I’m a researcher and data scientist with a background in neuroscience and psychology, with expertise in statistical data analysis and modeling, machine learning, and experimental design.
I earned my BS in Psychology from the University of Arizona, where I worked on neuroimaging research in the lab of Dr. Alan Sanfey, probing how people make decisions in competitive economic games that balance their own monetary gain with prosocial attitudes about fairness and cooperation.
I then completed my PhD in Neurobiology at Yale University in the lab of Dr. Daeyeol Lee, where I studied the capacity of non-human primates to attend to multiple temporal intervals and experimental variables simultaneously, and recorded and modeled the neural activity of prefrontal cortex neurons responsible for this complex multitasking behavior.
For my postdoctoral work, I joined the lab of Dr. David Foster, first at Johns Hopkins University and then the University of California, Berkeley, where I worked on the functions and mechanisms of generation of memory replay sequences, precisely timed and ordered population reactivations of neurons in a brain region called the hippocampus. These replay sequences recapitulate activity patterns that would be observed during active experience in an environment, but occur during rest and sleep periods when sensory cues are absent, coordinate the activity of many different brain regions, and begin to appear after a single brief experience in a novel environment. Replay sequences are therefore thought to be critical for offline training of brain wide networks, using internally-generated simulated experiences in order to optimize learning and memory from sparsely sampled and noisy real experiences.
Matt Kleinman, PhD 