Physiological control systems can display a specific type of reversible transition in behavior called bifurcations. Bifurcations can occur between steady states, periodic oscillations and chaotic dynamics. It has been suggested that these transitions in behavior constitute a common dynamical mechanism for several clinically observed failures of physiological regulation. A specific possibility has motivated this study: could a bifurcation be an early event in epileptogenesis? This investigation proposes to continue both theoretical and experimental studies of bifurcations in neural behavior, with specific reference to epileptogenesis. Theoretical work has focused on developing methods for the quantitative characterization of complex dynamical behavior. As the work progressed, the limitations of currently available procedures, especially for dealing with noisy experimental data, became increasingly apparent. Our theoretical work is, therefore, directed to improving these techniques and to constructing alternative measures of dynamical behavior. It includes Lyapunov exponents, correlation dimension and its generalizations to order-q information dimension, topological dimension, metric entropy, topological entropy and complexity. The experimental work will be directed toward establishing a dynamical characterization of focal epileptogenesis in an animal model and to enlarging our data base to include measures under normal (free moving) as well as seizure conditions. To this end we shall record the ECoG and the firing patterns in single cortical neurons. In particular, we wish to identify conditions which can precipitate bifurcations in dynamical behavior that result in seizures.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS019716-07
Application #
3399819
Study Section
Special Emphasis Panel (SSS (F))
Project Start
1983-07-01
Project End
1993-08-31
Budget Start
1991-09-01
Budget End
1992-08-31
Support Year
7
Fiscal Year
1991
Total Cost
Indirect Cost
Name
Allegheny University of Health Sciences
Department
Type
Schools of Medicine
DUNS #
City
Philadelphia
State
PA
Country
United States
Zip Code
19129
Rapp, P E; Schmah, T (1996) Complexity measures in molecular psychiatry. Mol Psychiatry 1:408-16
Theiler, J; Rapp, P E (1996) Re-examination of the evidence for low-dimensional, nonlinear structure in the human electroencephalogram. Electroencephalogr Clin Neurophysiol 98:213-22
Rapp, P E (1994) A guide to dynamical analysis. Integr Physiol Behav Sci 29:311-27
Farwell, L A; Martinerie, J M; Bashore, T R et al. (1993) Optimal digital filters for long-latency components of the event-related brain potential. Psychophysiology 30:306-15
Rapp, P E; Bashore, T R; Martinerie, J M et al. (1989) Dynamics of brain electrical activity. Brain Topogr 2:99-118
Zimmerman, I D; Rapp, P E (1989) Saltatory transitions are a naturally occurring property of evolving systems. Biol Cybern 62:167-75
Rapp, P E; Latta, R A; Mees, A I (1988) Parameter-dependent transitions and the optimal control of dynamical diseases. Bull Math Biol 50:227-53
Rapp, P E (1987) Why are so many biological systems periodic? Prog Neurobiol 29:261-73
Rapp, P E (1985) Communication and control in reproduction: the ubiquity of periodic phenomena. Biol Reprod 32:70-2