Computational/Mathematical Neuroscience

In summary, the individual is seeking advice on whether to pursue a graduate program in applied math or neuroscience with a focus on computational/mathematical neuroscience. They ask specific questions about the difficulty of getting accepted into top programs and the funding opportunities in each field. The expert suggests highlighting a strong background in both math and neuroscience and choosing a program with a strong focus on computational neuroscience.
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Is anybody here familiar with computational/mathematical neuroscience? I graduated with a B.S. in physics and math two years ago and have decided to apply to grad school for 2011. I need some help though on deciding what path to take. I don't know if I should go the applied math route or a standard neuroscience route (with emphasis on the mathematical side).

Here are some of my specific questions:

1) How hard is it to get accepted to an good applied math program doing research in the field of mathematical neuroscience ( e.g. NYU, Brown, Princeton, Duke, Washington etc...)?

2) How hard is it to get into the top neuroscience schools doing research in computational neuroscience (Yale, Princeton, MIT, UCSD, NYU, Columbia etc...)?

3) Is funding better in the neuroscience or applied math departments?

4) Which path would you advise for someone interested in computational/mathematical neuroscience?

Thanks!
 
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  • #2


As a computational/mathematical neuroscientist, I can offer some advice on your questions:

1) It can be competitive to get accepted into top applied math programs with a focus on mathematical neuroscience, but it ultimately depends on your qualifications and the specific program you are applying to. Make sure to have a strong background in both math and neuroscience and highlight your research experience in these fields in your application.

2) Similarly, getting into top neuroscience schools with a focus on computational neuroscience can also be competitive. However, having a strong background in both math and neuroscience can give you an advantage in this field. Again, highlight your research experience and make sure to have strong letters of recommendation.

3) Funding can vary between departments and programs, so it's important to do your research and compare the funding opportunities available. In general, both neuroscience and applied math departments may have funding available for research in computational neuroscience, so it's important to look into specific opportunities at each institution.

4) If you are interested in computational/mathematical neuroscience, I would advise looking into programs that have a strong focus on this field and offer opportunities for interdisciplinary research. This could be through a traditional neuroscience program with a focus on computational neuroscience, or through an applied math program with a focus on mathematical neuroscience. Ultimately, it's important to choose a program that aligns with your research interests and goals.

I hope this helps in your decision-making process and wish you the best of luck in your grad school applications!
 

What is Computational/Mathematical Neuroscience?

Computational/Mathematical Neuroscience is a multidisciplinary field that aims to use mathematical models and computational methods to study the brain and its functions. It combines principles from mathematics, physics, computer science, and neuroscience to understand how the brain processes information and generates behavior.

What are the main goals of Computational/Mathematical Neuroscience?

The main goals of Computational/Mathematical Neuroscience are to develop models that can accurately describe the behavior of neurons and neural networks, to understand how neural networks process information, and to use these models to make predictions and test hypotheses about brain function and dysfunction.

What are the different types of models used in Computational/Mathematical Neuroscience?

There are several types of models used in Computational/Mathematical Neuroscience, including biophysical models, which describe the electrical and chemical processes of individual neurons; network models, which describe the interactions between groups of neurons; and cognitive models, which aim to understand how the brain performs higher-level functions such as decision making and memory.

How is Computational/Mathematical Neuroscience used in research?

Computational/Mathematical Neuroscience is used in research to gain a deeper understanding of how the brain functions, to develop new treatments for neurological disorders, and to design and improve artificial intelligence and machine learning algorithms. It can also be used to analyze and interpret data from brain imaging techniques such as fMRI and EEG.

What are some current challenges in Computational/Mathematical Neuroscience?

Some current challenges in Computational/Mathematical Neuroscience include developing more accurate and realistic models of the brain, integrating different levels of analysis (from single neurons to large-scale networks), and improving our understanding of how different brain regions and networks work together to produce behavior. Additionally, there is a need for more collaborative efforts between mathematicians, computer scientists, and neuroscientists to advance the field and address complex research questions.

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