This course
- Introduces fundamentals inherent to any kind of signal and dynamical system, together with continuous- and discrete-time signal processing.
- Introduces the fundamental concepts of digital signal processing, and using these concepts for implementing and/or developing methods for processing uni- and multi-variate data.
- Gives an overview and hands-on experience with a wide variety of digital signal processing techniques used in Neuroscience research.
- In a broad manner, specifies how concepts and techniques of digital signal processing are applied to address Neuroscience questions.
- Is composed of a single theoretical module (lectures). Practicals, as done through regular assignments, will consolidate the acquired theoretical concepts in the context of neuroscience data processing problems. This part includes solving of class-exercises, analysis of simulated and experimental data, together with discussion and interpretation of results.
The tentative schedule for this course is summarized in the following key fundamentals of signals, dynamical systems, and signal processing:
1) Introduction to the course / Refresher of basic calculus concepts
2) Introduction to signals and systems
3) Dynamics of neural systems: an introduction to the brain as a dynamical system
4) Basics of digital signal processing
5) Fourier series
6) Continuous- and discrete-time Fourier transforms
7) Fourier analysis: Computational tools
8) Digital filters and filter design
9) Towards estimating the phase of oscillatory signals
10) Applications to neural data analysis
Target group: The course is for all students, who are interested in computational and systems neuroscience, and in acquiring a basis for analysing brain recordings from any existing experimental methodology
Prerequisites: Basic knowledge in mathematics; basic programming skills; basic neuroscience knowledge.
Evaluation: The participant is expected:
- to solve regular assignments (there will be a total of 6 to 7 assignments during the whole track of the course) (50%).
- to actively participate of the course discussions (lectures and, in particular, the solution to regular assignments) (50%).
Teaching format: The course is mostly theoretical (lectures). A practical part will be also included through assignments.
ECTS: 3 Year: 2022
Track segment(s):
Elective
Teacher(s):
Juan Ramirez Villegas
Teaching assistant(s):
If you want to enroll to this course, please click: REGISTER
- Teacher: Juan Felipe RAMIREZ VILLEGAS