An opioid peptide from synganglia of the tick, Amblyomma testindinarium

An opioid peptide, which shares similarity with mammalian hemorphins, has been identified from the synganglia (central nervous system) of the hard tick, Amblyomma testindiarium. Its primary sequence was established as LVVYPWTKM that contains a tetrapeptide sequence Tyr-Pro-Trp-Thr of hemorphin-like opioid peptides. By hot-plate bioassay, the purified peptide and synthetic peptide displayed dose-related antinociceptive effect in mice, as observed for other hemorphin-like opioid peptides. This is the first opioid peptide identified from ticks. Ticks may utilize the opioid peptide in their strategy to escape host immuno-surveillance as well as in inhibiting responses directed against themselves. (c) 2004 Elsevier Inc. All rights reserved.

Isolation and cDNA cloning of cholecystokinin from the skin of Rana nigrovittata

Many neuroendocrine peptides that are distributed in amphibian gastrointestinal tract and central nervous system are also found in amphibian skins, and these peptides are classified into skin-gut-brain triangle peptides, such as bombesins, gastrin-releasi

Cloning and developmental expression of the Xenopus Nkx6 genes

The evolutionarily conserved Nkx6 family transcription factors play important roles in the patterning of the central nervous system (CNS) and pancreas in vertebrates. In this study, we describe the cloning and expression patterns of the three Nkx6 family

Xenopus RCOR2 (REST corepressor 2) interacts with ZMYND8, which is involved in neural differentiation

Regulation of neuronal gene expression is critical to nervous system development. REST (RE1-silencing transcription factor) regulates neuronal gene expression through interacting with a group of corepressor proteins including REST corepressors (RCOR). Here we show that Xenopus RCOR2 is predominantly expressed in the developing nervous system. Through a yeast two-hybrid screen, we isolated Xenopus ZMYND8 (Zinc finger and MYND domain containing 8) as an XRCOR2 interacting factor. XRCOR2 and XZMYND8 bind each other in co-immunoprecipitation assays and both of them can function as transcriptional repressors. XZMYND8 is co-expressed with XRCOR2 in the nervous system and overexpression of XZMYND8 inhibits neural differentiation in Xenopus embryos. These data reveal a RCOR2/ZMYND8 complex which might be involved in the regulation of neural differentiation. (C) 2010 Elsevier Inc. All rights reserved.

Differential expression of the Brunol/CELF family genes during Xenopus laevis early development

The BRUNOL/CELF family of RNA-binding proteins plays important roles in post-transcriptional regulation and has been implicated in several developmental processes. In this study, we describe the cloning and expression patterns of five Brunol genes in Xenopus laevis. Among them, only Brunol2 is maternally expressed and the zygotic expression of the other four Brunol genes starts at different developmental stages. During Xenopus development, Brunol1, 4-5 are exclusively expressed in the nervous system including domains in the brain, spinal cord, optic and otic vesicles. Brunol2 and 3 are expressed in both the somatic mesoderm and the nervous system. Brunol2 is also extensively expressed in the lens. In transfected Hela cells, BRUNOL1, 2 and 3 proteins are localized in both the cytoplasm and the nucleus, while BRUNOL4 and 5 are only present in the cytoplasm, indicating their different functions.

Adaptive control of stiffness to stabilize hand position with large loads.

The goal of this work was to investigate stability in relation to the magnitude and direction of forces applied by the hand. The endpoint stiffness and joint stiffness of the arm were measured during a postural task in which subjects exerted up to 30% maximum voluntary force in each of four directions while controlling the position of the hand. All four coefficients of the joint stiffness matrix were found to vary linearly with both elbow and shoulder torque. This contrasts with the results of a previous study, which employed a force control task and concluded that the joint stiffness coefficients varied linearly with either shoulder or elbow torque but not both. Joint stiffness was transformed into endpoint stiffness to compare the effect on stability as endpoint force increased. When the joint stiffness coefficients were modeled as varying with the net torque at only one joint, as in the previous study, we found that hand position became unstable if endpoint force exceeded about 22 N in a specific direction. This did not occur when the joint stiffness coefficients were modeled as varying with the net torque at both joints, as in the present study. Rather, hand position became increasingly more stable as endpoint force increased for all directions of applied force. Our analysis suggests that co-contraction of biarticular muscles was primarily responsible for the increased stability. This clearly demonstrates how the central nervous system can selectively adapt the impedance of the arm in a specific direction to stabilize hand position when the force applied by the hand has a destabilizing effect in that direction.

