Attentional modulation of neural responses to action observation: Implications for models of the human 'mirror' system

In primates, the observation of meaningful, goaldirected actions engages a network of cortical areas located within the premotor and inferior parietal lobules. Current models suggest that activity within these regions arises relatively automatically during passive action observation without the need for topdown control. Here we used functional magnetic resonance imaging to determine whether cortical activit)' associated with action observation is modulated by the strategic allocation of selective attention. Normal observers viewed movie clips of reach-to-grasp actions while performing an easy or difficult visual discrimination at the fovea. A wholebrain analysis was performed to determine the effects of attentional load on neural responses to observed hand actions. Our results suggest that cortical areas involved in action observation are significantiy modulated by attentional load. These findings have important implications for recent attempts to link the human action-observation system to response properties of "mirror neurons" in monkeys.

Genetic basis of the formation and identity of type I and type II neurons in Drosophila embryos

The embryonic peripheral nervous system of Drosophila contains two main types of sensory neurons: type I neurons, which innervate external sense organs and chordotonal organs, and type II multidendritic neurons, Here, we analyse the origin of the difference between type I and type II in the case of the neurons that depend on the proneural genes of the achaete-scute complex (ASC), We show that, in Notch(-) embryos, the type I neurons are missing while type nr neurons are produced in excess, indicating that the type I/type II choice relies on Notch-mediated cell communication, In contrast, both type I and type II neurons are absent in numb(-) embryos and after ubiquitous expression of tramtrack, indicating that the activity of numb and the absence of tramtrack are required to produce both external sense organ and multidendritic neural fates, The analysis of string(-) embryos reveals that when the precursors are unable to divide they differentiate mostly into type II neurons, indicating that the type II is the default neuronal fate, We also report a new mutant phenotype where the ASC-dependent neurons are converted into-type II neurons, providing evidence for the existence of one or more genes required for maintaining the alternative (type I) fate, Our results suggest that the same mechanism of type I/type II specification may operate at a late step of the ASC-dependent lineages, when multidendritic neurons arise as siblings of the external sense organ neurons and, at an early step, when other multidendritic neurons precursors arise as siblings of external sense organ precursors.

Major histocompatibility complex (MHC) class II-positive dendritic cells in the rat iris - In situ development from MHC class II-negative precursors

Purpose. To examine the postnatal development of major histocompatibility complex (MHC) class II-positive dendritic cells (DC) in the iris of the normal rat eye. Methods. Single-and double-color immunomorphologic studies were performed on whole mounts prepared from rat iris taken at selected postnatal ages (2 to 3 days to 78 weeks). Immunopositive cells were enumerated, using a quantitative light microscope, and MHC class II expression on individual cells was assessed by microdensitometric analysis. Results. Major histocompatibility class II-positive DCs in the iris developed in an age-dependent manner and reached adult-equivalent density and structure at approximately 10 weeks of age, considerably later than previously described in other DC populations in the rat. In contrast, the anti-rat DC monoclonal antibody OX62 revealed a population of cells present at adult-equivalent levels as early as 3 weeks after birth. Dual-color immunostaining and microdensitometric analysis demonstrated that during postnatal growth, development of the network of MHC class II-positive DCs was a consequence of the progressive increase in expression of MHC class II antigen by OX62-positive cells. Conclusions. During postnatal growth, the DC population of the iris develops initially as an OX62-positive-MHC class II-negative population, which then develops increasing MHC class II expression in situ and finally resembles classic DC populations in other tissue sites. Maturation of the iris DC population is temporally delayed compared with time to maturation in other tissue sites in the rat.

Advanced precursors in marine biosynthetic study. Part 2: The biosynthesis of isocyanides and isothiocyanates in the tropical marine sponge Axinyssa n.sp.

The biosynthetic origins of the isocyanide and isothiocyanate groups in 9-isocyanop upukeanane (2) and 9-isothiocyanato-pupukeanane (3) are investigated by incorporation of [C-14]-labelled advanced precursors into the sponge Axinyssa n.sp. (C) 2001 Elsevier Science Ltd. All rights reserved.

An adaptive neural-wavelet model for short term load forecasting

This paper proposed a novel model for short term load forecast in the competitive electricity market. The prior electricity demand data are treated as time series. The forecast model is based on wavelet multi-resolution decomposition by autocorrelation shell representation and neural networks (multilayer perceptrons, or MLPs) modeling of wavelet coefficients. To minimize the influence of noisy low level coefficients, we applied the practical Bayesian method Automatic Relevance Determination (ARD) model to choose the size of MLPs, which are then trained to provide forecasts. The individual wavelet domain forecasts are recombined to form the accurate overall forecast. The proposed method is tested using Queensland electricity demand data from the Australian National Electricity Market. (C) 2001 Elsevier Science B.V. All rights reserved.

