I am researching histones, which are closely related to depression, from a system neuroscience perspective to find out how they control the brain. In particular, I want to use fMRI, which is capable of measuring brain activity shed light on histone brain control function from various perspectives using the analytical methods of network theory, dynamics, statistical physics and machine learning.
I chose OIST after learning that Professor Kenji Doya, who heads my unit, Neural Computation, is conducting research that combines neuroscience and machine learning and wanted to do the same. Courses are fun because of the in-depth discussions between students and professors from varying fields. My statistical physics courses were exciting whenever I got a new perspective on something from candid discussions with physics students. You'll never see that at any other graduate school.
Conversely, I had a hard time starting up a solo project all on my own with nobody else doing similar research. Not knowing what to do, I tried everything without thinking and gradually discovered what I could do through lots of failures and successes. The knowledge and techniques I gained during this period of trial and error sparked interest in other students and researchers with whom I started a joint research project. I'm glad that many of my own ideas and techniques were applied in multiple fields. And the more my research advanced to higher levels, the more people became interested in what I was doing, which made me want to devote myself to even more complex research.
I collaborated with various individuals from whom I ultimately earned trust but only after being tough with me at first. Praises pilled up and I felt like a real scientist when I realized I had built all those strong relationships.