Analog Neural Networks : Computational Power

Super-Turing Computation

Analog Computation and Dynamical Systems

Genetic Networks : Analog Computation and Artificial Design

Machine Learning: Data Clustering, Active Information Retrieval, Neural Networks and Applications

Circadian System and Jetlag

Perception, Memory and Decision Making

Circadian System and Jetlag

Tissues throughout the body exhibit circadian rhythms, forming a multi-oscillatory system whose disruption results in jet lag and other health problems in travelers and rotational shift workers. With T. Leise I designed a model of the circadian system based on data gathered from a number of studies of rats. The model's parameters take into account the system's hierarchical nature with and downstream from the SCN, the electrophysiological and behavioral animal data following re-entrainment, and the differences in natural circadian times in different organs e.g. liver, lungs, etc. Our simulations of the dynamics of a multistage circadian system reveal the flexibility and stability inherent in a multistage system, as well as potential pitfalls. The modeling predicts that jet lag tends to be most severe following an eastward change of 5-8 time zones due to prolonged desynchrony of the system. This desynchrony is partly due to differing re-entrainment rates among components which follow the SCN command to change their pick times, but a much greater source of desynchrony is the antidromic reentrainment of some but not all organs, where they follow the advance of the SCN in time by delaying their activity all the way around the circle to the other direction. Such antidromic reentrainment can be triggered by the overshoot of the master pacemaker's phase in response to large advances. Based on the multistage system dynamics, we design a simple protocol that results in a more orderly transition that avoids antidromic reentrainment in all components, thereby reducing the re-entrainment time from nearly two weeks to just a few days for the most difficult shifts. We compare the predicted behavior of damped versus robust oscillatory components in the system, as well as the effect of weak versus strong coupling from the master pacemaker to the peripheral components. This work has attracted much attention in the general media, see here.

In another work with student W. Bush what communication facilitates the synchronization of individual cells of the suprachiasmatic nucleus (SCN). One possibility is that firing rate is being used to communicate phase. Indeed neurons of the SCN exhibit a circadian rhythm in firing rate as well as protein expression, but it is not known exactly how these two rhythms interact. With student Will Bush we showed that in order for a population of SCN based oscillators to synchronize, it is sufficient that the oscillators have two properties. First, that the firing rate of the oscillator be driven by protein levels of the molecular clock. And second, that firing rate inputs to a cell can phase shift a molecular clock in the appropriate direction through the production rate of mRNA. We demonstrate that these interactions are sufficient to generate synchronous oscillation. This falsifiable theory suggests a way to facilitate the affect of gene networks and neurons firing and call for relevant experiments.


W. Bush and H.T. Siegelmann,"Circadian syncrhonicity in Networks of Proteim Rhythm Driven Neurons" Complexity Volume 12, Issue 1 (September/October 2006) 67-72.

T. Leise and H Siegelmann, "Dynamics of a multistage circadian system," Journal of Biological Rhythms, August, 21:4 (2006), 314-323