Dana H. Brooks
Gilead Tadmor, Solomon G. Diamond, Deniz Erdogmus, Maria Angela Franceschini
Date of Award
Doctor of Philosophy
Department or Academic Unit
College of Engineering. Department of Electrical and Computer Engineering.
habituation, low dimensional modeling, model order reduction
Multimodality functional brain imaging has been gaining importance due to the complementary nature of many of the modalities. Dynamical systems based models of neural activity and local hemodynamics can offer enhanced spatiotemporal resolution and insight into physiological signals and mechanisms. One major tool for studying brain function is to provoke local ”evoked responses” by repeated application of a stimulus.
Evoked responses to stimuli show complex habituation behavior as the stimulus repetition frequency increases. To gain insight into the relation between local neural activity and hemodynamics we propose a control structure that enables neural mass models to predict habituation as revealed in rat EEG under medial nerve stimulus. We report on the accuracy with which these models recreate the data waveform under stimuli at varying frequencies (from 1-8 Hz), as well as the accuracy with which they mimic complete inhibition of firing at higher stimulus rates. We also compare the predictive power of the models, demonstrating the capability of simplified representations to capture key features of the mass evoked neuronal response.
Equipped with such a predictive neuronal model we explore the relationship between the neural response and the local hemodynamics by reconstructing the inputs of a Windkessel-based hemodynamic model and relating the basis functions of the neural signal to those of the inputs to the hemodynamic model. The model that relates the neuronal responses to the hemodynamic inputs is termed as the Neurovascular
Laxminarayan, Srinivas, "Low dimensional modeling of localized neural and hemodynamic response with habituation from multimodal brain measurements" (2011). Electrical Engineering Dissertations. Paper 33. http://hdl.handle.net/2047/d20000954
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