I’m American and I must say, nothings more encouraging to my self esteem than to see someone with English as a second language speak, present, and explain information 12X better than me….
Hi Artem! I'm currently doing my own bachelor's in neuro, and I've struggled a ton over the last years - mental health, identity, life circumstances, all came together and had me leave schooling and research part-way through my degree. I'm only just coming back to it now. Your videos are doing two things: reminding me why I love computational neuroscience, and giving me the tools and understanding to push through this time. Thanks a ton, and keep at it.
Hey! Thanks a lot for your comment. Might sound weird coming from a stranger, but I've just been through a similar process. Restarting my studies nearly from zero after three years of bachelor's. I hope all goes well for you!
This is such an inspirational share. Thanks, I can relate to this. Life struggles, mental health, circumstances, etc; but a deep love for neuroscience and then strong desire to learn computational neuroscience after.
I'm doing a bachelor's in Neuroscience with a minor in Math and I have a background with CS. Most of the stuff covered in my program is focused on the biological and physical aspect of neurons. The computational side of neuroscience was always daunting to me but this encouraged to try it out. Thanks
Hello Artem, I have to say that your content is so incredibly underrated! After several years of leaving school, your channel has reminded me how much I enjoy learning neuroscience and mathematics. I will be returning to school to finish my bahelors in biomedical science with minors in neuroscience and applied maths and could not be more excited to continue the journey. Thank you for your content
Thank you! I had also falled in the pit of studying all of the math to get myself "ready" for all of the machine learning and deep learning algorithms. Which now I see was pointles, because as soon as I start learning some new pure math concept, I forget the ones I had learned prior, so I get frustrated and tired, and never get to do the coding. I was in the pit for a full year. I re-read Howard Antons Elementary Linear Algebra textbook 3 times. Now I will just get on with the coding and learn Math on the go.
Man! If I follow you , definitely I can grow in coding and computational neuroscience. You are so clear and convincing . You have a great future !! I by the way hold PhD in Structural Biology, Biophysics and Biochemistry in Alzheimer’s and Multi-molecular Complexes !! I am now into quest of Consciousness, Psychology and Neuroscience!!
Recently gained a little bit of interest in this subject, and this is the only video I have seen so far that has been able to give me a better understanding of what the field is all about. Thank you very much Artem!
Alot of very good advice! I'm interested in comp. neuro. and cog. sci., coming from a mathematical background, but only as an anscilliary to inform what I hope to do: which is essentially elucidating _epistemic facts,_ focusing on the "general solution" to intelligence from the top-down and stuff like that - yeah, I'm trying to be even _more_ interdisciplinary, and make even less money (I like the sort of stuff published in IEEE, and sometimes Synthese depending.) I was pretty much like you learning math as well, but I was less anticipatory, and would try and find proofs as they came. I thought that your idea would be essentially the best way to teach math to students: if you designed your major assignment such that it hit on a great swathe of the sort of problems you might see in as many industries/research as you can (the interdisciplinarity will be useful down the line) and then motivate the whole course by sticking the assignment questions right at the start of the first lecture, so students are contextualising everything they learn wrt the assignment.
I’ve been trying to tackle the problem similarly to you. I think epistemology is the most important, and least understood portion of the interdisciplinary approach. I’d love to chat about what you think about induction, concept-formation, and generalization, in the context of plausible cognitive science frameworks.
@@khalilhughes1481 Ah, well I am very influenced by Quine and Putnam on the one hand, and by Friston and Bach on the other. I would look to our best sciences of induction for clues concerning it's nature: statistics and ML are good case studies. From this approach, we can't be a nominalist - statistics really should be synonymous with dimensional reduction: that is, the central deep motivating dogma of statistics is the removal of information from the data makes it _more_ predictable. This becomes most pronounced with non-parametric methods, where excising a notion of magnitude between the data allows us to fit it better to a normal curve, because we know the distribution of ranks/signs/etc. It sounds obvious enough that the brain does this sort of thing - we have known as much since at least Kant - but that it is a feature of general learning systems is my motivation. A system seems to require, for it to learn, must find computational reducibility i.e. redundancy in it's environment to build it's models. It has to do this; it has a perfectly good computationally irreducible model of it's environment already at it's disposal: it's environment (this is Wolfram's idea). If it can't do this, it has to force it with some lossy method. Couple that with the insight that every organism is a model of it's environment necessarily. Information necessarily has to affect the internal states of an organism such that there is a motor response such that it minimises the free energy of the system. Induction in this sense is a very low order process. At the level of concept-formation, I suspect that's where identity comes in to play. I think Heidegger and Carnap asked the right questions: A concept only needs a name and a sense for it's being true. To get at this, we need to know what the necessary conditions for some concept to "refer" are. Heidegger's corpus ends there, but it's the big question afaic. Bach talks about consciousness as a system modelling itself - or self-evidencing (circularity's fine if it's big enough) - almost as though it's treating itself as a part of it's own environment, and attempts to compress itself into something it can predict and model itself across time. We may treat objects/concepts alike, to be modelled across time - likely accounting for the second horn in Carnap's definition, but I don't know if that's absolutely necessary for generalised learning systems. Something Friston has called for are MLAs that have exploratory/novelty-seeking behaviour. There's much talk of new language models "being conscious", but I have never seen an LM ask a question of it's environment, in an attempt to model it, let alone ask a question of _itself_ in an attempt to model itself. I hope you found that interesting!
