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