title: Temporal processing in the visual brain.
abstract: In conclusion these three results taken together--the single-unit data, the Gerstein and Mandelbrot model, and the modeled collection of neurons--suggest that the analysis of the temporal dynamics of neural systems can be furthered by the application of nonlinear dynamical theory. Furthermore, it appears that the range of temporal dynamics possible in visual cortex is quite broad, encompassing simple oscillations and more complex, perhaps chaotic, dynamics. Lastly, it appears that there are powerful principles at work that are leading to the organized behavior of a population of neurons. We suggest that these principles are constrained not only by the biological properties of the nervous system, but by profound mathematical principles that have already been described in many physical nonlinear systems under the aegis of chaos theory. If such constraints exist, we may have available to us mathematical and physical constructs that will allow us to study, model, and predict the behaviors of large collections of neurons that ultimately underlie the neural functioning of the brain.
authors.affiliation: Center for Molecular and Behavioral Neuroscience, Rutgers University, Newark, New Jersey 07102.
authors.forename: R M
authors.initials: RM
authors.lastname: Siegel
authors.forename: H L
authors.initials: HL
authors.lastname: Read
mesh_terms: D000200:Action Potentials / Q000502:physiology; D000818:Animals; D002415:Cats; D005260:Female; D008297:Male; D008959:Models, Neurological; D009431:Neural Conduction / Q000502:physiology; D013028:Space Perception / Q000502:physiology; D014793:Visual Cortex / Q000502:physiology*; D014796:Visual Perception / Q000502:physiology*