I'm applying for PhD programs in CompNeuro/ML and starting to develop my research interests.
My previous work has been in NeuroAI and Reinforcement Learning. I've developed niche interests in representational geometry because of my experiences, but what I would really like to work on is the most high-impact ambitious problems in the field. If you were beginning a PhD given what you now know, what would you attack?

TIA

I'm contemplating a master's in applied math from John Hopkin's Engineering online to gain the necessary math and stats background. I have a background in psych and will be working as an EEG or a sleep tech as I'm currently pursuing schooling related to that. I'm pretty much an older non-traditional student in all respects. In order to do something like computational neuroscience for a Phd if I go that route, would I need to become proficient in R and python as well as algorithms and machine learning?

I am curious to know how potential future fields could greatly benefit from a computational neuroscience specialty or just a computational approach in general. I recently took an interest in this field due its potential to impact many distinct areas of study and bring about new approaches to understanding them. I also have a question about computational neuroscience as it's so niche and interdisciplinary with multiple Ph.Ds from mathematics, neuroscience, and computer science all being a part of the field. My question in this regard is would it be possible for someone who specializes in neural networks and machine learning for a masters program in data science or statistics to later use their knowledge and experience to contribute to a field like clinical psychology as a later Ph.D? I have had some discussions with many people about it and they say that brain computer interfaces and computational data science have a large potential to reshape psychology towards a more scientific and empirically verifiable discipline. In the past it was assumed that emotions were subjective while still true to a degree we can now at least assign and align more rigorous data to them. I was very passionate about psychology but was disheartened to hear how unscientific and ideological psychology has grown to be, with psychologists in the past formulating ideas coming from medical related or other backgrounds to contribute to the field. My main question is that with the relevant research experience in a masters program, would it be possible to use knowledge from computational models and brain computer interfaces not only limited to computational psychiatry of simply diagnosing and understanding patterns in the brain for individuals with mental or cognitive conditions. But to use this data and integrate it with computational neuroscience to see and decipher how those connections are linked to behavior and utilizing computational neuroscience to map and chart them. If you had a passion to merge and go about pursuing the fields of clinical psychology and computational neuroscience what would a good plan be to combine or use both to further understandings within each field?

Lately, I’ve been considering specializing in combining neuroscience, particularly neurolinguistics, to improve neural networks and, in general, the language capabilities of AI systems. But I have several doubts about this.

First of all, I don’t come from a computer science or neuroscience background—I have an undergraduate degree in languages and linguistics, and now I’m pursuing a master’s in NLP and neuroscience.

I wanted to ask:

1.	Given the current development of LLMs, transformers, etc., is this type of research between neuroscience and NLP still useful?

2.	Could this kind of research be relevant in the tech industry as well as academia? Some people say that neuroscience has nothing more to offer to AI/NLP, while others believe it’s the future of AI.

3.	What types of research do you know about that combine neurolinguistics with NLP to improve the language of these models? Perhaps you could suggest some papers. So far, I’ve seen some very recent research using neurolinguistic data, like fMRI data, to analyze how language models like BERT represent language compared to the human brain.

4.	I’m not sure what kind of background is necessary for this field. I notice that people working in this area usually have a STEM background in engineering, CS, or neuroscience, and I wonder if my background would be suitable. 

The point is that I don’t want to do pure research in neurolinguistica or neuroscience so that the results can guide AI/ NLP researches. I would like to use neurolinguistics to improve AI and NLP, so it’s kinda different.

So i have neuroscience degree . I want to upskill my self and learn comp neuro . What is the best way to find and contribute to some comp neuro project .

Hello everyone, I know this question has probably been asked a million times and I apologize for that.

I am a computer science student and lately I have discovered a real passion for biology, more specifically neuroscience. My question is: knowing that my computer science background provides me with solid skills in linear algebra/probability & statistics, basically a foundation in mathematics in addition to computer science, can I pursue a PhD in computational neuroscience? And if it's possible, I would like to know if anyone has a similar background to mine and has succeeded in completing a PhD in neuroscience.

Sorry again if this question has been asked several times.

Hi all!

Will the combination of Mathematics and Comp. Sci for undergrad adequately prepare me for the world of Comp. Neuro? My goal is to go directly from undergrad into a PhD program, but if this does not seem applicable, would this combination atleast adequately prepare me for a Masters program?

Hi All,

I’m looking for some advice if anyone is kind enough to have a spare minute.

I’m finishing an Honours degree in physics (quantum computational focus). I am very interested in pursuing a PhD in neuroscience (on the computer science and highly mathematical side of it). I have been looking for research groups focused on comp neuro, especially with aspects of ML overlap.

