Theoretical and Computational Neuroscience Program
The Program supports research on the development and application of realistic models for the analysis and understanding of brain function. Project areas include empirical and theoretical studies of self-organizing behavior in neuronal systems, mathematical approaches to modeling non-stationary neuronal processes, functional imaging of dynamical processes, and the modeling of all levels of neuronal processing, from single cell activity to complex behaviors. Grant applications are encouraged for research projects combining mathematical and computational tools with neurophysiological, neuroanatomical, or neurochemical techniques in order to decipher the mechanisms underlying specific neuronal and behavioral systems. This program also supports research projects focusing on understanding the computations made by nerve cells and groups of nerve cells in orchestrating behaviors.
Areas of Emphasis
- Creating biologically realistic computational models of neural processes underlying all aspects of brain activity - from single cells to networks to systems to behavior.
- Understanding how individual differences in neuronal activity (variability) are involved in the transmission and processing of information in the central nervous system.
- Measuring the associations among neurons and establishing a theoretical basis, rationale, and validation for spike sorting procedures.
- Enhancing the analysis and interpretation of local field potentials both in conjunction with and apart from neural spike train data.
Dennis L. Glanzman, Ph.D.
6001 Executive Boulevard, Room 7192, MSC 9637