Computational Neuroscience/BCI Research Career (Advice Needed :S )

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SUMMARY

Nate is pursuing a Master of Biomedical Science with a focus on Neuroscience but is concerned about the lack of computational neuroscience content in the curriculum. He aims to transition into a PhD in Computational/Brain-Computer Interface (BCI) research and seeks advice on self-learning computational skills. Nate plans to learn Python through Codecademy and is inquiring about necessary mathematical knowledge and engineering principles relevant to BCI research. He expresses urgency for guidance on how to prepare for his Master's dissertation and future academic endeavors.

PREREQUISITES
  • Basic knowledge of Python programming
  • Introductory calculus, including functions, differentiation, and integration
  • Understanding of neuroscience concepts and terminology
  • Familiarity with Brain-Computer Interface (BCI) fundamentals
NEXT STEPS
  • Learn advanced Python programming and libraries such as NumPy and SciPy for scientific computing
  • Study machine learning concepts, focusing on neural networks and their applications in neuroscience
  • Explore engineering principles relevant to BCI, such as signal processing and control systems
  • Research mathematical topics like linear algebra and statistics, which are essential for data analysis in computational neuroscience
USEFUL FOR

Students and professionals in neuroscience, aspiring computational neuroscientists, and individuals interested in Brain-Computer Interface research seeking guidance on self-directed learning and preparation for advanced studies.

ndy890
Hi everyone :) I am looking for some career/academic advice and didn't know where else to ask!

I'm going to be doing a Master of Biomedical Science (Neuroscience) next year, here is the course outline:

Yr1:
- Biomedical Science Research in Context—Literature Review
- Global Challenges in Biomedical Science
- Human Neurobiology
- Comparative Neurobiology
- Advanced Neuroscience 1
- Advanced Neuroscience 2
- Physiology of Cells
- Neuroendocrinology

Yr2:
- Marine Neuroecology and Behaviour
- Modern Research Tools in Neuroscience
- Advanced Research Techniques
- Neurodevelopment and its Disorders
- Literature Review and Research Proposal (Dissertation)
- Science Research Project Part 1 (Dissertation)
- Science Research Project Part 2 (Dissertation)
- Science Research Project Part 3 (Dissertation)

The problem I feel that I have here, is that none of these units deal much with computational neuro. I would very much like to go on to do a PhD in Computational/Brain-Computer Interface research and so would love to something related to that in this Masters Dissertation. But I think the first year of this course would leave me at a disadvantage. So does anyone have any advice how I could go about learning the computational side of things on my own? Is it a steep learning curve? Do you think its possible to prepare myself for a Masters Diss./PhD in this area without formal academic education?

- So far, I'm planning to soon start learning Python through codeacademy, but of course that is very superficial. Where should I go after that to learn more/get applied programming practice?

- I also have introductory calculus level knowledge of math, including functions, differentiation, integration, inequalities, optimisation. What areas of math should I know before I start my masters dissertation?

- I also have no engineering knowledge, and I am thinking that this might be necessary if researching in the Brain-Computer Interface area. How would I also go about getting this knowledge without formal education?

As you can probably tell, I'm desperate for guidance.Thank you in advance for anyone willing to help! :)

Nate
 
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Are you talking about something like neural networks and artificial intelligence or about communication between the brain and devices (mind control of artificial limbs, cochlear implants, etc.) or about man-machine interfaces like pilot-vehicle interface (display / controls design)?

Or not sure yet?
 
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