Search

This study investigates the neuroadaptive tracking control problem for a class of strict-feedback nonlinear systems with spatiotemporal constraints. An adaptive neural network-based control system is developed to alleviate the effects of modeling uncertainties and external disturbances. In particular, the proposed method ensures that the system tracking error has a predefined performance boundary (spatial constraint). Moreover, using a novel time-scale transformation method, uncertain nonlinear systems can achieve a prescribed finitetime convergence to a time-varying scaling function in the pointing position (temporal constraint). Finally, the efficiency of the proposed method is verified with two simulation examples. [ABSTRACT FROM AUTHOR]

This paper studies the cooperative control problem of multiple humanoid robots handling a common payload in the presence of position and velocity constraints, unmeasurable velocity, as well as nonparametric uncertainties. By using a state observer to estimate the unmeasured velocity, a neuroadaptive output-feedback control scheme is developed, which by blending an error transformation with barrier Lyapunov function ensures that the full-state tracking error converges to a prescribed compact set around origin within a given finite time at a preassignable convergence rate. Furthermore, it is shown that all the signals in the closed-loop system are ultimately semiglobally uniformly bounded. Simulation results are verified to show the effectiveness and benefits of the proposed scheme. [ABSTRACT FROM AUTHOR]

Task-related functional magnetic resonance imaging (fMRI) is a widely-used tool for studying the neural processing correlates of human behavior in both healthy and clinical populations. There is growing interest in mapping individual differences in fMRI task behavior and neural responses. By utilizing neuroadaptive task designs accounting for such individual differences, task durations can be personalized to potentially optimize neuroimaging study outcomes (e.g., classification of task-related brain states). To test this hypothesis, we first retrospectively tracked the volume-by-volume changes of beta weights generated from general linear models (GLM) for 67 adult subjects performing a stop-signal task (SST). We then modeled the convergence of the volume-by-volume changes of beta weights according to their exponential decay (ED) in units of half-life. Our results showed significant differences in beta weight convergence estimates of optimal stopping times (OSTs) between go following successful stop trials and failed stop trials for both cocaine dependent (CD) and control group (Con), and between go following successful stop trials and go following failed stop trials for Con group. Further, we implemented support vector machine (SVM) classification for 67 CD/Con labeled subjects and compared the classification accuracies of fMRI-based features derived from (1) the full fMRI task versus (2) the fMRI task truncated to multiples of the unit of half-life. Among the computed binary classification accuracies, two types of task durations based on 2 half-lives significantly outperformed the accuracies using fully acquired trials, supporting this length as the OST for the SST. In conclusion, we demonstrate the potential of a neuroadaptive task design that can be widely applied to personalizing other task-based fMRI experiments in either dynamic real-time fMRI applications or within fMRI preprocessing pipelines. [ABSTRACT FROM AUTHOR]

Repeated cycles of alcohol [ethanol (EtOH)] intoxication and withdrawal dysregulate excitatory glutamatergic systems in the brain and induce neuroadaptations in the medial prefrontal cortex (mPFC) that contribute to cognitive dysfunction. The mPFC is composed of subdivisions that are functionally distinct, with dorsal regions facilitating drug-cue associations and ventral regions modulating new learning in the absence of drug. A key modulator of glutamatergic activity is the holoenzyme calcium/calmodulin-dependent protein kinase II (CaMKII) that phosphorylates ionotropic glutamate receptors. Here, we examined the hypothesis that abstinence from chronic intermittent EtOH (CIE) exposure dysregulates CaMKII activity in the mPFC to impair cognitive flexibility. We used an operant model of strategy set shifting in male Long-Evans rats demonstrating reduced susceptibility to trial omissions during performance in a visual cue-guided task versus albino strains. Relative to naïve controls, rats experiencing approximately 10 days of abstinence from CIE vapor exposure demonstrated impaired performance during a procedural shift from visual cue to spatial location discrimination. Phosphorylation of CaMKII subtype α was upregulated in the dorsal, but not ventral mPFC of CIE-exposed rats, and was positively correlated with perseverative-like responding during the set shift. The findings suggest that abstinence from CIE exposure induces an undercurrent of kinase activity (e.g. CaMKII), which may promote aberrant glutamatergic responses in select regions of the mPFC. Given the role of the mPFC in modulating executive control of behavior, we propose that increased CaMKII subtype α activity reflects a dysregulated 'top-down' circuit that interferes with adaptive behavioral performance under changing environmental demands. [ABSTRACT FROM AUTHOR]

Background Chronic nicotine exposure produces neuroadaptations in brain reward systems and α4β2 nicotinic acetylcholine receptors (nAChRs) in the corticolimbic brain areas. We previously demonstrated opposite effects of nicotine exposure delivered by self-administration or pumps on brain reward thresholds that can be attributed to the different temporal pattern and contingency of nicotine exposure. We investigated the effects of these two factors on reward thresholds and somatic signs during nicotine withdrawal, and on nAChRs binding in corticolimbic brain areas. Methods The intracranial self-stimulation procedure was used to assess reward thresholds in rats prepared with pumps delivering various doses of nicotine continuously or intermittently. Separate group of rats were randomly exposed to nicotine via pumps (non-contingent) or nicotine self-administration (contingent) to determine [ 125 I]-epibatidine binding at α4β2* nAChRs. Results Withdrawal from continuous non-contingent nicotine exposure led to significant elevations in thresholds and increases in somatic signs in rats, while there was no significant effect of withdrawal from intermittent non-contingent nicotine exposure at the same doses. nAChRs were upregulated during withdrawal from continuous non-contingent nicotine exposure. α4β2* nAChRs were upregulated in the ventral tegmental area and prelimbic cortex during withdrawal from non-contingent intermittent exposure and in the nucleus accumbens during withdrawal from contingent intermittent nicotine exposure to the same dose. Conclusions During non-contingent nicotine exposure, the temporal pattern of nicotine delivery differentially affected thresholds and somatic signs of withdrawal. Upregulation of α4β2* nAChRs was brain site-specific and depended on both temporal pattern and contingency of nicotine exposure. [ABSTRACT FROM AUTHOR]

