Contrasted Antibiotics and Pesticides Occurrence in Fish Exposed In Situ to Urban Effluents: A 20-Day Caging Experiment.

Urban freshwater ecosystems receive a wide array of organic pollutants through wastewater-treatment plant (WWTP) discharges and agricultural runoff. Evaluating the fate and effects of antibiotics and pesticides can be a challenging task, especially the effects on freshwater vertebrates because of their abilities to metabolize and excrete these chemicals and because of their high mobility and escape behavior when exposed to stressful environmental conditions. In the present study, 37 wild gudgeons (Gobio gobio) were caged for a period of up to 20 days, upstream and downstream of a WWTP effluent discharge in the Orge River (a tributary of the Seine River, France).

Wild fish from a highly urbanized river (Orge, France) as vectors of culturable resistant to antibiotics.

This study shows how wild fishes from urbanized rivers could be involved in the spread of antibiotic-resistant . Antibiotic resistance profiles and molecular detection of clinical integron (1) were carried out on 105 isolated from 89 wildfish (skin or gut) belonging to 8 species. The proportion of isolates resistant to at least one antibiotic was independent of fish species and reached 28.

What is the nature of motor adaptation to dynamic perturbations?

When human participants repeatedly encounter a velocity-dependent force field that distorts their movement trajectories, they adapt their motor behavior to recover straight trajectories. Computational models suggest that adaptation to a force field occurs at the action selection level through changes in the mapping between goals and actions. The quantitative prediction from these models indicates that early perturbed trajectories before adaptation and late unperturbed trajectories after adaptation should have opposite curvature, i.

Trace organic contaminants within solid matrices along an anthropized watercourse: Organo-mineral controls on their spatial distribution.

Although numerous studies have determined significant contamination in terms of trace organic contaminant (TrOC) diversity and concentration, the occurrence of TrOCs within solid matrices as suspended solids and sediments flies under the radar. In this study, the occurrence of 35 TrOCs of various classes (i.e.

A computational theory for the production of limb movements.

Motor control is a fundamental process that underlies all voluntary behavioral responses. Several different theories based on different principles (task dynamics, equilibrium-point theory, passive-motion paradigm, active inference, optimal control) account for specific aspects of how actions are produced, but fail to provide a unified view on this problem. Here, we propose a concise theory of motor control based on three principles: optimal feedback control, control with a receding time horizon, and task representation by a series of via-points updated at fixed frequency.

Record of trace organic contaminants in a river sediment core: From historical wastewater management to historical use.

Some trace organic contaminants (TrOCs) can be considered as ubiquitous contaminants since the 1950s, and the study of their historical distribution within river sediments allows us to better understand the temporal variation of the chemical quality of sediments, and make assumptions about the most insightful forcings impacting these distributions. In this study, the occurrence of 41 TrOCs of various classes (i.e.

Urbanization Constrains Skin Bacterial Phylogenetic Diversity in Wild Fish Populations and Correlates with the Proliferation of Aeromonads.

Changes in the state of rivers resulting from the activity and expansion of urban areas are likely to affect aquatic populations by increasing stress and disease, with the microbiota playing a potentially important intermediary role. Unraveling the dynamics of microbial flora is therefore essential to better apprehend the impact of anthropogenic disturbances on the health of host populations and the ecological integrity of hydrosystems. In this context, the present study simultaneously examined changes in the microbial communities associated with mucosal skin and gut tissues of eight fish species along an urbanization gradient in the Orge River (France).

Modulation of ellipses drawing by sonification.

Most studies on the regulation of speed and trajectory during ellipse drawing have used visual feedback. We used online auditory feedback (sonification) to induce implicit movement changes independently from vision. The sound was produced by filtering a pink noise with a band-pass filter proportional to movement speed.

Toward a motor signature in autism: Studies from human-machine interaction.

Background: Autism spectrum disorder (ASD) is a heterogeneous group of neurodevelopmental disorders which core symptoms are impairments in socio-communication and repetitive symptoms and stereotypies. Although not cardinal symptoms per se, motor impairments are fundamental aspects of ASD. These impairments are associated with postural and motor control disabilities that we investigated using computational modeling and developmental robotics through human-machine interaction paradigms.

Modifying upper-limb inter-joint coordination in healthy subjects by training with a robotic exoskeleton.

Background: The possibility to modify the usually pathological patterns of coordination of the upper-limb in stroke survivors remains a central issue and an open question for neurorehabilitation. Despite robot-led physical training could potentially improve the motor recovery of hemiparetic patients, most of the state-of-the-art studies addressing motor control learning, with artificial virtual force fields, only focused on the end-effector kinematic adaptation, by using planar devices. Clearly, an interesting aspect of studying 3D movements with a robotic exoskeleton, is the possibility to investigate the way the human central nervous system deals with the natural upper-limb redundancy for common activities like pointing or tracking tasks.

Balancing out dwelling and moving: optimal sensorimotor synchronization.

Sensorimotor synchronization is a fundamental skill involved in the performance of many artistic activities (e.g., music, dance).

