All posts from Feature

Feedback Control Indirect Response Models

A recent publication in the Journal of PK/PD presents a general framework for modeling pharmacodynamic processes that are subject to autoregulation. Yaping Zhang and David Z. D’Argenio. Feedback control indirect response models. Journal of Pharmacokinetics and Pharmacodynamics.43(4) :343-358, 2016. DOI: 10.1007/s10928-016-9479-8 A general framework is introduced for modeling pharmacodynamic processes that are subject to autoregulation, which combines the indirect response (IDR) model approach with methods from classical feedback control of engineered systems. The canonical IDR models are modified to incorporate linear combinations of feedback control terms related to the time course of the difference (the error signal) between the pharmacodynamic response and its basal value. Following the well-established approach of traditional engineering control theory, the proposed feedback control indirect response models incorporate terms proportional to the error signal itself, the integral of the error signal, the derivative of the error signal or combinations thereof. Simulations are presented to illustrate the… Read more

Model-based Biomarkers for Alzheimer’s Disease

Recent results of model-based “functional biomarkers” were presented in the IEEE Conference on Engineering in Medicine & Biology (San Diego, August 2012) that demonstrate the potential for improved diagnosis of early-stage Alzheimer’s Disease (AD) using dynamic nonlinear models of cerebral hemodynamics obtained from clinical time-series data via our novel modeling methods employing Principal Dynamic Modes. The key finding is that AD patients exhibit impaired vasomotor reactivity as quantified by our model-based biomarkers. Model-based Quantification of Cerebral Vasomotor Reactivity and its Use for Improved Diagnosis of Alzheimer’s Disease and MCI V. Z. Marmarelis, Fellow IEEE, D. C. Shin, Member IEEE, M. E. Orme, R. Diaz-Arrastia & R. Zhang This presentation addresses the issue of clinical diagnosis of Alzheimer’s disease (AD) which represents a major threat to public health since it affects more than 5 million people and absorbs about $150 billion annually in the US alone. Currently, clinical diagnosis of AD… Read more

Modeling the Metabolic Syndrome

An extensive overview of the efforts that have been made to better understand the pathophysiology of metabolic syndrome using computational modeling was published in the 2013 volume of IEEE Reviews in Biomedical Engineering. The review also introduces the notion that sleep-disordered breathing may play an important role in promoting the development of metabolic syndrome in obese individuals. Understanding the Metabolic Syndrome: A Modeling Perspective Khoo, M.C.K., Oliveira, F.M.G.S. & L. Cheng. IEEE Reviews in Biomedical Engineering 6, 2013. The prevalence of obesity is growing at an alarming rate, placing many at risk for developing diabetes, hypertension, sleep apnea, or a combination of disorders known as “metabolic syndrome”. The evidence to date suggests that metabolic syndrome results from an imbalance in the mechanisms that link diet, physical activity, glucose-insulin control, and autonomic cardiovascular control. There is also growing recognition that sleep-disordered breathing and other forms of sleep disruption can contribute significantly… Read more

MIMO Nonlinear Dynamical Modeling for a Hippocampal

A recent publication in the IEEE Transactions on Neural Systems and Rehabilitation Engineering presents the application and hardware fabrication of the multi-input, multi-output (MIMO) nonlinear model for a hippocampal cognitive prosthesis. The modeling results show that the MIMO model can accurate predict the hippocampal CA1 (output) spiking activity based on the ongoing hippocampal CA3 (input) spiking activity and thus restore the lost memory function in rodents. A Hippocampal Cognitive Prosthesis: Multi-Input, Multi-Output Nonlinear Modeling and VLSI Implementation. Berger, T.W., Song, D., Chan, R.H.M., Marmarelis, V.Z., LaCoss, J., Wills, J., Hampson, R.E., Deadwyler, S.A. & Granacki, J.J. A Hippocampal Cognitive Prosthesis: Multi-Input, Multi-Output Nonlinear Modeling and VLSI Implementation. IEEE Transactions on Neural Systems and Rehabilitation Engineering. 20(2): 198-211, 2012. This paper describes the development of a cognitive prosthesis designed to restore the ability to form new long-term memories typically lost after damage to the hippocampus. The animal model used is delayed… Read more