Impedance control and internal model use during the initial stage of adaptation to novel dynamics in humans.

This study investigated the neuromuscular mechanisms underlying the initial stage of adaptation to novel dynamics. A destabilizing velocity-dependent force field (VF) was introduced for sets of three consecutive trials. Between sets a random number of 4-8 null field trials were interposed, where the VF was inactivated. This prevented subjects from learning the novel dynamics, making it possible to repeatedly recreate the initial adaptive response. We were able to investigate detailed changes in neural control between the first, second and third VF trials. We identified two feedforward control mechanisms, which were initiated on the second VF trial and resulted in a 50% reduction in the hand path error. Responses to disturbances encountered on the first VF trial were feedback in nature, i.e. reflexes and voluntary correction of errors. However, on the second VF trial, muscle activation patterns were modified in anticipation of the effects of the force field. Feedforward cocontraction of all muscles was used to increase the viscoelastic impedance of the arm. While stiffening the arm, subjects also exerted a lateral force to counteract the perturbing effect of the force field. These anticipatory actions indicate that the central nervous system responds rapidly to counteract hitherto unfamiliar disturbances by a combination of increased viscoelastic impedance and formation of a crude internal dynamics model.

How is somatosensory information used to adapt to changes in the mechanical environment?

Recent studies examining adaptation to unexpected changes in the mechanical environment highlight the use of position error in the adaptation process. However, force information is also available. In this chapter, we examine adaptation processes in three separate studies where the mechanical environment was changed intermittently. We compare the expected consequences of using position error and force information in the changes to motor commands following a change in the mechanical environment. In general, our results support the use of position error over force information and are consistent with current computational models of motor learning. However, in situations where the change in the mechanical environment eliminates position error the central nervous system does not necessarily respond as would be predicted by these models. We suggest that it is necessary to take into account the statistics of prior experience to account for our observations. Another deficiency in these models is the absence of a mechanism for modulating limb mechanical impedance during adaptation. We propose a relatively simple computational model based on reflex responses to perturbations which is capable of accounting for iterative changes in temporal patterns of muscle co-activation.

Impedance control is tuned to multiple directions of movement

Humans are able to learn tool-handling tasks, such as carving, demonstrating their competency to make and vary the direction of movements in unstable environments. It has been shown that when a single reaching movement is repeated in unstable dynamics, the central nervous system (CNS) learns an impedance internal model to compensate for the environment instability. However, there is still no explanation for how humans can learn to move in various directions in such environments. In this study, we investigated whether and how humans compensate for instability while learning two different reaching movements simultaneously. Results show that when performing movements in two different directions, separated by a 35° angle, the CNS was able to compensate for the unstable dynamics. After adaptation, the force was found to be similar to the free movement condition, but stiffness increased in the direction of instability, specifically for each direction of movement. Our findings suggest that the CNS either learned an internal model generalizing over different movements, or alternatively that it was able to switch between specific models acquired simultaneously. © 2008 IEEE.

Differential effects of ageing on the EEG during pentobarbital and ketamine anaesthesia

Background and objectives: Pentobarbital and ketamine are commonly used in animal experiments, including studies on the effects of ageing on the central nervous system. The electroencephalogram is a sensitive measure of brain activity. The present study i

Detour behavior changes associated with prenatal morphine exposure in 11-day-old chicks

The central nervous system exhibits remarkable plasticity in early life. Prenatal morphine exposure may induce adverse behavioral effects on the neonate and the developing offspring. In the present study, we investigated the effect of prenatal morphine exposure (daily from embryonic days 12-16, 20 mg/kg) on 11-day-old chicks using two forms of spatial paradigms: one trial detour behavior task in which animals must bypass an obstacle to reach the desired goal without any training and detour learning task which required several trials of training to reach the detour criterion. The results showed that, on the condition that chicks could successfully detour in the first trial, morphine exposed chicks exhibited longer detour latency to finish the task, coupled by a preference for turning right versus turning left. In contrast, no significant difference in learning and memory was found in detour learning task between morphine exposed chicks and saline chicks. These findings suggest specific behavioral changes associated with prenatal exposure to opioids during mid to late gestation, also raise attention to the possible health hazard from pregnancy drug use in everyday life. (C) 2010 ISDN. Published by Elsevier Ltd. All rights reserved.

