Discovery and Validation of Biomarkers Based on Computational Models of Normal and Pathological Hippocampal Rhythms

Abstract

Quantitative systems pharmacology is an emerging field with the goal of offering new methodologies for drug discovery based on concepts that grew out of systems theory. Oscillation is a central topic of dynamical systems theory, and neural oscillations are related to both normal and pathological behavior. The role of abnormal neural oscillation in several dynamical diseases is briefly reviewed. Two special cases were investigated. The possible mechanisms of anxiolytic drugs on hippocampal electric patterns were analyzed by combined physiological and computational methods. A network of neuron populations that generates septo-hippocampal theta rhythm was modeled using a compartmental modeling technique. The effects of cellular and synaptic parameters were studied. Pyramidal hyperpolarization-activated (I-h) conductance and decay time constant of inhibitory post-synaptic current have significant effects on frequency. A biophysically realistic model of the electrical activity of the hippocampus, an early target of Alzheimer's disease is also manipulated on a synaptic and cellular level to simulate biochemical effects of amyloid-beta accumulation. This can help elucidate a mechanism of age-dependent theta oscillation changes in AD mouse models, reflecting changes in synchronous synaptic activity that could mediate oscillation-dependent memory deficiencies and serve as a biomarker for amyloid-beta accumulation.