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NJIT Mathematical Biology Seminar

Tuesday, February 7, 2006, 4:00 pm
Cullimore Hall 611
New Jersey Institute of Technology

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Predicting the Environment from CNS Dynamics

Alex Proekt

Department of Physiology and Biophysics
Mount Sinai School of Medicine

Sensory stimuli do not directly determine the behavior - the internal state of the nervous system intervenes. The dynamical properties of this state could be conceptualized as an internal model of the environment. If so, we may expect these dynamical properties to reflect the structure of the environment in which the animal has evolved to act. It should then be possible given the dynamical properties of the internal state of the CNS to predict the features of the environment to which they are adapted. Here, we describe experiments that characterize the dynamical properties of the internal state that governs the expression of feeding behaviors of Aplysia and a model of these results in which we are attempting such a prediction. By extrapolating from the previous history, the dynamics of the internal state embody an expectation of what will be the next appropriate action. To be adaptive this expectation has to be correct (i.e. reflect the true structure of the environment). To uncover this structure, we simulate the behavior of the model in various environments to find the structure of the environment that maximizes the performance of the model.