Fundamentals of MATLAB for neuroscience research
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The document outlines the fundamentals of MATLAB for neuroscience research, emphasizing the importance of defining research goals and selecting meaningful problems to solve. It explains the Dreyfus model of skill acquisition, ranging from novice to expert, and emphasizes best practices in programming while advising against repetitive code structures. The overall focus is on efficient coding techniques and the significance of scripting in MATLAB.
Fundamentals of MATLAB for neuroscience research
- 1. FUNDAMENTALS OF MATLAB FOR NEUROSCIENCE RESEARCH Dr. Brian J. Spiering
- 3. Your Job is to define Your Job
- 4. Your job is to pick problems worth solving
- 7. Current state of conducting research:
- 8. The future of conducting research:
- 11. Dreyfus Model of Skill Acquisition 1) Novice 2) Advanced beginner 3) Competent 4) Proficient 5) Expert
- 12. NOVICE • Best served by being told what to do • Follow a manual • No possible decisions
- 13. ADVANCED BEGINNER • Best served by a bit of freedom • But unable to quickly describe a hierarchy of which parts are more important than others.
- 14. COMPETENT • Best served by the choosing among activities • Has the ability to make plans and create routines
- 15. PROFICIENT • The more freedom offered & the more expected, the more output generated
- 16. EXPERT • Writes the manual, doesn't follow it • Creates novel solutions to problems worth solving
- 17. HAVE A GOAL
- 18. HAVE A PLAN
- 19. D. R. Y. DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF DON‘T REPEAT YOURSELF
- 24. for a=1:nb for b=1:nb for c=1:nb for d=1:nb p2hf(a,b,c,d) = 2*p1hf(a,b)*p1hf(c,d) - p1hf(a,c)*p1hf(b,d); end end end end LIFE’S TOO SHORT FOR “FOR LOOPS”