This is a fantastic video. I'm about to take a 12 month sabbatical to study computational neuroscience and deep neural networks (two very different fields obviously). I love that your channel exists, and will keep a close eye on recommendations like this. I've already reached out to a computational neuroscience lab at one of the best universities near me and they're supportive to mentor me into a masters program or PhD program. This would be a pretty big career pivot for me and I'm excited about the possibilities.
i wouldn’t say they’re very different, either. DNNs are based of the brain and while you wouldn’t be monitoring calcium ions levels for example, there is a lot of overlap. good luck with everything!!!
Studying Bio and Psych in undergrad rn looking to move into neuro this stuff is really helpful, not a lot of practical info about the field out there. Cheers man
Going to start my graduate program in computational neuroscience next year. I come from a mechanical engineering background, and this video provided a good library of resources to get started.
Literally thank you for this. First steps into neuroscience on my own. Will try and keep u updated with my exciting journey. Hope I don’t give up and find what I am looking for 🙌
I’m studying biomedical engineering with a focus on medical imaging to get a larger perspective on healthcare and its engineering aspects, but computational neuroscience is 100% what I want to do in the long run. Thanks for this rough outline so I can improve the computational neuroscience side hustle of my degree, lots of value I can add to my professors’ labs and connections I can make w/ these skills
Thanks again! I'm so so glad I stumbled across your channel! you've really given me a LOT to think about as I'm just starting down the path of data science. there haven't been too many channels I've come across on how to really pursue my goals in this sort of fluid, structured, unstructured way of being self-taught! also thank you for making me aware of these open data resources! Next challenge is to find a project that I get to play around with! thanks again!
Your channel revealed that the field id always wanted to go into was real and has a name . :) going to be finishing my biochemistry BS this year with three years of biophysics experience and I’m super excited to see what lays ahead!
Had the same problem with "trying to learn all the math first" with trying to get into AI. But that's just way to abstract, you have no results, learning curve and motivation starts fading. The best thing is just to code code code and build stuff yourself. Replicate the top research papers etc. You'll learn the necessary math on the way.
Glad I searched and clicked on this video. Thank you for your help and I hope I have the earned privilege to give my contributions to this field in the future.
Thank you very much for your video. I was not from a technical background, so it took me very long time to adapt, but now I want to learn more about CS applications in other Sciences. Your video gives me basic ideas of how to study by myself. If only your existed earlier 🥺
I want to commend you on the exceptional quality of your content. I have a background in programming with Matlab and R, and for the past few years, I have primarily relied on Python. However, I still have a deep appreciation for R. I would greatly value your opinion on whether it is worthwhile to continue using and studying R, considering its ecosystem, libraries, and other relevant factors. Any insights you could share would be immensely appreciated. Thank you very much.
Very helpful video. All necessary information of how to start learn neuroscience by yourself. Especial thanks for a bunch of resources of the computational neuroscience. Спасибо большое:)
Step 1.python Step 2.codeforces smth Step 3.books :- # general neuroscience 1.N exploring the brain- barry connors 2.principles of N- eric kandel 3.the brain from inside out- yuri And research papers # comp N 1.Theorotical N comp and mathematical modelling of neural systems - peter dayan &larry abbott 2. Dynamical systems in N - eugene Step 4.math stuff # mit yt lectures on linear algebra Step5. Projects// join a research lab
I love your videos! I'm studying a bachelor's in computer science centering around networking, algorithms and ai and systems penetration. I also love medicine and physics. What I am really interested in though is the brain, I'm autistic and it makes me think differently to most people. I want to understand those differences, neurologically. I want to incorporate computational neuroscience into artificial intelligence, approaching the subject through quantum computing. As part of an MSc I plan to study a bachelors neuroscience and signal theory module. Would have had a long way to go before I could start down that route, but mainly because I didn't know how to access it. But I think I should get some of those books you suggest and start!
