Knowing more about the discipline of mathematical neuroscience

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SUMMARY

The discussion centers on the pursuit of mathematical neuroscience, highlighting the lack of structured curricula and resources for those interested in this emerging field. Participants emphasize the importance of mathematical modeling skills and suggest that a background in biology or medicine is more beneficial than physics for entering neuroscience. They recommend exploring computer science, neural networks, and artificial intelligence as viable paths for those inclined towards theoretical neuroscience. Additionally, the conversation touches on the demanding work hours typical in neuroscience and the necessity of lab work for practical experience.

PREREQUISITES
  • Mathematical modeling techniques relevant to neuroscience
  • Basic understanding of biology and neuroscience principles
  • Familiarity with computer science concepts, particularly neural networks
  • Knowledge of research methodologies in theoretical neuroscience
NEXT STEPS
  • Research mathematical modeling approaches in neuroscience
  • Explore neural networks and artificial intelligence applications in neuroscience
  • Investigate academic programs related to mathematical neuroscience at institutions like MIT
  • Study the works of prominent mathematical neuroscientists, such as Stephen Grossberg
USEFUL FOR

Students and professionals interested in the intersection of mathematics, neuroscience, and computer science, particularly those exploring theoretical neuroscience and its applications in artificial intelligence.

  • #31
Pythagorean said:
The computer's just a tool like a calculator. You should write the models on paper, derive them mathematically, then (naturally) you're not going to want to solve the mathematics for 10000 neurons by hand so you use a numerical ODE solver or you write a snippet to compute the probabilities. Then you have to represent the data somehow (you don't just publish a bunch of numbers in a paper, you publish graphical representation) so you might as well have your code do that for you too (you're more then welcome to open up excel and do it all manuallly with your data, but it's the long route).

So while computer science is not at all the emphasis, any modern scientists (whether data mining, classifying behavior, integrating statistics, or simulating time-evolved equations) has everything to gain from knowing how to do some basic programming.

There's possibly more general, theoretical mathematics you can do, but I'd think most of them still rely on mining numerical data sets in the end... you're pretty much always going to be slower than the guy who has the same scientific knoweldge as you, but more programming skills.
ribozyme :)

That makes computational neuroscience more interesting to me. So what percentage of a computational neuroscientist's time would be used in writing down a program? If the time is little relative to other work they do then it would likely suit me.

I searched up on ribozyme real quick and that was very interesting actually, thank you.
 
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  • #32
Hey dude, this is for you: http://biomath.rutgers.edu/

Check it out. If you are interested in biology related areas and physics double major. That is what I intend on doing most likely. Doing a Physics and Biomathematics double major at Rutgers. As far as your interests go, check out the curriculum for Biomaths. There are some Neuro classes in the electives, there is also a class offered by the Biomedical Engineering Dept on sensory processes focusing on the analyzation of the auditory and visual modalities. There are courses on the use of computers in biology etc etc. As far as an undergrad preperation for some type of Mathematics/Biology overlap goes I would think that the Biomaths/Physics combo would be quite good.
 
  • #33
Also if you're interested go to the Aresty Research center website and check out all of the REU's they have listed and you can further see the type of stuff that you can work on.
 

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