www.iitm.ac.inWe present a computational model of basal ganglia as a key player in exploratory behavior. The model describes exploration of a virtual rat in a simulated water pool experiment. The virtual rat is trained using a reward-based or reinforcement learning paradigm which requires units with stochastic behavior for exploration of the system's state space. We model the Subthalamic Nucleus-Globus Pallidus externa (STN-GPe) segment of the basal ganglia as a pair of neuronal layers with oscillatory dynamics, exhibiting a variety of dynamic regimes such as chaos, traveling waves and clustering. Invoking the property of chaotic systems to explore state-space, we suggest that the complex exploratory dynamics of STN-GPe system in conjunction with dopamine-based reward signaling from the Substantia Nigra pars compacta (SNc) present the two key ingredients of a reinforcement learning system.
The phenomenon of systematic recruitment of motor units with increasing demand load is usually explained by the size principle. Though this principle successfully explains the gain-related aspects of muscle force generation, it does not address the need for desynchronization of motor unit activities in order to produce a smooth tension profile at the level of whole muscle, while individual muscle fibers are "twitching." We propose an oscillator model of motor neurons in which a pool of motor neurons fires a bundle of muscle fibers. Although individual muscle fibers have a complicated tension profile, the tension produced by the entire bundle is regulated and follows a command signal accurately. This is shown to be possible because of uncorrelated activity produced by local inhibitory connections among motor neurons. Connections that produce synchronized oscillations result in uncontrolled contractions of the muscle. These results seem to suggest that while synchronized activity indicates pathology and disease, desynchronized activity is the precondition for normal muscle function. Physiological evidence for the proposed theory of motor unit synchronization is presented.
In this article Figs. 4a and 4b (trajectories taken by the rat when the platform is within initial visual range) appeared as identical. The correct Fig. 4b
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