I want to be a neuroscientist. In September, I'll be attending university for BScH in Neuroscience. Should I double major in Neuroscience and Computer Science? This will take 5 years instead of the usual four.
I am going to Canada (from India) to study neuroscience. I'm just wondering if computer would be helpful in neuroscience. Remember that I really love Computer, know C and Java, but I would have so many things going on provided research, extracurricular activities, volunteering, and so on.
Computer Science is a degree that is very flexible, and can be utilised in almost any industry. If you're doing any kind of science in a professional capacity, particularly in research, you may find the skills you learn to be useful. If you take the extra year to study Computer Science, you will find that the quality of the code you are able to write is significantly higher and you will understand it at a much deeper level.
It will also give you the ability to pivot in your career if you later decide that Neuroscience isn't for you, and on it's own it's usually a 3-4 year degree depending on the university.
That you can spend only an extra year at uni to gain a whole other skillset that you already have an interest in I would say is definitely worth it. Remember also that you can always drop the Computer Science if you decide it's too much or you don't want to do it anymore for whatever reason. When I studied I started off doing Computer Engineering / Physics but I later decided that Physics wasn't for me so I dropped it; however if you go in just doing the Neuroscience you won't give yourself the opportunity to make that decision.
All the best!
One area that is incredibly popular right now (likely to continue into the next decade at least) is AI/machine learning as a method of understanding just about anything that is data-rich and complex enough that simple human intuition struggles to describe. One way to think of it is, people can typically only keep a handful of variables/trends in mind/graphed at any given time, but a computational model is only limited by the accuracy of the data fed into it and our understanding of how different variables may interact. Simply put, the analytical power of AI/ML is only beginning to be applied across just about every industry you can imagine. Because of the computational complexity and high dimensionality (meaning many variables at play) of neural circuits/function, neuroscience/neurotech is one of the best fields/industries for applying such tools.
Even if you end up changing your mind about neuroscience or CS, a minor in CS with applied AI/ML experience will make your resume vastly more attractive to potential employers in just about any industry.
Another thing to consider, as you mentioned, there are many aspects pulling at your limited time in university. It is important to balance both hard work and studies with extracurriculars to ensure you finish out with the same kind of passion and enthusiasm that you're going in with. Science is amazing, but also a lot of hard work. Failures are inevitable and exhausting, but if your scientific curiosity is insatiable, there's no stopping you. It's important to make sure you have good social support and some balance in your life. When those inevitable struggles occur, it's those friends and family and creative/athletic/etc. outlets that will allow you to recharge and bounce back. With this in mind, a double major is typically a much more significant workload than a minor, but if the program is already laid out for an extra year to compensate, that may not be too difficult.
However, if you are interested in industry or graduate studies, I highly recommend both interships and hands-on lab work. Don't be afraid to email research professors asking what opportunities they may have for a motivated student. Sometimes if you are excelling in a course you can speak with that professor and they are usually thrilled to refer motivated and excellent students to their colleagues. Most are happy to at least sit down and chat to either see if you might fit in their lab, or just because they enjoy providing mentorship/guidance. One compromise might be doing a minor in CS and getting started early on volunteering in a lab that does AI/ML neuroscience work. Even without a minor, 2-3 years of part-time work in such a lab is arguably more valuable than any minor both in reality and on paper. Also, I would recommend at least 2 years of research experience if you are looking at graduate studies. Most students cannot really learn/accomplish enough to write a meaningful publication in only one year, but with two years, you can gain the experience and execute the work to put together a meaningful publication that can be the factor that sets you apart from other graduate school applicants. If you're set on industry, an internship is likely the most valuable experience you can have on your resume. DO NOT slack in your 1st/2nd year studies. Most valuable internships require 3.0 GPA for participation, so your 1st/2nd year grades are essential for such opportunities.
One last thing to focus on is deliverables. Regardless of what path you choose, wherever you are putting in time and effort, you need to keep in mind concrete goals and accomplishments that serve to illustrate your skills, abilities, and drive. For example, 'I spent the summer working as an Undergraduate Research Fellow in Dr. So&So's lab. The modelling work I executed refined our understanding of mechanisms of memory formation in the hippocampus and provided seminal data for the lab's successful application to Such&Such research grant. The manuscript is currently under review for publication in BigNameSciencePub'
Best of luck! Stay curious!