Integrated Calendar

Behavioral and theoretical studies have focused on identifying the kinematic and temporal characteristics of various movements ranging from simple reaching to complex 2D and 3D drawing and curved motions. These kinematic and temporal features are quite instrumental in investigating the organizing principles that underlie trajectory formation. Similar kinematic constraints play also a critical role in visual perception of abstract as well as biological motion stimuli and in action recognition. In my talk I will review the results of recent studies showing that 2D and 3D movements might be represented in terms of non-Euclidian metrics. I will also present a recent extension of these studies leading to a new theory which suggests that movement duration, invariance, and compositionality may arise from cooperation among several geometries. The theory has led to concrete predictions which were corroborated by the kinematic and temporal features of both drawing and locomotion trajectories. Finally I will discuss the findings of several behavioral and brain mapping studies aiming at identifying the neural correlates of the suggested organizing principles.

A stable open queuing network is considered as a steady non-equilibrium system of interacting particles. The network is completely specified by its underlying graphical structure, type of interaction at each node, and the Poisson transition rates between nodes. For such systems we identify two regimes in which the system may operate depending on the value of currents accumulated on the graph edges over time, large compared to the system correlation time scale. In the first regime of moderate currents, the large-deviation distribution of currents is universal (independent of the interaction details), and the system behaves in an "uncongested" mode. In the second regime of larger currents, the large-deviation current distribution is sensitive to interaction details, and the system is in a "congested" mode. the transition between the two regimes can be described as a dynamical second order phase transition. We illustrate these ideas using a simple, yet non-trivial, example of a single node with feedback.