Neural adaptations to resistance training - Implications for movement control

It has long been believed that resistance training is accompanied by changes within the nervous system that play an important role in the development of strength. Many elements of the nervous system exhibit the potential for adaptation in response to resistance training, including supraspinal centres, descending neural tracts, spinal circuitry and the motor end plate connections between motoneurons and muscle fibres. Yet the specific sites of adaptation along the neuraxis have seldom been identified experimentally, and much of the evidence for neural adaptations following resistance training remains indirect. As a consequence of this current lack of knowledge, there exists uncertainty regarding the manner in which resistance training impacts upon the control and execution of functional movements. We aim to demonstrate that resistance training is likely to cause adaptations to many neural elements that are involved in the control of movement, and is therefore likely to affect movement execution during a wide range of tasks. We review a small number of experiments that provide evidence that resistance training affects the way in which muscles that have been engaged during training are recruited during related movement tasks. The concepts addressed in this article represent an important new approach to research on the effects of resistance training. They are also of considerable practical importance, since most individuals perform resistance training in the expectation that it will enhance their performance in-related functional tasks.

Neural influences on sprint running - Training adaptations and acute responses

Performance in sprint exercise is determined by the ability to accelerate, the magnitude of maximal velocity and the ability to maintain velocity against the onset of fatigue. These factors are strongly influenced by metabolic and anthropometric components. Improved temporal sequencing of muscle activation and/or improved fast twitch fibre recruitment may contribute to superior sprint performance. Speed of impulse transmission along the motor axon may also have implications on sprint performance. Nerve conduction velocity (NCV) has been shown to increase in response to a period of sprint training. However, it is difficult to determine if increased NCV is likely to contribute to improved sprint performance. An increase in motoneuron excitability, as measured by the Hoffman reflex (H-reflex), has been reported to produce a more powerful muscular contraction, hence maximising motoneuron excitability would be expected to benefit sprint performance. Motoneuron excitability can be raised acutely by an appropriate stimulus with obvious implications for sprint performance. However, at rest reflex has been reported to be lower in athletes trained for explosive events compared with endurance-trained athletes. This may be caused by the relatively high, fast twitch fibre percentage and the consequent high activation thresholds of such motor units in power-trained populations. In contrast, stretch reflexes appear to be enhanced in sprint athletes possibly because of increased muscle spindle sensitivity as a result of sprint training. With muscle in a contracted state, however, there is evidence to suggest greater reflex potentiation among both sprint and resistance-trained populations compared with controls. Again this may be indicative of the predominant types of motor units in these populations, but may also mean an enhanced reflex contribution to force production during running in sprint-trained athletes. Fatigue of neural origin both during and following sprint exercise has implications with respect to optimising training frequency and volume. Research suggests athletes are unable to maintain maximal firing frequencies for the full duration of, for example, a 100m sprint. Fatigue after a single training session may also have a neural manifestation with some athletes unable to voluntarily fully activate muscle or experiencing stretch reflex inhibition after heavy training. This may occur in conjunction with muscle damage. Research investigating the neural influences on sprint performance is limited. Further longitudinal research is necessary to improve our understanding of neural factors that contribute to training-induced improvements in sprint performance.

Probabilistic modelling of CO2 corrosion laboratory data using neural networks

The present paper addresses two major concerns that were identified when developing neural network based prediction models and which can limit their wider applicability in the industry. The first problem is that it appears neural network models are not readily available to a corrosion engineer. Therefore the first part of this paper describes a neural network model of CO2 corrosion which was created using a standard commercial software package and simple modelling strategies. It was found that such a model was able to capture practically all of the trends noticed in the experimental data with acceptable accuracy. This exercise has proven that a corrosion engineer could readily develop a neural network model such as the one described below for any problem at hand, given that sufficient experimental data exist. This applies even in the cases when the understanding of the underlying processes is poor. The second problem arises from cases when all the required inputs for a model are not known or can be estimated with a limited degree of accuracy. It seems advantageous to have models that can take as input a range rather than a single value. One such model, based on the so-called Monte Carlo approach, is presented. A number of comparisons are shown which have illustrated how a corrosion engineer might use this approach to rapidly test the sensitivity of a model to the uncertainities associated with the input parameters. (C) 2001 Elsevier Science Ltd. All rights reserved.