I only truly realised that this is what I wanted to do this year, and I do not have neuroscience related research experience. It’s very possible that my research this year will lead to a publication, but not before any PhD applications are due. I have just submitted this thesis and I’m graduating this year. I was thinking of 2 possible pathways - either applying to related Master’s programs or waiting a year - gaining research experience as a volunteer at my uni - then applying again. For context, I am at an Australian uni.

Does anyone have similar experience to share? Especially to do with transitioning into comp neuro from alternative backgrounds. It feels a bit like imposter syndrome even looking to apply to programs, despite that the skill set overlap seems fairly large

Thanks in advance.

Hi Folks!

I was under the impression that due to recent shifts in the systems neuroscience community, the computational abilities of an ensemble of neurons are attributed to behavior instead of individual neurons. Meanwhile, in Drosophila (100k neurons), neuroscience is still about individual neurons. Is it because of technological bottlenecks or are computations actually restricted to individual neurons in the flies? Or is there a problem in my knowledge and/or understanding of basics?

Thanks :)

I'm very far away from doing anything computational neuroscience-related but I am nonetheless very intrigued by the ideas and research being done.

I've read up a fair bit about the paths that lead into it, and, as you might know, the consensus is that it is very diverse--physics, applied math, electrical engineering, neurobiology, computer science are all disciplines that have commonly been said to contribute.

But what exactly do each of these careers do for CNeuro research projects? Is it as simple as "applied math makes the math, EE makes the hardware, computer science makes the simulation programs, etc"? I suspect not. What common trends (that might be more detailed than the ones I've just listed) do you guys see for different careers/roles in cneuro?

Hey everyone! I’m in the final stages of my PhD in engineering, focusing on neuroimaging—specifically diffusion MRI modeling and biomarker development. While my work has been quite technical, my real passion lies in neuroscience, and I’m planning to transition into a postdoc in Computational Neuroscience.

Although I’m familiar with many concepts in the field, there are still a lot of gaps in my knowledge. I’d love to hear your recommendations for books, papers (reviews, key studies, or even PhD theses), that could give me a solid introduction to the current landscape of computational neuroscience.

I’ll be meeting with a professor in a few months and would like to present myself well-prepared, with a comprehensive understanding of the key ideas and recent developments. I’ve come across some older resources (from around 2005-2014, including a book from the professor I plan to meet), but I imagine the field has evolved significantly since then. Any guidance on where to start or the latest must-reads?

Also, any tip regarding the "transition" into this field would be greatly appreciated.

Also (x2), I get that reading the contributions of the professor you're interested might be useful. But this professor in particular has hundreds of papers. Would you prioritize those with more citations even though they were published 15 years ago? How should I decide what papers are the most important?

So I've decided on a behavioral model for my experimental (behavioral) data on a variant of a deviant detection task, I don't think it will be too difficult to develop a corollary model for various cortical networks, or at least incorporate some learning rule and test it against available data in similar studies using neuroimaging modalities.

I have limited programming and developer experience (python,and anaconda , Jupyter lab/notebook, psychopy, and qiskit).

However, the tools gifted to me by the world wide web can help, so not too worried about that.

Mounting evidence for LC modulation of the cortical hierarchy has built up over the last few years, with a recent paper showing tonic and phasic patterns of activation induce network biases and behavioral biases in rodents.

Thankfully, I've managed to locate a repository on github of task driven and biophysically plausible models of various cortical networks.

Assuming that the locus coeruleus is involved in some universal optimization algorithm, I plan to look at my study of reward contingency to develop some learning rule for rule violation when reward inferences are induced in deviant detection tasks. Since I am bad at math and bayesian statistics wasn't as hard as I thought, I plan to incorporate some rule based on my bayesian behavioral model and incorporate it into these networks, many of which are variants of error driven RNN's with specific parameters to account for biophysical/ functional properties of specific cortical networks.

I promised my supervisor I wouldn't get ahead of myself and focus on my original goals, but this could be next semesters project for our undergrad research program. I'll make sure I complete this before I start another.

In any case, the only obstacles to making some feasible learning rule incorporated into some larger algorithm between different networks seems to be learning a bit of pytorch, PyNN, tensor flow, and maybe arbor. Plus finding some algorithm that fits to the behavioral data well.

The available code is set up for task implementation and development. So defining a similar task for my use shouldn't be difficult. I'm excited, resources at my institution are scarce and it's taken me months of sifting through publications to find the resources I need.

I just need to know if I'm in over my head.

Lastly, I know how annoying it is for some of you to be constantly pestered by me over the last 2 or so years, but I don't have much help outside of the internet and forums like these.