Impedance control is selectively tuned to multiple directions of movement

Humans are able to learn tool-handling tasks, such as carving, demonstrating their competency to make movements in unstable environments with varied directions. When faced with a single direction of instability, humans learn to selectively co-contract their arm muscles tuning the mechanical stiffness of the limb end point to stabilize movements. This study examines, for the first time, subjects simultaneously adapting to two distinct directions of instability, a situation that may typically occur when using tools. Subjects learned to perform reaching movements in two directions, each of which had lateral instability requiring control of impedance. The subjects were able to adapt to these unstable interactions and switch between movements in the two directions; they did so by learning to selectively control the end-point stiffness counteracting the environmental instability without superfluous stiffness in other directions. This finding demonstrates that the central nervous system can simultaneously tune the mechanical impedance of the limbs to multiple movements by learning movement-specific solutions. Furthermore, it suggests that the impedance controller learns as a function of the state of the arm rather than a general strategy. © 2011 the American Physiological Society.

Pituitary adenylate cyclase-activating polypeptide

Pituitary adenylate cyclase-activating polypeptide (PACAP) which belongs to the secretin/glucagon/ VIP family has been originally isolated from the sheep hypothalamus on the basis of its ability to stimulate cAMP formation in culture rat anterior pituitary cells. Post-translational processing of the PACAP precursor generates two biologically active molecular forms, PACAP-38 and PACAP-27. The primary structure of PACAP has been remarkably conserved during evolution. The sequence of PACAP-27 exhibits substantial similarities with those of vasoactive intestinal polypeptide (VIP), glucagon and secretin. The gene encoding the PACAP precursor is widely expressed in brain and various peripheral organs, notably in endocrine glands, gastro-intestinal, urogenital tracts and respiratory system. In vivo, and in vitro studies have shown that PACAP exhibits multiple activities especially a trophic activity during ontogenesis, notably in the adrenal medulla and the central nervous system. The biological effects of PACAP are mediated through three distinct receptor subtypes which exhibit differential affinities for PACAP and VIP. The PAC1 receptor, which shows high selectivity for PACAP, is coupled to several transduction systems. In contrast, VPAC1 and VPAC2, which bind with the same affinity for PACAP and VIP, are mainly coupled to the adenylyl cyclase pathway. In conclusion, PACAP is neuropeptide, and it functions as a hypothalamic hormone, neurohormone, neuromodulator, vasodilator, neurotransmitter or trophic factor in the brain and the various organs.

A neuro-inspired method for data rate limited feedback control

The nervous system implements a networked control system in which the plants take the form of limbs, the controller is the brain, and neurons form the communication channels. Unlike standard networked control architectures, there is no periodic sampling, and the fundamental units of communication contain little numerical information. This paper describes a novel communication channel, modeled after spiking neurons, in which the transmitter integrates an input signal and sends out a spike when the integral reaches a threshold value. The reciever then filters the sequence of spikes to approximately reconstruct the input signal. It is shown that for appropriate choices of channel parameters, stable feedback control over these spiking channels is possible. Furthermore, good tracking performance can be achieved. The data rate of the channel increases linearly with the size of the inputs. Thus, when placed in a feedback loop, small loop gains imply a low data rate. ©2010 IEEE.

Functional requirements for reward-modulated spike-timing-dependent plasticity.

Recent experiments have shown that spike-timing-dependent plasticity is influenced by neuromodulation. We derive theoretical conditions for successful learning of reward-related behavior for a large class of learning rules where Hebbian synaptic plasticity is conditioned on a global modulatory factor signaling reward. We show that all learning rules in this class can be separated into a term that captures the covariance of neuronal firing and reward and a second term that presents the influence of unsupervised learning. The unsupervised term, which is, in general, detrimental for reward-based learning, can be suppressed if the neuromodulatory signal encodes the difference between the reward and the expected reward-but only if the expected reward is calculated for each task and stimulus separately. If several tasks are to be learned simultaneously, the nervous system needs an internal critic that is able to predict the expected reward for arbitrary stimuli. We show that, with a critic, reward-modulated spike-timing-dependent plasticity is capable of learning motor trajectories with a temporal resolution of tens of milliseconds. The relation to temporal difference learning, the relevance of block-based learning paradigms, and the limitations of learning with a critic are discussed.