In this paper, the neuro-adaptive optimal nonlinear control approach and algorithm are proposed for the tracking control of an air-breathing hypersonic aircraft considering uncertainties. Based on the reinforcement learning mechanism, the neuro-adaptive control agent is constructed using actor-critic architecture, which consists of two interacting neural networks, one for optimal control protocol, known as the actor NN, and the other for policy evaluation, known as critic NN. The optimality conditions for this adaptive controller are derived by using the discrete minimum principle. In the meanwhile, the parametric and mismatched uncertainty and unmodeled nonlinearity are handled by using another neural network named as UNN with aid of the concept of a virtual plant. The output of the network in the virtual plant helps to estimate the optimal control with varying dynamics of air-breathing hypersonic flight aircraft. Simulation results are presented to verify the effectiveness of this design method for the tracking control of the air-breathing hypersonic aircraft in the presence of uncertainties. [ABSTRACT FROM AUTHOR]

Background and Purpose: Regulation of μ receptor dynamics such as its trafficking is a possible mechanism underlying opioid tolerance that contributes to inefficient recycling of opioid responses. We aimed to characterize the functional turnover of μ receptors in the noradrenergic nucleus locus coeruleus (LC).Experimental Approach: We measured opioid effect by single-unit extracellular recordings of LC neurons from rat brain slices. Immunocytochemical techniques were used to evaluate μ receptor trafficking.Key Results: After near-complete, irreversible μ receptor inactivation with β-funaltrexamine (β-FNA), opioid effect spontaneously recovered in a rapid and efficacious manner. In contrast, α2 -adrenoceptor-mediated effect hardly recovered after receptor inactivation with the irreversible antagonist EEDQ. When the recovery of opioid effect was tested after various inactivating time schedules, we found that the longer the β-FNA pre-exposure, the less efficient and slower the functional μ receptor turnover became. Interestingly, μ receptor turnover was slower when β-FNA challenge was repeated in the same cell, indicating constitutive μ receptor recycling by trafficking from a depletable pool. Double immunocytochemistry confirmed the constitutive nature of μ receptor trafficking from a cytoplasmic compartment. The μ receptor turnover was slowed down when LC neuron calcium- or firing-dependent processes were prevented or vesicular protein trafficking was blocked by a low temperature or transport inhibitor.Conclusions and Implications: Constitutive trafficking of μ receptors from a depletable intracellular pool (endosome) may account for its rapid and efficient functional turnover in the LC. A finely-tuned regulation of μ receptor trafficking and endosomes could explain neuroadaptive plasticity to opioids in the LC. [ABSTRACT FROM AUTHOR]

Alcoholism is a complex brain disease characterized by three distinct stages of the addiction cycle that manifest as neuroadaptive changes in the brain. One such stage of the addiction cycle is alcohol withdrawal and the negative affective states that promote drinking and maintain addiction. Repeated alcohol use, genetic predisposition to alcoholism and anxiety, and alcohol exposure during crucial developmental periods all contribute to the development of alcohol-induced withdrawal and negative affective symptoms. Epigenetic modifications within the amygdala have provided a molecular basis of these negative affective symptoms, also known as the dark side of addiction. Here, we propose that allostatic change within the epigenome in the amygdala is a prime mechanism of the biological basis of negative affective states resulting from, and contributing to, alcoholism. Acute alcohol exposure produces an anxiolytic response which is associated with the opening of chromatin due to increased histone acetylation, increased CREB binding protein (CBP) levels, and histone deacetylase (HDAC) inhibition. After chronic ethanol exposure, these changes return to baseline along with anxiety-like behaviors. However, during withdrawal, histone acetylation decreases due to increased HDAC activity and decreased CBP levels in the amygdala circuitry leading to the development of anxiety-like behaviors. Additionally, innately higher expression of the HDAC2 isoform leads to a deficit in global and gene-specific histone acetylation in the amygdala that is associated with a decrease in the expression of several synaptic plasticity-associated genes and maintaining heightened anxiety-like behavior and excessive alcohol intake. Adolescent alcohol exposure also leads to higher expression of HDAC2 and a deficit in histone acetylation leading to decreased expression of synaptic plasticity-associated genes and high anxiety and drinking behavior in adulthood. All these studies indicate that the epigenome can undergo allostatic reprogramming in the amygdaloid circuitry during various stages of alcohol exposure. Furthermore, opening the chromatin by inhibiting HDACs using pharmacological or genetic manipulations can lead to the attenuation of anxiety as well as alcohol intake. Chromatin remodeling provides a clear biological basis for the negative affective states seen during alcohol addiction and presents opportunities for novel drug development and treatment options. This article is part of the Special Issue entitled “Alcoholism”. [ABSTRACT FROM AUTHOR]

Nuclear calcium is an important signaling end point in synaptic excitation-transcription coupling that is critical for long-term neuroadaptations. Here, we show that nuclear calcium acting via a target gene, VEGFD, is required for hippocampus-dependent fear memory consolidation and extinction in mice. Nuclear calcium-VEGFD signaling upholds the structural integrity and complexity of the dendritic arbor of CA1 neurons that renders those cells permissive for the efficient generation of synaptic input-evoked nuclear calcium transients driving the expression of plasticity-related genes. Therefore, the gating of memory functions rests on the reciprocally reinforcing maintenance of an intact dendrite geometry and a functional synapse-to-nucleus communication axis. In psychiatric and neurodegenerative disorders, therapeutic application of VEGFD may help to stabilize dendritic structures and network connectivity, which may prevent cognitive decline and could boost the efficacy of extinction-based exposure therapies. [ABSTRACT FROM AUTHOR]

