Transcription
So scrolling is easy and doing deep research is not. And that's why on average we spend such a long time scrolling on our phone instead of working on that essay that is dusting off in the corner. Doing deep long hours of research might seem the exception and not the norm.
However, there's something really meditative about the research process. And I think if we learn a little bit more about the research process, this can actually help us in daily life to become a little bit more observant. So I've been doing research for almost six years now as both a PhD student and now as a post-doctoral researcher and I kind of want to lift the veil of how this research process goes. So how do we come up with a good research question? How do we find the right literature resources? How do we know what we can trust or shouldn't trust? And over time, I think this process will become a little bit more intuitive because I've kind of learned when I told people about the research process or how I would deep dive into specific topics that it's actually not as intuitive as I thought. So, I thought I might tell you a little bit about how I do research or how I would tackle a specific question or problem that I face both in daily life and in my work. So, let's get straight into it.
So in general, the first thing of course when you do research that you want to do is to pick a topic and here I would advise to start from general to specific. So most of us have a topic in mind that we might want to learn something about. So that can for example be neuroscience, the brain, consciousness, mental health. But this is very general and if you want to do research about a specific topic, you actually need to be a little bit more specific and it's really helpful to make a very specific question on the type of research you want to do. So for example, you first want to narrow it down to one specific angle. So if you want to learn a little bit about mental health, you might want to narrow it down to the impact of socioeconomic status on mental health such that when you do literature research, you are not just googling "mental health?" and then you can narrow it down even further. So for example, "What is the impact of low socioeconomic status during childhood on later development of psychiatric disorders?" And you already kind of get a feeling that this question will have a specific answer as opposed to mental health as a general topic or just socioeconomic status and mental health. So the more specific you make your question, the better your literature review basically will go and the better resources you will find over time. So write down a really specific research question and take time for this. And it can also even be that as you're doing your literature search, which we will talk about a little bit later, that you will refine your question over time.
So then the next step you want to do is what I call the literature hunt. And this is really a very involved process. So it will take a lot of time. So as I explain it, don't get scared and don't think like, "Oh my god, that is way too much work." But over time, you will get quite good at it. And I think even though it sounds like a lot, I think you get quite fast at finding the right resources because it does, yeah, it is a specific skill to find good resources. So in general, what I usually do when I have a specific research question in mind is I, or start with the classic papers in that research field and that depends a little bit on the research field you are in if there are classic papers, or I would start with a recent review of the last 5 to 10 years and again, that depends a little bit on the research field you're in, how fast it changes. So in general, when I find a good review, it's quite hard to decide a journal that has good reviews. So for example, I know for neuroscience that for example, Nature is quite good, or AP is quite good. And I've sometimes gotten the question as to how to decide if a journal is good in general. And I don't really think there is a way to decide this. The reason I trust specific journals is because specific authors that I trust and that have published quite good work over time publish in those journals. And it's not necessarily that those journals are better than other journals. One thing to always look out for is if a journal is peer-reviewed, but most of the reputable journals are. And then I think you want to see where are authors publishing that you like or that you think their work is good. And this really comes with experience. So it's quite hard to skip this step. But in general, you can of course rely on a bit the more, yeah, the bigger publishers such as Nature for example, or HP. But over time, you will also get a feeling which journals are trustworthy and which ones are not.
So then you have your review that you can start from. I would immediately go down to the citation section or the reference section where they basically put all the citations of the work they think is relevant for the field. And then you already have a gold mine of information. So all of these papers I would put in a common reference manager. This can be Zotero, Paperpile, or anything you want. And then I would slowly try to kind of make maps between which authors are the most important and which papers are the main nodes of your knowledge network. One way to do this as well is through Research Rabbit. So they kind of do it for you, which is really nice. And over time, then you will get this big graph-like network with all the papers.
