Dr. Katie Bottenhorn is a neuroscientist and postdoctoral researcher at the University of Southern California. In this episode we talk about Katie's background in neuropsychology, the methodological aspect of neuroinformatics, and Katie's dissertation research focusing on how hormonal fluctuations during the menstrual cycle impact women's brains. Additionally, we discuss gender imbalances in STEM fields such as neuroscience, and compare large sample neuroimaging studies to deep phenotyping approaches featuring a large number of scans within a small sample.
Timestamps:
0:00 - Introduction
0:46 - Pursuing psychology and chemistry as an undergrad
3:33 - Neuroimaging vs wet lab neuroscience research
5:47 - Plans for neuroscience grad school
9:13 - STEM gender imbalance and the "leaky pipeline"
11:11 - Katie's transition into methodological research
15:52 - Pursuing data science without a math or computer science background
18:33 - Applying deep phenotyping methodology to studying women's health
20:55 - Dense sampling methods in neuroimaging: more scans, not more participants
24:14 - The replication crisis in neuroimaging
26:11 - Big data neuroscience via large samples vs. deep phenotyping
28:25 - Katie's dissertation work looking at how hormonal fluctuations change women's brains
32:00 - Determining causality in brain and behavior
34:59 - How hormones change brains during puberty
36:46 - Katie's plans for postdoctoral research