This paper proposes a practical design method for the robust control of a class of MIMO nonlinear plants operating under model uncertainties and matched disturbances where the only available information for feedback are the outputs of the plant. A neural networks based dynamic integral sliding mode control (NNDISMC) with output differentiator observer is developed for the considered class. This NNDISMC approach utilizes the robust output differentiation observer for the higher derivative estimation and neural networks to estimate the nonlinear functions which are assumed unknown. Having estimated the unknown derivatives and uncertain functions, an integral manifold based on the estimated states is designed and a control law is proposed which confirms the sliding mode enforcement across the designed integral manifold from the very start of the process. The overall robustness of the controller is guaranteed by using the neural networks, differentiator observer and dynamic integral control law in a closed loop. The closed loop stability analysis is presented in detail, and the asymptotic convergence of the system states to the equilibrium is confirmed. The proposed method is very practical and plays a very significant role in the robust control of electromechanical systems, such as robotic manipulators, unmanned air vehicles and underwater vehicles. The simulation results on a robotic manipulator are presented to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The effectiveness of today's human-machine interaction is limited by a communication bottleneck as operators are required to translate high-level concepts into a machine-mandated sequence of instructions. In contrast, we demonstrate effective, goal-oriented control of a computer system without any form of explicit communication from the human operator. Instead, the system generated the necessary input itself, based on real-time analysis of brain activity. Specific brain responses were evoked by violating the operators' expectations to varying degrees. The evoked brain activity demonstrated detectable differences reflecting congruency with or deviations from the operators' expectations. Real-time analysis of this activity was used to build a user model of those expectations, thus representing the optimal (expected) state as perceived by the operator. Based on this model, which was continuously updated, the computer automatically adapted itself to the expectations of its operator. Further analyses showed this evoked activity to originate from the medial prefrontal cortex and to exhibit a linear correspondence to the degree of expectation violation. These findings extend our understanding of human predictive coding and provide evidence that the information used to generate the user model is task-specific and reflects goal congruency. This paper demonstrates a form of interaction without any explicit input by the operator, enabling computer systems to become neuroadaptive, that is, to automatically adapt to specific aspects of their operator'smindset. Neuroadaptive technology significantlywidens the communication bottleneck and has the potential to fundamentally change the way we interact with technology. [ABSTRACT FROM AUTHOR]

It is difficult to measure the wind speed accurately in short term. This reveals challenges for wind turbine control, especially for maximum power point tracking with adaptive control strategies. In this paper, a genetic algorithm based support vector machine model is adopted to estimate the wind speed, using physically measurable signals, such as the electrical power, pitch angle, and rotor speed, while the desired rotor speed can be obtained accordingly. Further, by combining the radial basis function neural networks with adaptive algorithms, a novel virtual parameter based neuroadaptive controller is developed to accommodate the system uncertain and external disturbances. The effectiveness and performances of the proposed method are validated and demonstrated with FAST (Fatigue, Aerodynamics, Structures, and Turbulence) and Simulink. [ABSTRACT FROM AUTHOR]

This paper presents two neuro-adaptive controllers for a class of uncertain single-input, single-output (SISO) nonlinear non-affine systems with unknown gain sign. The first approach is state feedback controller, so that a neuro-adaptive state-feedback controller is constructed based on the backstepping technique. The second approach is an observer-based controller and K-filters are designed to estimate the system states. The proposed method relaxes a priori knowledge of control gain sign and therefore by utilizing the Nussbaum-type functions this problem is addressed. In these methods, neural networks are employed to approximate the unknown nonlinear functions. The proposed adaptive control schemes guarantee that all the closed-loop signals are semi-globally uniformly ultimately bounded (SGUUB). Finally, the theoretical results are numerically verified through simulation examples. Simulation results show the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper addresses synchronisation problem of high-order multi-input/multi-output (MIMO) multi-agent systems. Each agent has unknown nonlinear dynamics and is subject to uncertain external disturbances. The agents must follow a reference trajectory. An adaptive distributed controller based on relative information of neighbours of each agent is designed to solve the problem for any undirected connected communication topology. A radial basis function neural network is used to represent the controller's unknown structure. Lyapunov stability analysis is employed to guarantee stability of the overall system. By the theoretical analysis, the closed-loop control system is shown to be uniformly ultimately bounded. Finally, simulations are provided to show effectiveness of the proposed control method against uncertainty and disturbances. [ABSTRACT FROM AUTHOR]

Copyright of Automatika: Journal for Control, Measurement, Electronics, Computing & Communications is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

ABSTRACT This paper discusses a general design pattern that can provide systems engineering guidance for building adaptive systems. The Neocortex Adaptive System Pattern (NASP) architecture is an adaptive decision-making architecture. It is derived from the physical architecture observed within the neocortex. It allows different adaptive system components with diverse methodologies and techniques to coexist and cooperate within a single system. A literature review of relevant neuroscience literature is provided. An architectural view, along with a taxonomy of architecture features, is explained in detail. Experiment results that compare an implemented NASP system, a non-NASP adaptive system, and rule-based systems within a combative simulation are presented. The NASP design pattern unifies the diverse set of algorithms and technologies found across the spectrum of adaptive systems. Evidence from this study indicates that multiple methods and time windows for adaptation can result in superior performance of the overall system. The implications of this result infer a clear preference for Bayesian-based adaptive systems over neural network-based adaptive systems when the system faces time-sensitive problems. This paper supports the claim of a design pattern by providing an example system that shares the same architectural features as NASP. [ABSTRACT FROM AUTHOR]

