Tibialis posterior in health and disease: a review of structure and function with specific reference to electromyographic studies

Tibialis posterior has a vital role during gait as the primary dynamic stabiliser of the medial longitudinal arch; however, the muscle and tendon are prone to dysfunction with several conditions. We present an overview of tibialis posterior muscle and tendon anatomy with images from cadaveric work on fresh frozen limbs and a review of current evidence that define normal and abnormal tibialis posterior muscle activation during gait. A video is available that demonstrates ultrasound guided intra-muscular insertion techniques for tibialis posterior electromyography

Temporal-Difference Reinforcement Learning with Distributed Representations

Temporal-difference (TD) algorithms have been proposed as models of reinforcement learning (RL). We examine two issues of distributed representation in these TD algorithms: distributed representations of belief and distributed discounting factors. Distributed representation of belief allows the believed state of the world to distribute across sets of equivalent states. Distributed exponential discounting factors produce hyperbolic discounting in the behavior of the agent itself. We examine these issues in the context of a TD RL model in which state-belief is distributed over a set of exponentially-discounting “micro-Agents”, each of which has a separate discounting factor (γ). Each µAgent maintains an independent hypothesis about the state of the world, and a separate value-estimate of taking actions within that hypothesized state. The overall agent thus instantiates a flexible representation of an evolving world-state. As with other TD models, the value-error (δ) signal within the model matches dopamine signals recorded from animals in standard conditioning reward-paradigms. The distributed representation of belief provides an explanation for the decrease in dopamine at the conditioned stimulus seen in overtrained animals, for the differences between trace and delay conditioning, and for transient bursts of dopamine seen at movement initiation. Because each µAgent also includes its own exponential discounting factor, the overall agent shows hyperbolic discounting, consistent with behavioral experiments

Short-term parasite-infection alters already the biomass, activity and functional diversity of soil microbial communities

Native parasitic plants may be used to infect and control invasive plants. We established microcosms with invasive Mikania micrantha and native Coix lacryma-jobi growing in mixture on native soils, with M. micrantha being infected by parasitic Cuscuta campestris at four intensity levels for seven weeks to estimate the top-down effects of plant parasitism on the biomass and functional diversity of soil microbial communities. Parasitism significantly decreased root biomass and altered soil microbial communities. Soil microbial biomass decreased, but soil respiration increased at the two higher infection levels, indicating a strong stimulation of soil microbial metabolic activity (+180%). Moreover, a Biolog assay showed that the infection resulted in a significant change in the functional diversity indices of soil microbial communities. Pearson correlation analysis indicated that microbial biomass declined significantly with decreasing root biomass, particularly of the invasive M. micrantha. Also, the functional diversity indices of soil microbial communities were positively correlated with soil microbial biomass. Therefore, the negative effects on the biomass, activity and functional diversity of soil microbial community by the seven week long plant parasitism was very likely caused by decreased root biomass and root exudation of the invasive M. micrantha

When Artificial Intelligence and Computational Neuroscience Meet

International audienceComputational Intelligence and Artificial Intelligence are both aiming at building machines and softwares capable of intelligent behavior. They are consequently prone to interactions, even if the latter is not necessarily interested in understanding how cognition emerges from the brain substrate. In this chapter, we enumerate, describe and discuss the most important fields of interactions. Some are methodological and are concerned with information representation, processing and learning. At the functional level, the focus is set on major cognitive functions like perception, navigation, decision making and language. Among the salient characteristics of the critical contributions of Computational Neuroscience to the development of intelligent systems, its systemic view of the cerebral functioning is particularly precious to model highly multimodal cognitive functions like decision makin