Edit, for clarification: The learning rule will serve as some proxy for LC input into these networks.

Hi! I heard a lot of comp neuro majors in college do a master's or phD, but I was wondering which one is more common? I just want to be able to get a decent-paying job in the field that I enjoy, so I'd prefer to just do a master's since it gets me there quicker but I'm not sure if that's feasible. Also, what should one do their master's or phD in if they want to work in the comp neuro field? Appreciate any help!

I'm a 4th year IT undergrad and I have been looking into pursuing my masters in comp neuro but I can't seem to find any such courses in US except for one Neural engineering and computation course in Columbia. UCSD had a link for ms in comp neuro I think but now that link is not working. I looked into John Hopkins too but it seems like they are offering a Ph.D and not masters. Can someone help me find one? (and please do leave a link to the program if you can cause anytime I search them up Idk why I can't find the right webpage.)

Thanks for reading!

I was an int’l student in the U.S., but due to mental issues transferred back to my home country to keep on doing my bachelor degree.

The decision of studying aboard initially was unforgivably hasty, but it’s the only choice I know with the knowledge/resources I had at that time. I did not enjoy the city and environment, which got me depressed. It became worse, I realized I have to stop, so I transferred back to my home country.

After transferring back, I discovered my fiercely-burning interest in comp neuro. Also my vision got wide enough to found that it was the location, school, and the first time being in a foreign country that got me depressed and frustrated. Plus I developed serious elite school complex, so now the school in Taiwan couldn’t satisfy me (I have a feeling that no matter how good the grad school I end up being, this bachelor will follow me forever), also on the reality perspective, it indeed would have me seem one point worse than other applicants in future grad school applications. So I’m considering transferring back to the U.S., to a school with wisely picked location and at least decent reputation in neuro. However I am also worried that the two times transfer will just be my criminal record, which might also affects grad school application.

I’m in a position where I cannot move forward nor backward, I understand the above description might make me seemed immature, clueless and irritating. But I do seriously need help, psychological support and academic pathway counseling at the same time. To my knowledge there isn’t a therapist that could do both, so if you are/you know someone that happens to be familiar with undergrad system in the U.S., do neuro research, and knows how to settle one’s mind, I would be greatly, greatly appreciated your help, please pm or comment or pm for my Gmail.

I understand my description might seem messy and too straightforward, if you need any clarification, I’m happy to answer! Thanks again!!🫡

This is maybe a weird question, but I don't know how else to word it.

I'm a mature student in Australia studying a double bachelor degree (Computer Engineering + Computer Science). About 5 quarters of a year ago I quit my job working in a warehouse to find something to do with my life that was more interesting. After getting into uni my mind has opened to so many avenues, and after discovering Comp Neuro I felt like "this is it, this is what I want to do".

But is it really something I can do? Im hard-working, getting excellent grades, but from my perspective it just doesn't seem real. I don't come from an educated family, I don't come from a place where these sorts of things are possible. I want to be on the cutting edge of research, contributing to the scientific world, but all I think is "that's not a real job, that's not going to get me a house and support a family". Or I think "that's not a real thing that normal people do, that's for people who have excelled their whole lives, I should aim lower".

Is Comp Neuro even real? How do I get started with it? I don't even know if my current degree will give me the right knowledge to excel in comp neuro, but I'm too scared to take a course that more aligns with it (say CompEng + Data Science) since it could reduce employability compared to CompEng+CompSci.

Thanks for being my void to shout into. If anyone has any thoughts I'd be grateful.

Same as question

Hello everyone I'm feeling so excited right now! My lab finally gave me a High performance PC(16 X 9i cores) I can use for simulations!

I'm new to all this, so would you guys give some insight of how to use it compared to a normal pc(7i core)?

How can I use it for its worth?

Thank you in advance

Hi all. I'm a second year at UCSD majoring in cognitive science (spec. ML/neural computation) and math-computer science. I kind of dismissed the neuroscience aspect of cogsci when I was going in, but I took a neuroanatomy class last quarter and found out I was actually really interested in this stuff. I've read a few papers about various comp/math neuro topics since then but don't really have anything particular in mind yet.

In general, I feel like these two majors intersect pretty well and obviously lend themselves pretty well to a field such as this one. As far as coursework goes, what should I focus on taking? I still have some requirements, like a neuroscience sequence, a data science class, DSA and probability, all of which I imagine would be pretty useful across the board. But I'm also wondering what electives would be helpful - there are a lot of data science-y/research-y Python programming classes under the cognitive science department, but I can't imagine those would be too useful if I'll already have strong programming fundamentals from CS classes and I could probably pick up whatever I need for a lab or for grad school. Should I just take more neuroscience classes instead?