The goal of this research is to test the potential for neuroadaptive automation to improve response speed to a hazardous event by using a brain-computer interface (BCI) to decode perceptual-motor intention. Seven participants underwent four experimental sessions while measuring brain activity with magnetoencephalograpy. The first three sessions were of a simple constrained task in which the participant was to pull back on the control stick to recover from a perturbation in attitude in one condition and to passively observe the perturbation in the other condition. The fourth session consisted of having to recover from a perturbation in attitude while piloting the plane through the Grand Canyon constantly maneuvering to track over the river below. Independent component analysis was used on the first two sessions to extract artifacts and find an event related component associated with the onset of the perturbation. These two sessions were used to train a decoder to classify trials in which the participant recovered from the perturbation (motor intention) vs. just passively viewing the perturbation. The BCI-decoder was tested on the third session of the same simple task and found to be able to significantly distinguish motor intention trials from passive viewing trials (mean = 69.8%). The same BCI-decoder was then used to test the fourth session on the complex task. The BCI-decoder significantly classified perturbation from no perturbation trials (73.3%) with a significant time savings of 72.3 ms (Original response time of 425.0-352.7 ms for BCI-decoder). The BCI-decoder model of the best subject was shown to generalize for both performance and time savings to the other subjects. The results of our off-line open loop simulation demonstrate that BCI based neuroadaptive automation has the potential to decode motor intention faster than manual control in response to a hazardous perturbation in flight attitude while ignoring ongoing motor and visual induced activity related to piloting the airplane. [ABSTRACT FROM AUTHOR]

This paper presents a new approach for the modeling of an Electrochromic (EC) device. The proposed system relies on an adaptive network-based fuzzy inference system or equivalently, Adaptive Neuro-Fuzzy Inference System (ANFIS). The ANFIS network has used 33 experimental data sets of which, 24 data sets were taken as training data and 9 data sets were taken as testing data. The ANFIS performance statistical indices mean absolute error (MAE), root mean square error (RMSE), and non-dimensional error index (NDEI) are found to be close to zero and coefficient of determination ( R 2 ) and linear correlation coefficient ( ρ ) and variance account for (VAF) are found to be close to one. Some interpretability issues regarding the ANFIS models, such as rule consistency, rule separation, and rule completeness are discussed. Simulation examples are provided to illustrate the effectiveness of the proposed approach. This study also includes experiments that confirm the good performance and the potential of the ANFIS models for datasets with noise. The proposed models can be seen as virtual luminous transmittance sensors. [ABSTRACT FROM AUTHOR]

In this paper, a hybrid approach is proposed for detecting and classifying the vibration signal of induction motor. The proposed hybrid technique is the combination of S-transformation algorithm and adaptive neuro fuzzy inference system (ANFIS) method. Here, the proposed hybrid method contains two processes, such as, fault detection and classification process. Initially, the pre-processing is applied in the electric motor vibration signal. In the fault detection process, significant features from vibration signals are extracted through the S-transformation algorithm. Consequently, the ANFIS classification technique is employed to classify the signal into the faulty or the normal. The proposed hybrid technique is implemented in MATLAB working platform. The performance of the proposed hybrid technique is evaluated with five types of faulty vibration signals. The performance of the proposed hybrid method is compared with the existing method such as S-transform-RBFNN and S-transform-FFBNN. Analyze these methods with the help of statistical measures such as, accuracy, sensitivity and specificity value. [ABSTRACT FROM AUTHOR]

Previous results from our laboratory showed that angiotensin II AT 1 receptors (AT 1 -R) are involved in the neuroadaptative changes induced by amphetamine. The aim of the present work was to study functional and neurochemical responses to angiotensin II (ANG II) mediated by AT 1 -R activation in animals previously exposed to amphetamine. For this purpose male Wistar rats (250–320 g) were treated with amphetamine (2.5 mg/kg/day intraperitoneal) or saline for 5 days and implanted with intracerebroventricular (i.c.v.) cannulae. Seven days after the last amphetamine administration the animals received ANG II (400 pmol) i.c.v. One group was tested in a free choice paradigm for sodium (2% NaCl) and water intake and sacrificed for Fos immunoreactivity (Fos-IR) determinations. In a second group of rats, urine and plasma samples were collected for electrolytes and plasma renin activity determination and then they were sacrificed for Fos-IR determination in Oxytocinergic neurons (Fos-OT-IR). Results: Repeated amphetamine exposure (a) prevented the increase in sodium intake and Fos-IR cells in caudate-putamen and accumbens nucleus induced by ANG II i.c.v. (b) potentiated urinary sodium excretion and Fos-OT-IR in hypothalamus and (c) increased the inhibitory response in plasma renin activity, in response to ANG II i.c.v. Our results indicate a possible functional desensitisation of AT 1 -R in response to ANG II, induced by repeated amphetamine exposure. This functional AT 1 -R desensitisation allows to unmask the effects of ANG II i.c.v. mediated by oxytocin. We conclude that the long lasting changes in brain AT 1 -R functionality should be considered among the psychostimulant-induced neuroadaptations. [ABSTRACT FROM AUTHOR]

Chronic intermittent ethanol consumption is associated with neurodegeneration and cognitive deficits in preclinical laboratory animals and in the clinical population. While previous work suggests a role for neuroadaptations in the N-methyl-D-aspartate (NMDA) receptor in the development of ethanol dependence and manifestation of withdrawal, the relative roles of ethanol exposure and ethanol withdrawal in producing these effects have not been fully characterized. To examine underlying cytotoxic mechanisms associated with chronic intermittent ethanol (CIE) exposure, organotypic hippocampal slices were exposed to 1e3 cycles of ethanol (50 mM) in cell culture medium for 5 days, followed by 24 h of ethanol withdrawal, in which a portion of slices were exposed to competitive NMDA receptor antagonist (2R)-amino-5-phosphonovaleric acid (APV; 40 μM). Cytotoxicity was assessed using immunohistochemical labeling of neuron-specific nuclear protein (NeuN; Fox-3), a marker of mature neurons, and thionine (2%) staining of Nissl bodies. Multiple cycles of CIE produced neurotoxicity, as reflected in persisting losses of neuron NeuN immunoreactivity and thionine staining in each of the primary cell layers of the hippocampal formation. Hippocampi aged in vitro were significantly more sensitive to the toxic effects of multiple cycles of CIE than were non-aged hippocampi. This effect was not demonstrated in slices exposed to continuous ethanol, in the absence of withdrawal, or to a single exposure/withdrawal regimen. Exposure to APV significantly attenuated the cytotoxicity observed in the primary cell layers of the hippocampus. The present findings suggest that ethanol withdrawal is required to produce NMDA receptor-dependent hippocampal cytotoxicity, particularly in the aging hippocampus in vitro. [ABSTRACT FROM AUTHOR]