Nice video, Artem :) I think theoretical/mathematical neuroscientists are bit less rare than you might think. However, their identity also tends to morph into others like mathematicians, physicists, or machine learning researchers, so I can understand why you might prefer not to identify them as 'neuroscientists' if that's your view.
Thanks! Well, I just meant that as our technologies advance, there is an emerging subdivision between "computational" and "theoretical" neuroscientists. I feel like the former inherently operate with large amounts of information (either experimental or simulated data), while the latter deal with former mathematical descriptions (think computer vs blackboard & chalk) Anyway, this is just my impression, so take it with a grain of salt. I am by no means in position to say who qualifies as "true neuroscientist" and who doesn't. Especially considering that all the boundaries between fields are really blurred ;)
Amazing video 👏🏼👏🏼 I'm BSc in neuroscience, and learned to love computing through cmput electives. But I didn't touch computational neuro since I thought I'd have to know all the math and be a genius coder or a graduate comp sci student first. It was really helpful to see that debunked! Especially that you mentioned python was popularly used, the only programming language I know. I'm soon getting into research, and stumbling into your channel has encouraged me to pursue it with this angle :)
I've got ADHD which can sometimes help, but when it comes to my long term goal concerning sentient AI it makes me kind of scatterbrained. I'm already 2 chapters into the neuroscience book. I'm interested in the path to sentient (conscious is the next step) artificial intelligence. The idea is that text based AIs such as the one the google researcher claims is sentient, cannot be since they are only taking an input and spitting out an output. A sentient AI must be able to take inputs, store them for later use (memory), and remember past events, experiences, etc. Preferably there is some sort of "neurogenesis", adaptation, etc. I'm currently taking a course in AI at my university for a broad survey of the field, and I'm trying to find the most promising, practical path towards sentient AI. I think bio-inspired design will play a huge role in developing a sentient AI and computation neuroscience is a similar field. I have no illusions that I'm going to create something intelligent or even something that is sentient, but with a solid base in relevant areas I hope to be able to eke out some form of progress in this pursuit and have something to show for it
Hey I know a year is passed but you should check out the book being you by Anil Seth. It’s a really good up to date introduction to consciousness neuroscience. He actually addresses whether or not a conscious ai is possible (he’s a bit agnostic towards).
My attempt to summarize the video 1. Write on an index card the key information of the section you’re studying or the questions that may be asked 2. trial your memory at increasingly spaced repetitions 3. Make sure that when you’re studying and when you’re rewriting you’ve given an excited answer to the question: why do I want to learn this?
I think the reason people get so hung up on deciding which programming language they want to go with is because deciding to learn a human language is a big deal. You need time and patience to learn human languages as an adult which is no small task. Of course, some of the differences between programming languages can also be very difficult that require time and patience of their own; but for sure the differences and time needed to learn human languages are of a much higher magnitude than programming languages; each programming language essentially just needs to describe the basic architecture which at its most basic level is the same everywhere.
🎯 Key Takeaways for quick navigation: 00:46 🧠 *Computational neuroscience involves using computers for data analysis and simulations, addressing the overwhelming amount of data collected through experimental techniques in neuroscience.* 04:25 🛠️ *Necessary skills for computational neuroscience include coding (Python or MATLAB), knowledge of neuroscience concepts, and a mathematical toolbox relevant to the chosen project.* 05:33 📚 *Recommended textbooks for getting started in computational neuroscience include "Neuroscience: Exploring the Brain" and "Principles of Neural Science." Reading research papers is also emphasized.* 09:44 💻 *Algorithmic thinking is crucial for effective coding in computational neuroscience. Practice solving non-straightforward problems to develop problem-solving skills.* 15:50 🔄 *Projects are essential for learning computational neuroscience. Joining a research lab is beneficial, but self-started projects, inspired by research papers, can also be valuable for hands-on learning.* Made with HARPA AI
This was very useful, Artem. To paraphrase you, from the bottom of my heart: thank you. 😊 Two questions, please: 1. have you ever created visuals like the ones at 2:50 or like an interactive brain connectome? Do you know if those visuals are usually made using a certain programming language or using specialized software? 2. what are your thoughts on the book on your desk? I didn't see it mentioned in the video. 😊 Thank you again for the video. I've just starting self-studying neuroscience and the video made me more confident in my approach.