So following this theme of trying to do research and learning something new, I've also realized that the real challenge is not just finding the information, it's also making sense of it, connecting the dots, and turning these scattered ideas into one common framework. And I realized this is really quite difficult and one thing that quite helps is where today's sponsor comes in, and that's Brilliant. So Brilliant is really designed for this kind of transformative learning, the kind that sticks and can be applied beyond the app. So their interactive courses in math, science, and logic aren't just passive. They also train you to think the way real scientists do and problem solvers do. Through hands-on exploration, visual reasoning, and through a step-by-step process, you will gain mastery over any topic. And what's new this year is that they've also personalized the experience. So Brilliant adapts to your background and pace, giving you the exact targeted practice and tailored review so that you build real understanding and not just finish a lesson. And one of the courses I really like currently is this course on scientific thinking. So it focuses down on breaking down problems, testing assumptions, and building reasoning patterns from the ground up. The same skills you need for evaluating resources, spotting patterns, and structuring your own learning goals. So if you're starting a mini research project or a mini learning project, setting new goals, or just trying to simply build new learning habits, Brilliant is an easy way to stay consistent and actually make progress every day. To start learning for free, go to brilliant.org or scan the QR code on the screen or click the link in the description. Brilliant is also offering 20% off an annual premium subscription, which gives you unlimited access to a library full of courses. So check Brilliant out and let's get back to the video.
So in general, you now have this large knowledge web, but this is just your starting point. So you have all these resources from the review, but then what you want to do is from those resources, you also want to backtrace citations. So who is citing whom, who is citing where, and all of this will then build out your knowledge network basically. You also want to forward trace. So if you have a big note or a paper that's cited by a lot of other papers in the field, you also want to see which other papers are citing this paper as well. And one way to do that in Google Scholar, you can actually see which other papers cite your paper. But you can also do that in Research Rabbit, for example, you can see which other papers are citing your paper. And the thing is with this literature review, you want to make it really wide. So you basically don't want to miss any of the main papers in the last 5 years that talk about the question that you're researching. And as you can see, this is already quite an involved process and you will already find a lot of resources. So the more specific your question is, the less resources you will find, and that's actually a good thing, cuz otherwise this knowledge network will explode. So as you're doing this and you're going over these papers, you also want to clip, save quotes, highlights, and pages to, for example, Zotero or Notion to really make this second brain idea where you note down everything that you're learning along this research process. You want to identify themes that appear across resources and you also want to keep in the back of your mind always, what is missing? Where are the gaps? Are there certain specific other papers that I should read and go over such that your knowledge network over time is very complete.
So also as you are going into or through these papers, you also want to keep a critical thinking mode on. And this is a little bit different from learning. So usually when you learn a new topic, you pick one book that is given by your professor, for example, and you just blindly trust the knowledge that is in that book. But as you're doing research or finding papers, you actually don't want to blindly trust the resources you're selecting. And the reason for that is that not all research is good, but also that a lot of research is limited. So it might be that they're quite biased or that they're promoting a specific idea that has not been fully proven yet. So you really always want to be critical when reading research papers. So something that I do for every paper that I read is I check for biases. So I check who funded it. Is it big pharma? If it's big pharma, maybe keep that in the back of your head. Does the tone sound objective? Do I think the arguments they present are valid and not from a very biased point of view? Does the data match the headline? So this is something I quite often notice is that the first, the headline, the title of the paper doesn't match the data or the introduction, the questions they ask can actually not be answered with the data. So for example, sometimes I read something like, "Depression is caused by chocolate," but then when I see the paper that they're citing, I see that paper was actually done only on mice. So the headline should have actually read, "Depression is caused by chocolate in mice." And I think quite often authors or in popular scientific journals, these headlines are tailored to, yeah, gather a little bit of clicks or to make a little bit of a controversy, but you want to be really aware like, what is the data actually telling me and not just the title.
Also, something to keep in mind is correlation versus causation. So in most neuroscientific research, we're actually talking about correlational research and not causational research. And the reason for that is that we often cannot manipulate directly human brains because that's not ethical. So most of the studies we have to do are correlational, or we're limited by the type of interventions that we can do. Also, learn some basic fallacies when you're reading papers that you should automatically flag. How do they deal with outliers? Do they use a lot of anecdotes instead of real research? And all of these kind of topics. You will over time kind of get a sense for this. But it's also good to remember that often times when you read the discussion of a paper, it's a very good sign if the research disagrees with itself to a certain degree. So most researchers know the limitations of their own studies and they will put that in the discussion for you. So if you read a discussion that's very thoughtful and points out the clear limitations of the research, that's actually a good thing because the reason that there are limitations is because research is so much at the edge of knowledge, and we cannot do all the experiments that need to be done to answer all the questions. So good research shows these limitations and guides you through the limitations of their work.