In this paper, an indirect approach to the dual-mode adaptive robust controller (DMARC) is proposed, which combines the typical transient and robustness properties of variable structure systems with a smooth control signal in steady state, typical of conventional adaptive controllers, as model reference adaptive controller. The aim of this indirect version, here named indirect DMARC, is to provide a more intuitive controller design, based on physical plant parameters, as resistances, inertia moments, capacitances, and so on, maintaining DMARC properties. In this paper, a stability analysis for the proposed controller and simulations to an unstable second-order plant will be presented. Copyright © 2013 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

The only way we can interact with the world is through movements, and our primary interactions are via the hands, thus any loss of hand function has immediate impact on our quality of life. However, to date it has not been systematically assessed how coordination in the hand's joints affects every day actions. This is important for two fundamental reasons. Firstly, to understand the representations and computations underlying motor control "in-the-wild" situations, and secondly to develop smarter controllers for prosthetic hands that have the same functionality as natural limbs. In this work we exploit the correlation structure of our hand and finger movements in daily-life. The novelty of our idea is that instead of averaging variability out, we take the view that the structure of variability may contain valuable information about the task being performed. We asked seven subjects to interact in 17 daily-life situations, and quantified behavior in a principled manner using Cyber Glove body sensor networks that, after accurate calibration, track all major joints of the hand. Our key findings are: (1) We confirmed that hand control in daily-life tasks is very low-dimensional, with four to five dimensions being sufficient to explain 80-90% of the variability in the natural movement data. (2) We established a universally applicable measure of manipulative complexity that allowed us to measure and compare limb movements across tasks. We used Bayesian latent variable models to model the low-dimensional structure of finger joint angles in natural actions. (3) This allowed us to build a naÏve classifier that within the first 1000ms of action initiation (from a flat hand start configuration) predicted which of the 17 actions was going to be executed-enabling us to reliably predict the action intention from very short-time-scale initial data, further revealing the foreseeable nature of hand movements for control of neuroprosthetics and tele operation purposes. (4) Using the Expectation-Maximization algorithm on our latent variable model permitted us to reconstruct with high accuracy (<5-6° MAE) the movement trajectory of missing fingers by simply tracking the remaining fingers. Overall, our results suggest the hypothesis that specific hand actions are orchestrated by the brain in such a way that in the natural tasks of daily-life there is sufficient redundancy and predictability to be directly exploitable for neuroprosthetics. [ABSTRACT FROM AUTHOR]

Previous studies suggest that nuclear histone deacetylase HDAC5 has a dynamic relationship with drug-induced behavioral neuroadaptations. The new work by Taniguchi et al. (2017) suggests that targets of nuclear HDAC5 mediate the behavioral effects of rewarding drugs via regulation of cocaine-associated stimuli. [ABSTRACT FROM AUTHOR]

A single or repeated exposure to psychostimulants induces long-lasting neuroadaptative changes. Different neurotransmitter systems are involved in these responses including the neuropeptide angiotensin II. Our study tested the hypothesis that the neuroadaptative changes induced by amphetamine produce alterations in brain RAS components that are involved in the expression of the locomotor sensitization to the psychostimulant drug. Wistar male rats, pretreated with amphetamine were used 7 or 21 days later to study AT1 receptors by immunohistochemistry and western blot and also angiotensinogen mRNA and protein in caudate putamen and nucleus accumbens. A second group of animals was used to explore the possible role of Ang II AT1 receptors in the expression of behavioral sensitization. In these animals treated in the same way, bearing intra-cerebral cannula, the locomotor activity was tested 21 days later, after an amphetamine challenge injection and the animals received an AT1 blocker, losartan, or saline 5 min before the amphetamine challenge. An increase of AT1 receptor density induced by amphetamine was found in both studied areas and a decrease in angiotensinogen mRNA and protein only in CPu at 21 days after treatment; meanwhile, no changes were established in NAcc. Finally, the increased locomotor activity induced by amphetamine challenge was blunted by losartan administration in CPu. No differences were detected in the behavioral sensitization when the AT1 blocker was injected in NAcc. Our results support the hypothesis of a key role of brain RAS in the neuroadaptative changes induced by amphetamine. [ABSTRACT FROM AUTHOR]

Impulsivity is a behavioral trait frequently seen not only in drug-addicted individuals but also in individuals who pathologically overeat. However, whether impulsivity predates the development of uncontrollable feeding is unknown. In this study, we hypothesized that a high impulsivity trait precedes and confers vulnerability for food addiction-like behavior. For this purpose, we trained ad libitum-fed male Wistar rats in a differential reinforcement of low rates of responding (DRL) task to select Low- and High-impulsive rats. Then, we allowed Low- and High-impulsive rats to self-administer a highly palatable diet (Palatable group) or a regular chow diet (Chow group) in 1-h daily sessions, under fixed ratio (FR) 1, FR3, FR5, and under a progressive ratio (PR) schedules of reinforcement. In addition, we tested the compulsiveness for food in Low- and High-impulsive rats by measuring the food eaten in the aversive, open compartment of a light/dark conflict test. Finally, we measured the expression of the transcription factor ΔFosB in the shell and the core of the nucleus accumbens, which is a marker for neuroadaptive changes following addictive drug exposure. The data we obtained demonstrate that impulsivity is a trait that predicts the development of food addiction-like behaviors, including: (i) excessive intake, (ii) heightened motivation for food, and (iii) compulsive-like eating, when rats are given access to highly palatable food. In addition, we show that the food addiction phenotype in high impulsive subjects is characterized by an increased expression of the transcription factor ΔFosB in the nucleus accumbens shell. These results reveal that impulsivity confers an increased propensity to develop uncontrollable overeating of palatable food. [ABSTRACT FROM AUTHOR]

