Neuroscience & Math: Advice for Beginners

In summary, if you are interested in Neuroscience and have little computer experience, it is recommended to focus on learning graph theory, statistics, probability, and linear algebra. These areas of mathematics are important for a strong foundation in computational neuroscience. Additionally, it is useful to learn programming languages such as R, Matlab, and Python for implementations. A strong background in calculus, linear algebra, statistics, and differential equations is necessary, as well as familiarity with dynamical systems for biologically realistic modelling. Other areas of mathematics such as stochastic processes, topology, and analysis can also be beneficial.
  • #1
andryd9
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2
I am interested in Neuroscience, but have little computer experience- can anyone advise me on a good place to start? Also, I would like to know which areas of Mathematics could most benefit me to look at. I worry that I am weak in Math, and would like to bolster relevant applications. TIA!
 
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  • #2


Learn your graph theory, statistics, probability, and linear algebra very well. I don't know too much about general computational neuroscience, but I do know some related fields and subdisciplines like machine learning. Control theory has differential equations that you need to know as well. So those four topics should be good for you to know in regards to mathematics.

For implementations, I can't be sure, but for statistics people like to use R and Matlab, and Python has some really awesome libraries for all kinds math including linear algebra and statistics. I would say Python is also the most accessible to you.
 
  • #3


Matlab is standard in computational neuroscience (and most disciplines) for drafting programs and for less computationally intensive analysis and modelling. Compiled languages are usually a better choice if you need to do something extremely intensive. R is, of course, standard for statistics, but I honestly do most of my analysis in Matlab.

As far as mathematics: A strong background in calculus, linear algebra, statistics, and differential equations is non-negotiable. If you're interested in the biologically realistic modelling of neurons and neural networks, than you really can't get your foot in the door without some familiarity with dynamical systems (I've been working with a fairly abstract model of pre-frontal neural clusters over the last few months, and 90% of what I'm doing involves non-linear dynamics). Beyond that, you can find a use for almost anything; knowledge of stochastic processes is extremely useful, and I've even managed to make use of some topology and analysis.
 

1. What is the relationship between neuroscience and math?

Neuroscience and math have a strong and intertwined relationship, as understanding the brain and its functions heavily relies on mathematical principles and analysis. Math is used in areas such as data analysis, modeling brain activity, and creating computational models of neural networks.

2. How can math be used in neuroscience research?

Math is used in neuroscience research to analyze and interpret data, create models of brain function, and understand complex neural networks. It is also used in fields such as neuroimaging, where mathematical algorithms are used to analyze brain images and map brain activity.

3. Do I need a strong background in math to study neuroscience?

While a strong background in math can be helpful in studying neuroscience, it is not a requirement. Many neuroscience programs offer courses specifically designed for students who may not have a strong math background, and there are also resources available to help students improve their math skills for neuroscience research.

4. How can neuroscience benefit from advances in mathematics?

Advances in mathematics, such as machine learning and artificial intelligence, have greatly benefited neuroscience research. These mathematical techniques allow for the analysis and interpretation of large amounts of complex data, providing insights into brain function and disorders.

5. Are there any specific areas of math that are particularly important in neuroscience?

There are several areas of math that are particularly important in neuroscience, including statistics, calculus, linear algebra, and differential equations. These branches of math are used to analyze and interpret data, create models of brain function, and understand the complex neural networks in the brain.

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