So after you have this huge knowledge plan, and then your question might be, how do I start reading from this? Or how do I start learning from this or gleaning information from this? And this is really where you want to create your own research plan or your own learning plan. And you kind of almost can treat this like a personal university course or curriculum where you basically set out daily time to go over some of the resources. And I usually start from the top nodes, and then I go to the more peripheral nodes. And again, how you can do this is through Research Rabbit, or if you link yourself all the papers together, you will see which ones are the top nodes or the top papers that get cited the most by other papers. So you want to set a daily time that you will go over these papers and will start reading that. And for me, that's quite easy cuz I do this for work. But if you don't do this for work, you can for example pick a dedicated place, time, and topic that you will go over, and that can for example be before your work or after your work, depending on how much time you have.
And then something I usually do is to build this self-study Notion template. So I do it in Notion. Again, you don't have to do it in Notion, but you have this project page, your notes database, a literature review table. This can also be in Zotero. An open questions list, daily logs of what you learned, what you've done, and some summaries of the papers that you've read. So just taking down a few snippets of what you're actually reading. And over time, this study Notion template really becomes this gold mine of information. So something that I really want to emphasize here is to try to document everything, and I really think your future self will thank you. So basically, this Notion template becomes like a mini lab book over time where you record what you read, what you've tried, what field open questions that you have as you're researching, and try to note down everything. And the reason for this is as you're doing research, your thoughts about the research will actually change over time. And I think the first questions that you have when you get into any type of topic are the most interesting because those questions really show the eyes of a novice, and it's quite hard to remember what questions you had when you research more about a topic. So really try to note down everything you're learning and all the questions you have.
And then after you have all this knowledge, something that I always say on this channel is to try to build something from it. So if you have this knowledge bank, try to create for example, an essay out of it, a chapter, a video script, a paper, or a blog post. And the reason for this is that as you work with the knowledge or you try to answer the question that you started with, I think you really start to consolidate it. And just passively learning knowledge or reading knowledge is not really a good way to truly get into a certain topic. So I would definitely encourage to write a blog post. You don't have to publish this, of course, but to try to shape the knowledge into a coherent answer on the research question that you started with. And this is really then the idea of active learning versus passive learning. So passive learning, for example, is only reading and just highlighting and just scrolling. And active is really this retrieval where you teach what you've learned. You can also try to close your eyes and try to go over the story that you've learned, or you for example, try to explain it on a whiteboard, and everything you've done. But I really think it is very important to not confuse passive learning with actual learning. And that is also when you do research, I think it's really again, like quite good to create something out of it afterwards. So to go from this research to then action.
And also something that I try to do at the end of every research session is to end with a few questions that I try to answer. So that is, "What did I learn today?" "What makes it unclear?" and "What's my next step?" And of course, I don't always exactly write it down like that, but I do try to take some quick notes of what is the next step, or what do I still want to learn, or where is the missing information. And the reason for this is over time, this really builds momentum. So if every time you sit down every day for to research this topic and you see from the previous day what is still missing, it's quite easy to follow up on that on the next day, and then you create this research or learning momentum over time. And I think this really allows for your curiosity to kind of push you forward. And especially with research, which can take one year, two years, or even 5 years for a specific topic, over time it can feel quite tedious, and there is so much to learn and so much we do not know, and you also really start doubting yourself. But I think if you note down all these thoughts and all of the questions you have over time, I think almost the questions become more interesting than the answers that you find.
So, I really hope that this research process, or as I lifted the veil a little bit, that you've learned something from this and that you might use this process to guide your research as well. And I'm just really curious, what are you researching currently? What topics are you interested in? Is there anything you would like me to make a video on? I would also love to tell a little bit about my research one time here on YouTube, but I always find it really complicated because I feel that the research I'm doing is so new. So I don't really want to talk about it online because I feel then people think that this is already the truth. Whereas something with research that I always have in the back of my mind is that it's still so malleable. So maybe what I'm actually showing today will be disproven in 10 years. Whereas I think online or also on YouTube, it's very much a platform to show what's truth and what is already out there. But I would love to know what your thoughts are about this. Do you think there's a good way to show research that we as scientists are still really unsure about? And how do we show this scientific process in a way that doesn't claim any type of truth or, um, validity? I would be really curious. So, let me know down in the comments below. And otherwise, I see you next week. Bye.