Thoughts After Accepting a PhD Offer and the Future of Neuro Mo

My thoughts after accepting an offer

The good news is I will be attending UCSD’s Experimental Psychology PhD program, studying with Dr. Timothy Rickard who’s work was the basis of my senior thesis. I’m thoroughly overjoyed and excited to get back to my interests in memory and learning. (Un)fortunately, this means Neuro Mo will become much less neuro. Before I make the transition, I’m going to churn out as many tutorials as possible before I start my program and lose the time I have now. There have been a couple setbacks (death of a laptop, breakup, life etc.) slowing down this progress and I am determined to get through two more tutorial series before I start producing content more related to psychology and R. I also hope to embark on a fun project or two during my down time between my job and school. Anyways, on to my thought after accepting an offer.

The time between submission and first interviews feels quite unmemorable at this moment. I remember feeling like I was in a stasis, not moving forward until someone sent me an email saying you have the chance at your future (an interview). I tried to distract myself with whatever, trying to enjoy the new found free time. I won’t go as far as saying this period was worse than the actual applications themselves but it was for sure not an enjoyable period. For me personally, I thrive off of the self perception of moving forward and the feeling like I’m building myself up for something. I don’t have much to say about what to do during this other than it just kind of sucks and you’ll come out on the other end.

In selecting, I really had to do some soul searching. I had to ask myself what was the point of building up all of these nifty (pun intended) neuroimaging and machine learning skills if I’m not going to be using them for a while. It seems like a waste right? Neuroimaging is much sexier than behavioral experiments and better funded with a greater likelihood of landing a nice job. The reason I feel comfortable switching is deeply rooted in utility and personal enjoyment. I asked myself, given my limited knowledge of the field, how much does an MRI experiment give insight into the brain and it’s relation to behavior? I would argue in many cases it’s not worth the time and money to answer deeper questions. It does a great job at saying this area of the brain is associated with this task. It doesn’t do much more than that. Yes, I’ll still do MRI studies and I think it’s important to be the most critical of the data you work on.

My view of this started to emerge the summer of my senior year in uni when reading this paper: Could a neuroscientist understand a microprocessor? The short answer is a complete no. Actually, it started incubating four months prior after reading some excerpts from the late David Marr’s Vision about levels of analysis. At the time I hadn’t fully realized my interests fall heavily on the computational and the algorithmic levels. After this, I began to realize neuroscience is not the tool I will use to gain a deep understanding of questions I’m curious about in the brain, especially in relation to higher order cognition.

I didn’t throw the baby out with the bath water and finished a degree in neuroscience. I still value and continue to value the knowledge the field produces and I also believe the conclusions about the relationship between brain and cognition can be misleading, particularly with MRI studies. Not to say psychology is without its many faults in reproducibility and conclusions. In terms of personal enjoyment, I asked myself what I can do for 60 hours a week for five years? Computation and behavioral experiments I can churn out at a rapid rate. The annoyances and slowness of MRI would be a little too much for me eventually and I think I would break after some time in grad school. This and many other reasons are why enjoy cognitive psychology more than cognitive neuroscience. I enjoy all the coding and overcoming all the technical problems in MRI analyses but for me, it takes away the creativity I find in psychology by letting layers of overly complex models I can mildly interpret that is probably giving me a false positive to answer my original hypothesis. Psychology is a lot more ambiguous, which for me, makes it more challenging and forces creative solutions to get at complex questions.

This whole process forced me to look at what I really enjoy doing in research and the questions that really tickle me. It’s been a crazy journey and I’m thankful for all of my mentors inside and outside of academia who’ve helped me get to this point. If I aim for the stars, maybe I’ll crash into the moon.

These are some of the questions I asked myself repeatedly while going through the acceptance process:

What questions are you trying to answer with your research?

Are the programs you are applying to going to give you the right tools to accomplish this?

_Why are you pursuing a PhD? Is it for discovering knowledge for the sake of knowledge? Answering questions that will help people? _

Will your research actually have an impact? If your research won’t be directly impactful, what are other ways to make an impact?

Can you imagine doing anything else besides research?

Are you trying to remain in academia or go to industry?

Mohan Gupta
Psychology PhD Student

My research interests include the what are the best ways to learn, why those are the best ways, and can I build computational models to predict what people will learn in both motor and declarative learning .