In recent years, research on military applications of neuroscience has grown in sophistication, raising the question as to whether states using weapon systems that draw on neuroscience are capable of applying international humanitarian law (IHL) to that use. I argue that neuroweapons largely eliminate the role of language in targeting, render unstable the distinction between superior and subordinate, and ultimately disrupt the premise of responsibility under IHL. I conclude that it is impossible to assess whether future uses of these weapons will be lawful under IHL. [ABSTRACT FROM AUTHOR]

Abstract: The cellular mechanisms by which opiate addiction develops with repetitive use remain largely unresolved. Intercellular calcium homeostasis is one of the most critical elements to determine neuroadaptive changes and neuronal fate. Heroin, one of the most addictive opiates, may induce neurotoxicity potentially inducing brain impairment, especially for those chronic users who get an overdose. Here we examined changes in intracellular calcium concentration ([Ca2+] i ) after repeated exposure to heroin using cultured cerebral cortical neurons. Dynamic changes in [Ca2+] i indicated by fluo-3-AM were monitored using confocal laser scan microscopy, followed by cytotoxicity assessments. It showed that the cells dissociated from heroin-dependent rats had a smaller depolarization-induced [Ca2+] i responses, and a higher elevation in [Ca2+] i when challenged with a high concentration of heroin (500μM). The restoration ability to remove calcium after washout of these stimulants was impaired. Calcium channel blocker verapamil inhibited the heroin-induced [Ca2+] i elevations as well as the heroin-induced cell damage. The relative [Ca2+] i of the nerve cells closely correlated with the number of damaged cells induced by heroin. These results demonstrate that nerve cells from heroin-dependent rats manifest abnormal [Ca2+] i homeostasis, as well as vulnerability to heroin overdose, suggesting involvement of [Ca2+] i regulation mechanisms in heroin addiction and neurotoxicity. [Copyright &y& Elsevier]

The article focuses on understanding the challenges posed for neuroethics. Topics discussed include the emergence of neuroethics, the consideration of neuroethics as a theoretical challenge, the account of neuroethics as a socio-political challenge, and the application of neurotechnology suggesting terrorist brain identification.

Background: The dynorphin (DYN)/kappa-opioid receptor (KOR) system undergoes neuroadaptations following chronic alcohol exposure that promote excessive operant self-administration and negative affective-like states; however, the exact mechanisms are unknown. The present studies tested the hypothesis that an upregulated DYN/KOR system mediates excessive alcohol self-administration that occurs during withdrawal in alcohol-dependent rats by assessing DYN A peptide expression and KOR function, in combination with site-specific pharmacologic manipulations. Methods: Male Wistar rats were trained to self-administer alcohol using operant behavioral strategies and subjected to intermittent alcohol vapor or air exposure. Changes in self-administration were assessed by pharmacologic challenges during acute withdrawal. In addition, 22-kHz ultrasonic vocalizations were utilized to measure negative affective-like states. Immunohistochemical techniques assessed DYN A peptide expression and [35S]GTPγS coupling assays were performed to assess KOR function. Results: Alcohol-dependent rats displayed increased alcohol self-administration, negative affective-like behavior, DYN A-like immunoreactivity, and KOR signaling in the amygdala compared with nondependent control rats. Site-specific infusions of a KOR antagonist selectively attenuated self-administration in dependent rats, whereas a mu-opioid receptor/delta-opioid receptor antagonist cocktail selectively reduced self-administration in nondependent rats. A mu-opioid receptor antagonist/partial KOR agonist attenuated self-administration in both cohorts. Conclusions: Increased DYN A and increased KOR signaling could set the stage for a one-two punch during withdrawal that drives excessive alcohol consumption in alcohol dependence. Importantly, intracentral nucleus of the amygdala pharmacologic challenges functionally confirmed a DYN/KOR system involvement in the escalated alcohol self-administration. Together, the DYN/KOR system is heavily dysregulated in alcohol dependence and contributes to the excessive alcohol consumption during withdrawal. [Copyright &y& Elsevier]

Abstract: Both type I interferons (IFNs) and neurotrophins regulate neuroadaptive responses, but relatively little is known on the interaction between these two classes of regulatory proteins. Here we investigated the effect of IFN-β on the expression and functional activity of the common neurotrophin receptor p75NTR and the nerve growth factor (NGF) receptor TrkA. In differentiated human SH-SY5Y neuroblastoma cells prolonged exposure to IFN-β up-regulated p75NTR and TrkA levels, failed to affect the content of sortilin, a p75NTR co-receptor, and, consistent with our previous finding, down-regulated the brain-derived neurotrophic factor receptor TrkB. Quantitative real time RT-PCR indicated that IFN-β increased p75NTR and TrkA mRNA levels. In control and IFN-β treated cells proNGF failed to induce c-Jun N-terminal kinase and nuclear factor/kB activation, two p75NTR/sortilin signalling pathways mediating neuronal death. On the other hand, IFN-β treatment enhanced TrkA autophosphorylation and signalling induced by NGF and proNGF. Knockdown of p75NTR by siRNA reduced TrkA activation by proNGF and a subnanomolar concentration of NGF, whereas co-immunoprecipitation indicated close association of p75NTR and TrkA. Co-treatment with either NGF or proNGF reduced IFN-β pro-apoptotic and anti-neurotrophic effects. Similarly, in primary mouse hippocampal neurons IFN-β increased p75NTR and TrkA expression, down-regulated TrkB and enhanced NGF-induced phosphorylation of the pro-survival protein kinase Akt. The data demonstrate that in neuronal cells IFN-β differentially affects the expression and signalling of neurotrophin receptors and suggest that the up-regulation of the p75NTR/TrkA signalling complex may constitute a novel mechanism by which this cytokine selectively attenuates its pro-apoptotic effect in NGF-responsive cells. [Copyright &y& Elsevier]

