doi:10.1155/2008/868425 Research Article Neural Network Adaptive Control for Discrete-Time Nonlinear Nonnegative Dynamical Systems

Nonnegative and compartmental dynamical system models are derived from mass and energy balance considerations that involve dynamic states whose values are nonnegative. These models are widespread in engineering and life sciences, and they typically involve the exchange of nonnegative quantities between subsystems or compartments, wherein each compartment is assumed to be kinetically homogeneous. In this paper, we develop a neuroadaptive control framework for adaptive set-point regulation of discrete-time nonlinear uncertain nonnegative and compartmental systems. The proposed framework is Lyapunov-based and guarantees ultimate boundedness of the error signals corresponding to the physical system states and the neural network weighting gains. In addition, the neuroadaptive controller guarantees that the physical system states remain in the nonnegative orthant of the state space for nonnegative initial conditions. Copyright q 2008 Wassim M. Haddad et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 1

The effect of Midazolam and Propranolol on fear memory reconsolidation in ethanol-withdrawn rats: Influence of D-cycloserine

Background: Withdrawal from chronic ethanol facilitates the formation of contextual fear memory and delays the onset to extinction, with its retrieval promoting an increase in ethanol consumption. Consequently, manipulations aimed to reduce these aversive memories, may be beneficial in the treatment of alcohol discontinuation symptoms. Related to this, pharmacological memory reconsolidation blockade has received greater attention due to its therapeutic potential. Methods: Here, we examined the effect of post-reactivation amnestic treatments such as Midazolam (MDZ, 3 mg/kg i.p) and Propranolol (PROP, 5 mg/kg i.p) on contextual fear memory reconsolidation in ethanol- withdrawn (ETOH) rats. Next, we examined whether the activation of N-methyl-D-aspartate (NMDA) receptors induced by d-cycloserine (DCS, 5 mg/kg i.p., a NMDA partial agonist) before memory reactivation can facilitate the disruptive effect of PROP and MDZ on fear memory in ETOH rats. Results: We observed a resistance to the disruptive effect of both MDZ and PROP following memory reactivation. Although intra-basolateral amygdala (BLA; 1.25 ug/side) and systemic PROP administration attenuated fear memory in DCS pre-treated ETOH rats, DCS/MDZ treatment did not affect memory in these animals. Finally, a decrease of both total and surface protein expression of the α1 GABAA receptor (GABAA-R) subunit in BLA was found in the ETOH rats. Conclusions: Ethanol withdrawal facilitated the formation of fear memory resistant to labilization post-reactivation. DCS administration promoted the disruptive effect of PROP on memory reconsolidation in ETOH rats. The resistance to MDZ's disruptive effect on fear memory reconsolidation may be, at least in part, associated with changes in the GABAA-R composition induced by chronic ethanol administration/withdrawal.Fil: Ortiz, Vanesa. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Farmacología Experimental de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Farmacología Experimental de Córdoba; ArgentinaFil: Giachero, Marcelo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Farmacología Experimental de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Farmacología Experimental de Córdoba; ArgentinaFil: Espejo, Pablo Javier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Farmacología Experimental de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Farmacología Experimental de Córdoba; ArgentinaFil: Molina, Víctor Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Farmacología Experimental de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Farmacología Experimental de Córdoba; ArgentinaFil: Martijena, Irene Delia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto de Farmacología Experimental de Córdoba. Universidad Nacional de Córdoba. Facultad de Ciencias Químicas. Instituto de Farmacología Experimental de Córdoba; Argentin

Remembering Forward: Neural Correlates of Memory and Prediction in Human Motor Adaptation

We used functional MR imaging (FMRI), a robotic manipulandum and systems identification techniques to examine neural correlates of predictive compensation for spring-like loads during goal-directed wrist movements in neurologically-intact humans. Although load changed unpredictably from one trial to the next, subjects nevertheless used sensorimotor memories from recent movements to predict and compensate upcoming loads. Prediction enabled subjects to adapt performance so that the task was accomplished with minimum effort. Population analyses of functional images revealed a distributed, bilateral network of cortical and subcortical activity supporting predictive load compensation during visual target capture. Cortical regions – including prefrontal, parietal and hippocampal cortices – exhibited trial-by-trial fluctuations in BOLD signal consistent with the storage and recall of sensorimotor memories or “states” important for spatial working memory. Bilateral activations in associative regions of the striatum demonstrated temporal correlation with the magnitude of kinematic performance error (a signal that could drive reward-optimizing reinforcement learning and the prospective scaling of previously learned motor programs). BOLD signal correlations with load prediction were observed in the cerebellar cortex and red nuclei (consistent with the idea that these structures generate adaptive fusimotor signals facilitating cancelation of expected proprioceptive feedback, as required for conditional feedback adjustments to ongoing motor commands and feedback error learning). Analysis of single subject images revealed that predictive activity was at least as likely to be observed in more than one of these neural systems as in just one. We conclude therefore that motor adaptation is mediated by predictive compensations supported by multiple, distributed, cortical and subcortical structures

Dopamine D4 receptor counteracts morphine-induced changes in M opioid receptor signaling in the striosomes of the rat caudate putamen.

