Ryan Senne

Ryan Senne’s research lies at the intersection of machine learning, statistical modeling, and the neuroscience of decision-making. Over the past several decades, neuroscientists have developed novel tools to record from hundreds, if not thousands, of neurons simultaneously. However, analysis methods have generally lagged behind this technological progress. Senne aims to develop machine learning and statistical tools to analyze large, multivariate time-series data. Specifically, he is focused on understanding how neuromodulatory systems, particularly norepinephrine (NE), alter local neuronal network dynamics in awake, behaving animals during decision-making tasks. Senne hypothesizes that non-neuronal cell types, such as astrocytes, work in tandem with noradrenergic neurons to change neural dynamics in response to new evidence, ultimately influencing an agent’s behavior.