A model of reward- and effort-based optimal decision making and motor control.

Costs (e.g. energetic expenditure) and benefits (e.

A computational model of use-dependent motor recovery following a stroke: optimizing corticospinal activations via reinforcement learning can explain residual capacity and other strength recovery dynamics.

This paper describes a computational model of use-dependent recovery of movement strength following a stroke. The model frames the problem of strength recovery as that of learning appropriate activations of residual corticospinal neurons to their target motoneuronal pools. For example, for an agonist/antagonist muscle pair, we assume the motor system must learn to activate preserved agonist-exciting corticospinal neurons and deactivate preserved antagonist-exciting corticospinal neurons.

Dendritic signals command firing dynamics in a mathematical model of cerebellar Purkinje cells.

Dendrites of cerebellar Purkinje cells (PCs) respond to brief excitations from parallel fibers with lasting plateau depolarizations. It is unknown whether these plateaus are local events that boost the synaptic signals or they propagate to the soma and directly take part in setting the cell firing dynamics. To address this issue, we analyzed a likely mechanism underlying plateaus in three representations of a reconstructed PC with increasing complexity.

Active control of bias for the control of posture and movement.

Posture and movement are fundamental, intermixed components of motor coordination. Current approaches consider either that 1) movement is an active, anticipatory process and posture is a passive feedback process or 2) movement and posture result from a common passive process. In both cases, the presence of a passive component renders control scarcely robust and stable in the face of transmission delays and low feedback gains.

Do robotic and non-robotic arm movement training drive motor recovery after stroke by a common neural mechanism? Experimental evidence and a computational model.

Different dose-matched, upper extremity rehabilitation training techniques, including robotic and non-robotic techniques, can result in similar improvement in movement ability after stroke, suggesting they may elicit a common drive for recovery. Here we report experimental results that support the hypothesis of a common drive, and develop a computational model of a putative neural mechanism for the common drive. We compared weekly motor control recovery during robotic and unassisted movement training techniques after chronic stroke (n = 27), as assessed with quantitative measures of strength, speed, and coordination.

Computational motor control: feedback and accuracy.

Speed/accuracy trade-off is a ubiquitous phenomenon in motor behaviour, which has been ascribed to the presence of signal-dependent noise (SDN) in motor commands. Although this explanation can provide a quantitative account of many aspects of motor variability, including Fitts' law, the fact that this law is frequently violated, e.g.

Optimality, stochasticity, and variability in motor behavior.

Recent theories of motor control have proposed that the nervous system acts as a stochastically optimal controller, i.e. it plans and executes motor behaviors taking into account the nature and statistics of noise.

A new principle for information storage in an enzymatic pathway model.

Strong experimental evidence indicates that protein kinase and phosphatase (KP) cycles are critical to both the induction and maintenance of activity-dependent modifications in neurons. However, their contribution to information storage remains controversial, despite impressive modeling efforts. For instance, plasticity models based on KP cycles do not account for the maintenance of plastic modifications.

Coding of movement- and force-related information in primate primary motor cortex: a computational approach.

Coordinated movements result from descending commands transmitted by central motor systems to the muscles. Although the resulting effect of the commands has the dimension of a muscular force, it is unclear whether the information transmitted by the commands concerns movement kinematics (e.g.

Persistent toxic substance inputs to the river Seine basin (France) via atmospheric deposition and urban sludge application.

Paris constitutes a major direct and indirect source of persistent toxic substances (PTS) to the river Seine, its tributaries and its basin, by atmospheric depositions and sewage sludge land-filling. The contaminant cycle and transfer pathways were investigated from 1999 to 2003 at local and inter regional scales in order to determine the respective importance of the main input and diffusion processes (wastewater, rainwater and runoff) from urban to rural areas. Paris constitutes an atmospheric emission hot spot for PAHs and PCBs.

Computational motor control: redundancy and invariance.

The nervous system controls the behavior of complex kinematically redundant biomechanical systems. How it computes appropriate commands to generate movements is unknown. Here we propose a model based on the assumption that the nervous system: 1) processes static (e.

Supervised learning in a recurrent network of rate-model neurons exhibiting frequency adaptation.

For gradient descent learning to yield connectivity consistent with real biological networks, the simulated neurons would have to include more realistic intrinsic properties such as frequency adaptation. However, gradient descent learning cannot be used straightforwardly with adapting rate-model neurons because the derivative of the activation function depends on the activation history. The objectives of this study were to (1) develop a simple computational approach to reproduce mathematical gradient descent and (2) use this computational approach to provide supervised learning in a network formed of rate-model neurons that exhibit frequency adaptation.

Interpolation and extrapolation in human behavior and neural networks.

Unlike most artificial systems, the brain is able to face situations that it has not learned or even encountered before. This ability is not in general echoed by the properties of most neural networks. Here, we show that neural computation based on least-square error learning between populations of intensity-coded neurons can explain interpolation and extrapolation capacities of the nervous system in sensorimotor and cognitive tasks.