Chronic exposure to ethanol produces a number of detrimental effects on behavior. Neuroadaptive changes in brain structure or function underlie these behavioral effects and may be transient or persistent in nature. Central to the functional changes are alterations in the biology of neuronal and glial cells of the brain. Recent data show that ethanol induces glial cells of the brain to produce elevated levels of neuroimmune factors including CCL2, a key innate immune chemokine. Depending on the conditions of ethanol exposure, the upregulated levels of CCL2 can be transient or persistent and outlast the period of ethanol exposure. Importantly, results indicate that the upregulated levels of CCL2 may lead to CCL2-ethanol interactions that mediate or regulate the effects of ethanol on the brain. Glial cells are in close association with neurons and regulate many neuronal functions. Therefore, effects of ethanol on glial cells may underlie some of the effects of ethanol on neurons. To investigate this possibility, we are studying effects of chronic ethanol on hippocampal synaptic function in a transgenic mouse model that expresses elevated levels of CCL2 in the brain through enhanced glial expression, a situation know to occur in alcoholics. Both CCL2 and ethanol have been reported to alter synaptic function in the hippocampus. In the current study, we determined if interactions are evident between CCL2 and ethanol at the level of hippocampal synaptic proteins. Two ethanol exposure paradigms were used; the first involved ethanol exposure by drinking and the second involved ethanol exposure in a paradigm that combines drinking plus ethanol vapor. The first paradigm does not produce dependence on ethanol, whereas the second paradigm is commonly used to produce ethanol dependence. Results show modest effects of both ethanol exposure paradigms on the level of synaptic proteins in the hippocampus of CCL2 transgenic mice compared with their non-transgenic littermate controls, consistent with ethanol-CCL2 interactions. No evidence of toxic effects of CCL2 or CCL2-ethanol interactions was observed. Taken together, these results support the idea that ethanol induced astrocyte production of CCL2 can result in neuroadaptive changes that interact with the actions of ethanol. [ABSTRACT FROM AUTHOR]

Abstract: In this paper we propose a practical design method for distributed cooperative tracking control of a class of higher-order nonlinear multi-agent systems. Dynamics of the agents (also called the nodes) are assumed to be unknown to the controller and are estimated using Neural Networks. Linearization-based robust neuro-adaptive controller driving the follower nodes to track the trajectory of the leader node is proposed. The nodes are connected through a weighted directed graph with a time-invariant topology. In addition to the fact that only few nodes have access to the leader, communication among the follower nodes is limited with some nodes having access to the information of their neighbor nodes only. Command generated by the leader node is ultimately followed by the followers with bounded synchronization error. The proposed controller is well-defined in the sense that control effort is restrained to practical limits. The closed-loop system dynamics are proved to be stable and simulation results demonstrate the effectiveness of the proposed control scheme. [Copyright &y& Elsevier]

Most clinically-used antidepressants acutely increase monoamine levels in synaptic clefts, while their therapeutic effects often require several weeks of administration. Slow neuroadaptive changes in serotonergic neurons are considered to underlie this delayed onset of beneficial actions. Recently, we reported that sustained exposure of rat organotypic raphe slice cultures containing abundant serotonergic neurons to selective serotonin (5-HT) reuptake inhibitors (citalopram, fluoxetine and paroxetine) caused the augmentation of exocytotic serotonin release. However, the ability of other classes of antidepressants to evoke a similar outcome has not been clarified. In this study, we investigated the sustained actions of two tricyclic antidepressants (imipramine and desipramine), one tetracyclic antidepressant (mianserin), three 5-HT and noradrenaline reuptake inhibitors (milnacipran, duloxetine and venlafaxine) and one noradrenergic and specific serotonergic antidepressant (mirtazapine) on serotonin release in the slice cultures. For seven of nine antidepressants, sustained exposure to the agents at concentrations of 0.1–100 μm augmented the level of increase in extracellular serotonin. The rank order of their potency was as follows: milnacipran>duloxetine>citalopram>venlafaxine>imipramine>fluoxetine>desipramine. Neither mirtazapine nor mianserin caused any augmentation. The highest augmentation by sustained exposure to milnacipran was partially attenuated by an α1-adrenoceptor antagonist, benoxathian, while the duloxetine-, venlafaxine- and citalopram-mediated increases were not affected. These results suggest that inhibition of the 5-HT transporter is required for the enhancement of serotonin release. Furthermore, the potent augmentation by milnacipran is apparently due to the accompanied activation of the α1-adrenoceptor. [ABSTRACT FROM PUBLISHER]

Background: Studies have demonstrated an enhanced dynorphin/kappa-opioid receptor (KOR) system following repeated cocaine exposure, but few reports have focused on neuroadaptations within the central amygdala (CeA). Methods: We identified KOR-related physiological changes in the CeA following escalation of cocaine self-administration in rats. We used in vitro slice electrophysiological (intracellular and whole-cell recordings) methods to assess whether differential cocaine access in either 1-hour (short access [ShA]) or 6-hour (long access [LgA]) sessions induced plasticity at CeA gamma-aminobutyric acid (GABA)ergic synapses or altered the sensitivity of these synapses to KOR agonism (U50488) or antagonism (norbinaltorphimine [norBNI]). We then determined the functional effects of CeA KOR blockade in cocaine-related behaviors. Results: Baseline evoked GABAergic transmission was enhanced in the CeA from ShA and LgA rats compared with cocaine-naïve rats. Acute cocaine (1 µmol/L) application significantly decreased GABA release in all groups (naïve, ShA, and LgA rats). Application of U50488 (1 µmol/L) significantly decreased GABAergic transmission in the CeA from naïve rats but increased it in LgA rats. Conversely, norBNI (200 nmol/L) significantly increased GABAergic transmission in the CeA from naïve rats but decreased it in LgA rats. Norbinaltorphimine did not alter the acute cocaine-induced inhibition of GABAergic responses. Finally, CeA microinfusion of norBNI blocked cocaine-induced locomotor sensitization and attenuated the heightened anxiety-like behavior observed during withdrawal from chronic cocaine exposure in the defensive burying paradigm. Conclusions: Together these data demonstrate that CeA dynorphin/KOR systems are dysregulated following excessive cocaine exposure and suggest KOR antagonism as a viable therapeutic strategy for cocaine addiction. [ABSTRACT FROM AUTHOR]

