2020-01-04May 20192019-05May 2019https://hdl.handle.net/10657/5739Reinforcement-learning brain machine interfaces could reduce the number of times a neural prosthesis has to be updated daily for individual use. This can be achieved by using reward signals that are present in cortical neural activity but firing rates have been shown to be varied across trials, even if the same stimulus is being presented. This trial-to-trial variability, also known as noise correlation, is shared across a neuronal population and has been shown to be modulated by attention, learning, and behavior. To investigate this the current study performs a noise correlation analysis using data recorded from the primary motor cortex (M1) of two rhesus monkeys performing a grip force task (GFT). It is seen that the noise correlation generally increases with the presentation of a rewarding cue. The results also suggest a stimulus dependence as well as independence to changes in firing rates.application/pdfengThe author of this work is the copyright owner. UH Libraries and the Texas Digital Library have their permission to store and provide access to this work. Further transmission, reproduction, or presentation of this work is prohibited except with permission of the author(s).Noise correlationReward modulation2020-01-04Thesisborn digital