As for the math side, I'm planning on taking probability and statistics courses this year; I've heard diffeq can be useful for things like dynamical systems so I'm wondering if I should push that up? I'm also interested in taking harder more pure math-y sequences like real analysis and algebra at some point, but I imagine neither of those are particularly useful and I'm wondering if I should focus more on applied stuff instead.

Also, coursework is obviously only one part of college, so what should I be focusing on outside of classes? Should I keep trying to read more papers/books to educate myself first or should I just be trying to get a lab position somewhere? I'm also coming at this from the perspective of someone who's coming from the CS/SWE grind - are there projects or other extracurricular things I should be doing (I guess this is more of a question for grad school in general)?

Kind of a longer post than I intended it to be, so TL;DR: what coursework should I be taking if I'm interested in comp/math neuro grad? (both on the cognitive science and the math side of things) What other actions outside of coursework (i.e. seeking for lab positions) should I be doing?

My current work aims to characterize novelty based on its relation to reward inferences or contingencies

I plan on doing this separately, but if the data is solid, I plan on trying to develop a learning rule that I can test in a model assigned different tasks.

I’m a bit frustrated, as it seems work has been done that has coupled reward and novelty in a reinforcement learning paradigm a few months ago. So that’s about 7 to 9 months down the drain. I aim to do so in a predictive coding lense, though.

Need something that’s easy to use and something with nice visualization.

Thanks in advance.

Hi everyone,

I'm considering pursuing a master's degree in Computational Neuroscience, and the field really interests me. However, my bachelor's degree is in Software Engineering, and I'm wondering if that would be a good enough foundation for this transition.

I have a strong background in programming, algorithms, and data structures, and I’ve worked with large datasets and simulations before. That said, I don't have much formal education in biology or neuroscience, and my math knowledge mainly covers what’s typical in a software engineering program (discrete math, linear algebra, some calculus).

Would my software engineering skills be useful in this field? And what kind of additional knowledge or coursework should I prepare for if I want to pursue this?

Any advice from people who have made similar transitions or who are familiar with the field would be much appreciated!

Thanks in advance!

Hi, I’m a bachelor student in Artificial Intelligence in Brazil, and I was wondering how difficult it would be to continue my studies abroad. I’m very interested in Neuroscience and would like to know how qualified I would need to be to join a master's program in this field.

Hey! I’m a psych undergrad (Licentiate degree) and I’m planning to apply to BCCN or TU Berlin next year. For those who self-learned math and are now studying or graduated with a comp neuro degree, how did you prove you actually had the knowledge? Did you take the GRE or did you report online courses you took?

Hi everyone,

I'm based in Canada, and am looking to do a master's in mathematics or comp sci. My undergrad was neuroscience and computational cognitive sciences, so I do have some programming and machine learning experience. I also have wet lab experience, if that helps.

Other than taking introductory physics and 2nd-year mathematics, both of which I don't have great grades in due to the pandemic and favouring neuroscience courses at the time, I'm at a loss as to my next steps. I entered a master's that is running out of funding, and my department is now looking for some PhD students to fund their own degrees (crazy, I know).

I'm wondering if it's better to aim for CS, which I have more practical experience in? Otherwise, I would love to aim for a mathematics degree, but am unsure if that would be closing the CS door if I did something like topology. On top of that, is the math GRE enough to cover bad mathematics grades?

If tools from classical dynamics are successful in computational neuroscience, could quantum dynamics tools be useful too? I'm not suggesting the brain uses quantum computation, but techniques from quantum many-body dynamics, like phase transitions/criticality, thermalization, and renormalization theory, might have applications in other fields of complexity science. I know that stat physics, which is related, has been applied to comp neuro as well. As an aside, not sure if this is far fetched, but we could for example try to describe emotional states by phase transitions. Maybe we could even characterise dynamics for many-body neuronal systems (like neuronal wetware).

Are there researchers applying these techniques to computational neuroscience, or is it not feasible? Gabriel Silva mentions this (https://arxiv.org/abs/2403.18963), though they are talking more about utilising quantum computation, which I'm not too keen on.

Edit: I just saw the previous quantum info post lol 😅

Hi All,

I figured this would be a good subreddit to send this question. I am currently transitioning from a psychology and neuroscience bachelor's to a master's in computer science, with the aim of moving into the private sector. While my focus is on tech, my passion for neuroscience and cognitive psychology remains, and I plan to integrate areas like BCI and neural networks into my coursework. As I prepare for roles in the tech industry, I’m interested in understanding what positions outside of academia would allow me to apply my (hopefully upcoming) computer science expertise while incorporating my background in neuroscience. Thank you!