Despite decades of basic and clinical research, our understanding of how benzodiazepines tend to lose their efficacy over time (tolerance) is at least incomplete. In appears that tolerance develops relatively quickly for the sedative and anticonvulsant actions of benzodiazepines, whereas tolerance to anxiolytic and amnesic effects probably does not develop at all. In light of this evidence, we review the current evidence for the neuroadaptive mechanisms underlying benzodiazepine tolerance, including changes of (i) the GABAA receptor (subunit expression and receptor coupling), (ii) intracellular changes stemming from transcriptional and neurotrophic factors, (iii) ionotropic glutamate receptors, (iv) other neurotransmitters (serotonin, dopamine, and acetylcholine systems), and (v) the neurosteroid system. From the large variance in the studies, it appears that either different (simultaneous) tolerance mechanisms occur depending on the benzodiazepine effect, or that the tolerance-inducing mechanism depends on the activated GABAA receptor subtypes. Importantly, there is no convincing evidence that tolerance occurs with α subunit subtypeselective compounds acting at the benzodiazepine site. [ABSTRACT FROM AUTHOR]

Drug addiction is a major public health issue. It is typically a multigenetic brain disorder, implying combined changes of expression of several hundred genes. Psychostimulants (such as cocaine, heroin and amphetamines) induce strong and persistent neuroadaptive changes through a surfeit of gene regulatory mechanisms leading to addiction. Activity-dependent synaptic plasticity of the mesolimbic dopaminergic system, known as the 'reward pathway', plays a crucial role in the development of drug dependence. miRNAs are small non-coding RNAs, particularly abundant in the nervous system, that play key roles as regulatory molecules in processes such as neurogenesis, synapse development and plasticity in the brain. They also act as key spatiotemporal regulators during dendritic morphogenesis, controlling the expression of hundreds of genes involved in neuroplasticity and in the function of synapses. Recent studies have identified changes of several specific miRNA expression profiles and polymorphisms affecting the interactions between miRNAs and their targets in various brain disorders, including addiction: miR-16 causes adaptive changes in production of the serotonin transporter; miR-133b is specifically expressed in midbrain dopaminergic neurons, and regulates the production of tyrosine hydroxylase and the dopamine transporter; miR-212 affects production of striatal brain-derived neurotrophic factor and synaptic plasticity upon cocaine. Clearly, specific miRNAs have emerged as key regulators leading to addiction, and could serve as valuable targets for more efficient therapies. In this review, the aim is to provide an overview of the emerging role of miRNAs in addiction. [ABSTRACT FROM AUTHOR]

Brain–computer interfaces enable active communication and execution of a pre-defined set of commands, such as typing a letter or moving a cursor. However, they have thus far not been able to infer more complex intentions or adapt more complex output based on brain signals. Here, we present neuroadaptive generative modelling, which uses a participant's brain signals as feedback to adapt a boundless generative model and generate new information matching the participant's intentions. We report an experiment validating the paradigm in generating images of human faces. In the experiment, participants were asked to specifically focus on perceptual categories, such as old or young people, while being presented with computer-generated, photorealistic faces with varying visual features. Their EEG signals associated with the images were then used as a feedback signal to update a model of the user's intentions, from which new images were generated using a generative adversarial network. A double-blind follow-up with the participant evaluating the output shows that neuroadaptive modelling can be utilised to produce images matching the perceptual category features. The approach demonstrates brain-based creative augmentation between computers and humans for producing new information matching the human operator's perceptual categories. [ABSTRACT FROM AUTHOR]

In the article, the author discusses opioid dependence and addiction. The author explains that opioid addiction can be understood in terms of neuroadaptations that arise when exogenous opioids are taken regularly. Tolerance is described as the need to increase dose to achieve same effect while dependence is a physiologic response either to uncompensated increase in tolerance or withdrawal of a drug. The attempt of Washington to limit opioid doses prescribed for chronic pain is also discussed.

Sensitivity, selectivity and stability are decisive properties of sensors. In chemical gas sensors odor recognition can be severely compromised by poor signal stability, particularly in real life applications where the sensors are exposed to unpredictable sequences of odors under changing external conditions. Although olfactory receptor neurons in the nose face similar stimulus sequences under likewise changing conditions, odor recognition is very stable and odorants can be reliably identified independently from past odor perception. We postulate that appropriate pre-processing of the output signals of chemical sensors substantially contributes to the stability of odor recognition, in spite of marked sensor instabilities. To investigate this hypothesis, we use an adaptive, unsupervised neural network inspired by the glomerular input circuitry of the olfactory bulb. Essentially the model reduces the effect of the sensors' instabilities by utilizing them via an adaptive multicompartment feed-forward inhibition. We collected and analyzed responses of a 4 × 4 gas sensor array to a number of volatile compounds applied over a period of 18 months, whereby every sensor was sampled episodically. The network conferred excellent stability to the compounds' identification and was clearly superior over standard classifiers, even when one of the sensors exhibited random fluctuations or stopped working at all. [ABSTRACT FROM AUTHOR]