Morphine is one of the most potent analgesic drugs used to relieve moderate to severe pain. After long-term use of morphine, neuroadaptive changes in the brain promotes tolerance, which result in a reduced sensitivity to most of its effects with attenuation of analgesic efficacy, and dependence, revealed by drug craving and physical or psychological manifestations of drug withdrawal. The mu opioid receptor (MOR) is critical, not only in mediating morphine analgesia, but also in addictive behaviors by the induction of a strong rewarding effect. We have previously shown that dopamine D4 receptor (D4R) stimulation counteracts morphine-induced activation of dopaminergic nigrostriatal pathway and accumulation of Fos family transcription factors in the caudate putamen (CPu). In the present work, we have studied the effect of D4R activation on MOR changes induced by morphine in the rat CPu on a continuous drug treatment paradigm, by analyzing MOR protein level, pharmacological profile, and functional coupling to G proteins. Furthermore, using conditioned place preference and withdrawal syndrome test, we have investigated the role of D4R activation on morphine-related behavioural effects. MOR immunoreactivity, agonist binding density and its coupling to G proteins are up-regulated in the striosomes by continuous morphine treatment. Interestingly, co-treatment of morphine with the dopamine D4 receptor (D4R) agonist PD168,077 fully counteracts these adaptive changes in MOR, in spite of the fact that continuous PD168,077 treatment increases the [3H]DAMGO Bmax values to the same degree as seen after continuous morphine treatment. In addition, the administration of the D4R agonist counteracts the rewarding effects of morphine, as well as the development of physical dependence. The present results give support for the existence of antagonistic functional D4R-MOR receptor-receptor interactions in the adaptive changes occurring in MOR of striosomes on continuous administration of morphine and preventing morphine-related behaviour.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

Analyzing P300 Distractors for Target Reconstruction

P300-based brain-computer interfaces (BCIs) are often trained per-user and per-application space. Training such models requires ground truth knowledge of target and non-target stimulus categories during model training, which imparts bias into the model. Additionally, not all non-targets are created equal; some may contain visual features that resemble targets or may otherwise be visually salient. Current research has indicated that non-target distractors may elicit attenuated P300 responses based on the perceptual similarity of these distractors to the target category. To minimize this bias, and enable a more nuanced analysis, we use a generalized BCI approach that is fit to neither user nor task. We do not seek to improve the overall accuracy of the BCI with our generalized approach; we instead demonstrate the utility of our approach for identifying target-related image features. When combined with other intelligent agents, such as computer vision systems, the performance of the generalized model equals that of the user-specific models, without any user specific data.Comment: 4 pages, 3 figure

Deep Transfer Learning for Error Decoding from Non-Invasive EEG

We recorded high-density EEG in a flanker task experiment (31 subjects) and an online BCI control paradigm (4 subjects). On these datasets, we evaluated the use of transfer learning for error decoding with deep convolutional neural networks (deep ConvNets). In comparison with a regularized linear discriminant analysis (rLDA) classifier, ConvNets were significantly better in both intra- and inter-subject decoding, achieving an average accuracy of 84.1 % within subject and 81.7 % on unknown subjects (flanker task). Neither method was, however, able to generalize reliably between paradigms. Visualization of features the ConvNets learned from the data showed plausible patterns of brain activity, revealing both similarities and differences between the different kinds of errors. Our findings indicate that deep learning techniques are useful to infer information about the correctness of action in BCI applications, particularly for the transfer of pre-trained classifiers to new recording sessions or subjects.Comment: 6 pages, 9 figures, The 6th International Winter Conference on Brain-Computer Interface 201

Current Concepts on Drug Abuse and Dependence

Drug addiction is a complex disease characterized by compulsive and uncontrollable desire to seek and consume the drug. In time, drug-related terminology has undergone many changes, arising from the deepening of the mechanisms of action, but also about the need for a greater precision in the definition. Drug dependence can be assigned not only to pharmacological effects of the drugs of abuse, but also to their interaction with each particular neurological and psychological constitution. The research on the neurobiological mechanisms of addiction processes allows both a better understanding of current pharmacotherapy and the development of new treatment strategies in drug abuse and dependence. In this review we intend to present the current concepts related to drug abuse and dependence

MT-7716, a potent NOP receptor agonist, preferentially reduces ethanol seeking and reinforcement in post-dependent rats

Dysregulation of the nociceptin (N/OFQ) system has been implicated in alcohol abuse and alcoholism, and growing evidence suggests that targeting this system may be beneficial for treating alcoholism. To further explore the treatment target potential of the N/OFQ system, the novel non-peptide, small-molecule N/OFQ (NOP) agonist MT-7716, (R)-2-3-[1-(Acenaphthen-1-yl)piperidin-4-yl]-2-oxo-2,3-dihydro-1H-benzimidazol-1-yl-N-methylacetamide hydrochloride hydrate, was examined for its effects on ethanol self-administration and stress-induced reinstatement of alcohol seeking in non-dependent and post-dependent rats. Male Wistar rats were trained to self-administer ethanol and then made ethanol dependent via repeated intragastric ethanol intubation. The effects of MT-7716 (0.3 and 1 mg/kg; PO) on alcohol self-administration were determined 2 weeks following dependence induction, when baseline self-administration was restored. Effects of MT-7716 on stress-induced reinstatement were tested in separate cohorts of rats, 1 and 3 weeks post-withdrawal. MT-7716 reduced alcohol self-administration and stress-induced reinstatement of alcohol seeking in post-dependent rats, but was ineffective in non-dependent animals. Moreover, the prevention of stress-induced reinstatement by MT-7716 was more pronounced at 3 weeks post-dependence. The results further confirm treatment target potential for the NOP receptor and identify non-peptide NOP agonists as promising potential treatment drugs for alcohol abuse and relapse prevention. The findings also support dysregulation of the N/OFQ system as a factor in alcohol seeking and reinforcement