SPECIFIC AIMS The overall goal of this project is to develop a better understanding and improved quantitative characterization of the complex dynamics that result from abnormal regulation of the respiratory, cardiovascular and metabolic control systems in important chronic diseases or clinical syndromes, such as hypertension. Type 2 diabetes, sickle cell disease, metabolic syndrome, and sleep disordered breathing (SDB). These problems will be addressed by employing a combination of structured (""""""""parametric"""""""") modeling and minimal (""""""""non-parametric"""""""") modeling approaches that we have successfully applied in previous cycles of this grant. The proposed project will build on the work that has been accomplished in the current funding cycle, addressing several important issues that remain unresolved and extending our modeiing efforts to more clinical applications. There are three major emphases in our proposed studies. The first pertains to developing models that can characterize the dynamics of the interactions among the participating physiological control systems (eg. respiratory, cardiovascular, metabolic and renal) as they are altered with time because of disease progression or therapy. The second lends recognition to the fact that the vast majority of computational models of human physiology (and pathophysiology) have been designed with the adult forms of the disorder or disease under study;in the next cycle, we will devote significant effort to developing models that pertain more specifically to the pediatric manifestations of these multi-factor disorders. A third focus is translate the computational methods and models that we have developed in this core project into clinical applications (biophysical markers) that can be used for early disease detection, noninvasive assessment of disease severity, and therapeutic decision- making.

National Institute of Health (NIH)
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Biotechnology Resource Grants (P41)
Project #
Application #
Study Section
Special Emphasis Panel (ZEB1-OSR-C)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
University of Southern California
Los Angeles
United States
Zip Code
Wu, L S; Jimmerson, L C; MacBrayne, C E et al. (2016) Modeling Ribavirin-Induced Anemia in Patients with Chronic Hepatitis C Virus. CPT Pharmacometrics Syst Pharmacol 5:65-73
Hendrickson, Phillip J; Yu, Gene J; Song, Dong et al. (2016) A Million-Plus Neuron Model of the Hippocampal Dentate Gyrus: Critical Role for Topography in Determining Spatiotemporal Network Dynamics. IEEE Trans Biomed Eng 63:199-209
Marmarelis, V Z; Mitsis, G D; Shin, D C et al. (2016) Multiple-input nonlinear modelling of cerebral haemodynamics using spontaneous arterial blood pressure, end-tidal CO2 and heart rate measurements. Philos Trans A Math Phys Eng Sci 374:
Javed, Ahsan; Kim, Yoon-Chul; Khoo, Michael C K et al. (2016) Dynamic 3-D MR Visualization and Detection of Upper Airway Obstruction During Sleep Using Region-Growing Segmentation. IEEE Trans Biomed Eng 63:431-7
Gallegos, Karen M; Drusano, George L; D Argenio, David Z et al. (2016) Chikungunya Virus: In Vitro Response to Combination Therapy With Ribavirin and Interferon Alfa 2a. J Infect Dis 214:1192-7
Weiss, Michael; Tura, Andrea; Kautzky-Willer, Alexandra et al. (2016) Human insulin dynamics in women: a physiologically based model. Am J Physiol Regul Integr Comp Physiol 310:R268-74
Sandler, Roman A; Marmarelis, Vasilis Z (2015) Understanding spike-triggered covariance using Wiener theory for receptive field identification. J Vis 15:16
Hu, Eric Y; Bouteiller, Jean-Marie C; Song, Dong et al. (2015) The volterra functional series is a viable alternative to kinetic models for synaptic modeling--calibration and benchmarking. Conf Proc IEEE Eng Med Biol Soc 2015:3291-4
Sandler, Roman A; Song, Dong; Hampson, Robert E et al. (2015) Hippocampal closed-loop modeling and implications for seizure stimulation design. J Neural Eng 12:056017
Song, Dong; Chan, Rosa H M; Robinson, Brian S et al. (2015) Identification of functional synaptic plasticity from spiking activities using nonlinear dynamical modeling. J Neurosci Methods 244:123-35

Showing the most recent 10 out of 127 publications