estudios transculturales y evolutivos, centrándose a continuación en el repaso de las mediciones faciales llevadas a cabo desde diversas perspectivas, en las cuestiones relativas a la exactitud de la información proporcionada por la expresión y en los trabajos sobre retroalimentación facial. La última parte se reserva a la exposición del control neural y correlatos autónomos de la expresión facial, cerrando su síntesis con una visión prometedora de las aportaciones de investigaciones futuras en este campo a otras áreas de la psicología y citando varios hallazgos que muestran cómo el estudio de la expresión facial puede ayudar a entender algunos de los aspectos prácticos de la interacción social