Computational neurosciences: what to expect contentwise?

In summary, the speaker is considering a new program in computational neurosciences instead of their original plan to pursue a Master's degree in Electrical Engineering. They are unfamiliar with the field but have read the syllabus and are excited about the course descriptions. The program covers a range of topics including signal processing, circuit modeling, machine learning, stochastics, and biology. The speaker asks for others' experiences and opinions on the program. The program is a new one and aims to merge courses from different fields such as neuroprosthetics, computational neuroscience, and imaging. The program also includes a course where students can discuss and analyze current research papers and potentially publish their own work. The speaker asks for feedback on the syllabus and how it compares
  • #1
fatpotato
Hello,

I was going back to university for Grad school (Master's degree) this fall in Electrical Engineering, but since my application and admission, the uni created a brand new program in computational neurosciences, and I am heavily considering to follow this path instead. Thrilling!

However, I am not really familiar with the field. I have read the syllabus and have been memserized by course descriptions. From what I read, I imagine this field as the perfect mix of signal processing, circuit modelling and analysis, machine learning, stochastics and of course, biology.

Is this correct? Am I idealizing? I fear being too optimistic, and would love to hear about your experience if you have an academic background in comp. neuro. Please share!

Thank you
 
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  • #3
Hello,

I can post the list of courses and program structure, which should be found in attachment. Otherwise, follow this link: Neuro-X Master at EPFL

This is a new program which aims to merge a lot of courses previously proposed as electives or as a minor. I suppose that there is a need for this type of engineers, for I have seen a few other universities offering this kind of studies these last few years.

Courses are distributed among three categories :
  1. Technology: most of the content here was included in the former "neuroprosthetics" minor. This category focuses on designing interfaces for the body and analysing motor functions of the nervous system.
  2. Data science and ML: most the content here was included in the former "computational neuroscience" minor, with a focus on machine learning, signal processing and statistics.
  3. Imaging: covering all subfields: from tomography and optics to image processing and computer vision.
Courses in the last category is organised a bit like a medical symposium, where "hot" topics and papers are discussed and analysed, and can lead to a publication from the students.

For people who studied computational neurosciences: how does this differ from the syllabus you followed? Does this syllabus look good to you?
 

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Related to Computational neurosciences: what to expect contentwise?

1. What is computational neuroscience?

Computational neuroscience is a field of study that combines principles and methods from neuroscience, computer science, mathematics, and physics to understand how the brain processes information and generates behavior.

2. What are the main topics covered in computational neuroscience?

The main topics covered in computational neuroscience include neural coding, neural networks, learning and memory, sensory and motor systems, and brain-computer interfaces.

3. How is computational neuroscience different from traditional neuroscience?

Traditional neuroscience focuses on studying the brain at the cellular and molecular level, while computational neuroscience uses mathematical and computational models to understand brain function and behavior.

4. What skills are necessary to study computational neuroscience?

To study computational neuroscience, one should have a strong background in mathematics, computer science, and neuroscience. Knowledge of programming languages such as Python and Matlab is also important.

5. What are the applications of computational neuroscience?

Computational neuroscience has a wide range of applications, including understanding brain disorders and developing treatments, creating artificial intelligence and robotics, and improving brain-computer interfaces for medical and technological purposes.

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