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Aaron Gudmundson

Aaron Gudmundson, B.S.

Graduate Student, Neurobiology & Behavior 2017 – 
B.S., Psychology, 2017, University of California, Irvine







Aaron graduated with his bachelor’s degree in Psychology in 2017 from the University of California, Irvine (UCI). Immediately following, he was admitted as a PhD student through UCI’s Interdepartmental Neuroscience Program where he continued on as a member of the department of Neurobiology and Behavior (NBB). While his research interests are multifaceted, his work tends to center around a central theme of age-related brain changes. Primarily through the use of a human memory model (sequence memory), he has begun to investigate the neurobiological and cognitive declines commonly seen in the ‘normal’ aging brain. Aaron aims to shed light on the underlying mechanisms that lead to age-related declines using neuroimaging, machine learning, and mathematical modeling. In addition to his graduate research, Aaron is also the coordinator of the NBB graduate development program, NeuroBlitz, plays an active role in maintaining the Campus Center for NeuroImaging Journal Club (MRIUG), and organizes an outreach program that supports community college students entering STEM.


Research Recruitment Fellowship (2017)

Diversity Fellowship (2017)


Gudmundson, A.T., Boucquey V.B., Stark S.M., Stark C.E. (2016). Analysis of the Neurobiological Mechanisms Supporting Sequence Memory Using High Resolution fMRI within the Hippocampus. Southern California Conference for Undergraduate Research, 2016.

Gudmundson, A.T., Stark S.M., Stark C.E. (2017). Behavioral Insights for how memory can be organized with respect to time. Competitive Edge Research Symposium, 2017.

Gudmundson, A.T., Stark S.M., Stark C.E. (2017). Item-item and item-position strategy use in a cross-species sequence memory task. Society for Neuroscience, 2017.

Gudmundson, A.T. (2018) The effect of aging on fMRI activity during a sequence memory task. Neurobiology and Behavior NeuroBlitz, 2018.

Gudmundson, A.T. (2018) Denoising fMRI data with machine learning algorithms. Campus Center for Neuroimaging MRIUG, (2018)