Thanks! 1) The animation at 2:50 was taken from a RU-vid video ru-vid.com/video/%D0%B2%D0%B8%D0%B4%D0%B5%D0%BE-3JQ3hYko51Y.html I would really love to know what software the author has used, but unfortunately, I couldn't find any information. 2) This book is called "The Computational Brain" by Terrence Sejnowski and Patricia Churchland ( www.amazon.com/Computational-Brain-Neuroscience/dp/0262533391 ). I've got to confess, I haven't yet read this book fully, it's still on my reading list. I didn't want to explicitly recommend something I don't have a lot of personal experience with. But judging by a couple of chapters I did manage to read, it's a pretty good book ;)
@@ArtemKirsanov Thank you, Artem. I looked through the comments for Denis Dmitriev's video, and found that he used Autodesk 3ds Max. Apparently, the video took 30 hours to render. That makes me wonder: how much time and effort did Denis spend on creating it?🙂 Thank you also for the book info. I'll take a look at it.
Did my AI MSc 20-odd years ago -- very pleased to hear Matlab is dying if not actually dead. Get Python and you can graduate with a usable skill that can earn you money even outside academia.
Hello my friend, I am a young man living in Syria. I am 21 years old and studying computer engineering. I am still a university student and need three years to graduate. I want to study computational neuroscience because it interests me, especially the topic of brain control of limbs and muscles. I want to migrate to one of the advanced countries like Russia or Germany to complete my studies. Currently, I do not work and my parents support me and give me money to complete my studies. I want to ask you what should I do in the next three years? Should I study a field of work and master it so that I can support myself and after graduation head towards studying a master’s degree in computational neuroscience or should I start studying computational neuroscience now? I really want advice and I have no one to guide me or direct me.
Dear Artem! According to Your expirience, is it enough to have only a bachelor degree (in electrical engineering) to join a reseach project? Or it would be nice to have at least a master degree? I am interested in how to heal spinal cord injuries, but do not really know where to start. Also, I like to work with hardware as well, I do not know is it possible in this field. Thanks for Your answer.
Hi, I wondered if a lot of people go into computational neuroscience research (e.g. BCIs) from doing a CS or AI background, and if it's better to have done something with more maths? I am choosing between CS and Maths, and CS and AI undergraduate degree, but I don't know if the latter usually contains enough of the math needed, and if it's harder to teach yourself on the side. I don't know if good computational neuroscience postgraduate programs prefer you to have done the math in the degree itself?
Can you share any resources regarding your dissertation work on modeling calcium with diff equations? It sounds very interesting and something I've never heard of. Would love to read a draft of your work or point us in the right direction! Thanks!
Sure! Here's the central paper written by my scientific supervisors (it was published before I joined the team), which we are currently expanding to include astrocyte-neuron communication. www.frontiersin.org/articles/10.3389/fncel.2021.645068/full It proves a nice introduction to the topic (at least in my opinion) and you can find lots of relevant sources in the references and along reading the text
Thank you very much for this video. I am a practicing critical care physician and I have been interested in learning computational method to use it in critical care, neurocritical in particular. I can code with python and I have good grasp of algorithmic thinking and programming in general. My math, I am learning calculus nowadays and willing to follow your advice in linear algebra and differential equations. later im intending to take the course in ML by Andrew Ng but I am not quiet sure of my approach and roadmap, it would be of great help to give me some insights. Thank you :)
Hey, Great video, I wanted to know about any topics or suggestions on neuroscience projects for beginners. Projects which could be completed within 6 months or less. Would be thankful for any sort of help. Thanks
I did materials science and engineering, have little coding experience, but am dying to get involved with brain computer interfaces (black mirror kindof inspiration). I have no idea what kind of projects to look for, or what fields would bridge my knowledge to this field, but I’m very overwhelmed at the idea of learning to code just from home. Pls help
Thank you so much for this amazing video I have a degree in psychology and I want apply a master degree in computational neuroscience but i am a little bit scared because they usually looking for bac degree in math or physic I want to learn math and coding maybe I get a change to apply master in this field and I am open for advices. Thank you.
bro do you know how many research papers get released on ai? those chineese professors releasing papers every day. its like: you think your are state of the art but suddenly another paper pops out that does it better
Hey, thanks a lot for the video! It sums up pretty well stuff I already knew and adds just everything else I needed. Especially the math pitfall was like reading my mind. Quick question: do you think there's any merit in learning C? Moreover, say one is a total novice, would your advise them(aka me) to start learning python and C at the same time or is it better to do it sequentially? 😊
Thanks! Well, I'd say if you're starting from scratch, definitely go with Python. It is much easier to use and understand then C/C++, which can seem intimidating and discouraging. I wouldn't say that C experience is a must, though. Sure, it is used to create some sophisticated packages, which require doing lots of computations blazingly fast. For example, packages like Brian2 and Ripser use C++ under the hood. If you would like to go into the realm of developing software for neuroscience, C++ would be very useful. But for most people out there, solid knowledge of Python / MATLAB / Julia would be enough
