Activation of human arm muscles during flexion/extension and supination/pronation tasks: A theory on muscle coordination

Generally the number of muscles acting across a joint exceeds the number of degrees of freedom available to the joint. This redundancy raises a problem regarding the ratio in which these muscles are activated during a particular motor task. In this paper we present a theory to explain the activation patterns of muscles used during voluntary and reflex induced contractions. The basic assumptions underlying the theory are that 1) coordination of muscles is based on synergistic muscle activities, 2) the synergisms involved satisfy certain transformations of muscle spindle signals to muscle activation signals and 3) muscle spindle output is proportional to the ratio of muscle stretch and muscle length in lengthening muscles, and is zero in shortening muscles. The theory is used to predict the recruitment threshold of motor units in six arm muscles during voluntary isometric contractions. All theoretical predictions are in reasonable agreement with the experimentally observed behavior of a large population of motor units within each muscle. However, within a single muscle sometimes motor-unit populations have been found to have different types of recruitment behavior. This deviating behavior is discussed in the light of the theory presented here.     

A biologically inspired neural net for trajectory formation and obstacle avoidance

In this paper we present a biologically inspired two-layered neural network for trajectory formation and obstacle avoidance. The two topographically ordered neural maps consist of analog neurons having continuous dynamics. The first layer, the sensory map, receives sensory information and builds up an activity pattern which contains the optimal solution (i.e. shortest path without collisions) for any given set of current position, target positions and obstacle positions. Targets and obstacles are allowed to move, in which case the activity pattern in the sensory map will change accordingly. The time evolution of the neural activity in the second layer, the motor map, results in a moving cluster of activity, which can be interpreted as a population vector. Through the feedforward connections between the two layers, input of the sensory map directs the movement of the cluster along the optimal path from the current position of the cluster to the target position. The smooth trajectory is the result of the intrinsic dynamics of the network only. No supervisor is required. The output of the motor map can be used for direct control of an autonomous system in a cluttered environment or for control of the actuators of a biological limb or robot manipulator. The system is able to reach a target even in the presence of an external perturbation. Computer simulations of a point robot and a multi-joint manipulator illustrate the theory.     

Identification of the nonlinear state-space dynamics of the action-perception cycle for visually induced postural sway

Human subjects standing in a sinusoidally moving visual environment display postural sway with characteristic dynamical properties. We analyzed the spatiotemporal properties of this sway in an experiment in which the frequency of the visual motion was varied. We found a constant gain near 1, which implies that the sway motion matches the spatial parameters of the visual motion for a large range of frequencies. A linear dynamical model with constant parameters was compared quantitatively with the data. Its failure to describe correctly the spatiotemporal properties of the system led us to consider adaptive and nonlinear models. To differentiate between possible alternative structures we directly fitted nonlinear differential equations to the sway and visual motion trajectories on a trial-by-trial basis. We found that the eigenfrequency of the fitted model adapts strongly to the visual motion frequency. The damping coefficient decreases with increasing frequency. This indicates that the system destabilizes its postural state in the inertial frame. This leads to a faster internal dynamics which is capable of synchronizing posture with fast-moving visual environments. Using an algorithm which allows the identification of essentially nonlinear terms of the dynamics we found small nonlinear contributions. These nonlinearities are not consistent with a limit-cycle dynamics, accounting for the robustness of the amplitude of postural sway against frequency variations. We interpret our results in terms of active generation of postural sway specified by sensory information. We derive also a number of conclusions for a behavior-oriented analysis of the postural system.     

Structural rearrangements of NR1/NR2A NMDA receptors during allosteric inhibition

Ionotropic glutamate receptor (iGluR) subunits contain a large N-terminal domain (NTD) that precedes the agonist-binding domain (ABD) and participates in subunit oligomerization. In NMDA receptors (NMDARs), the NTDs of NR2A and NR2B subunits also form binding sites for the endogenous inhibitor Zn(2+) ion. Although these allosteric sites have been characterized in detail, the molecular mechanisms by which the NTDs communicate with the rest of the receptor to promote its inhibition remain unknown. Here, we identify the ABD dimer interface as a major structural determinant that permits coupling between the NTDs and the channel gate. The strength of this interface also controls proton inhibition, another form of allosteric modulation of NMDARs. Conformational rearrangements at the ABD dimer interface thus appear to be a key mechanism conserved in all iGluR subfamilies, but have evolved to fulfill different functions: fast desensitization at AMPA and kainate receptors, allosteric inhibition at NMDARs.