Date of Graduation

5-2019

Document Type

Dissertation

Degree Name

Doctor of Philosophy in Physics (PhD)

Degree Level

Graduate

Department

Physics

Advisor/Mentor

Woodrow Shew

Committee Member

Wayne J. Kuenzel

Second Committee Member

Jiali Li

Third Committee Member

Pradeep Kumar

Keywords

Granger Causality, olfactory bulb, predictive coding theory, sensory input processing, sensory systems

Abstract

The conglomeration of myriad activities in neural systems often results in prominent oscillations. The primary goal of the research presented in this thesis was to study effects of sensory stimulus on the olfactory system of rats, focusing on the olfactory bulb (OB) and the anterior piriform cortex (aPC). Extracellular electrophysiological measurements revealed distinct frequency bands of oscillations in OB and aPC. However, how these oscillatory fluctuations help the animal to process sensory input is not clearly understood. Here we show high frequency oscillations in olfactory bulb carry feedforward signals to anterior piriform cortex whereas feedback from the aPC is predominantly carried by lower frequency oscillations. Similar frequency multiplexing of feedforward and feedback signals has been observed in other sensory systems, but our work is the first to show this in the olfactory system. We also pharmacologically manipulated inhibition in the OB. We found that weaker OB inhibition made the feedforward and feedback signal stronger whereas stronger inhibition resulted in a weaker feedforward and feedback signals. Our observations support hypotheses derived from predictive coding theory which suggests that low frequency inhibitory feedback may make coding more efficient by suppressing response to predictable sensory input. Our work, together with similar observations in other sensory brain regions, suggests that frequency-specific flow of information is a general principle of the sensory systems in the mammalian brain.

In a second project with entirely different goals, we developed a new experimental system for doing closed-loop control of neural activity in motor cortex of mice. We present preliminary results and discuss future directions for this second project.

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