Prof. Emery N Brown

Dr. Brown’s research focuses on mathematical modeling of physiologic systems in three areas: (1) signal processing algorithms to study how individual and ensembles of neurons encode information about relevant biological stimuli; (2) statistical methods for analysis of functional neural imaging data; 3) statistical models to accurately characterize the physiologic properties of human circadian and neuroendocrine rhythms. He is investigating how computing accurate estimates of the period, phase and amplitude of the human circadian pacemaker from different marker rhythms; quantifying the effects of light on the circadian pacemaker; and characterizing differences between normal and abnormal physiology in terms of the components of circadian and neuroendocrine rhythms. Dr. Brown has also developed a new class of statistical methods -- point process adaptive filters -- for tracking the dynamics of neural receptive fields directly from experimental data. This work has important implications for accurately representing hippocampal plasticity as well as that in other neural systems.