Credits: 5
Schedule: 09.01.2019 - 28.05.2019
Teaching Period (valid 01.08.2018-31.07.2020):
III-V (spring), odd years
Learning Outcomes (valid 01.08.2018-31.07.2020):
After completing the course, the student should be able to:
- Explain the basic principles of information processing in neural circuits
- Define coding information and reconstruction of stimuli based on neural information
- Quantify the information content of a spike train
- Analyze the fundamental constraints arising from noise on neural circuit function
- Perform basic mathematical analysis to characterize neural signals and noise
- Explain the basic requirements for fidelity and specificity of neural circuit function
- Give examples of neural circuit computations and neural codes in well-defined neural circuits.
Content (valid 01.08.2018-31.07.2020):
- Basic building blocks of the neural circuits
- Neural wiring vs. neural circuit function
- Basic principles of neural information transfer
- Signal and noise in neural circuits
- Quantifying information in neural circuits
- Fidelity and specificity of neural circuit function
- Examples of neural circuit computations.
Assessment Methods and Criteria (valid 01.08.2018-31.07.2020):
Teaching Methods: Lectures, exercises and exam.
Requirements, Assessment Methods and Criteria:
- Active participation in teaching and exercises
- Exam
Workload (valid 01.08.2018-31.07.2020):
- Lectures: 20–24 hours
- Exercises: 20–24 hours
- Preparations for exercises: 30 hours
- Independent (self) study and preparation for lectures: 43 hours
- Preparing for the exam: 10 hours
Exam: 3 hours.
Study Material (valid 01.08.2018-31.07.2020):
TBA
Course Homepage (valid 01.08.2018-31.07.2020):
https://mycourses.aalto.fi/course/search.php?search=NBE-E4130
Prerequisites (valid 01.08.2018-31.07.2020):
Basic knowledge of biophysics and cellular electrophysiology (recommended courses: NBE-C2102 Biophysics, NBE-E4120 Cellular Electrophysiology)
Grading Scale (valid 01.08.2018-31.07.2020):
0 to 5
Further Information (valid 01.08.2018-31.07.2020):
The number of participants may be restricted.
- Teacher: Ala-Laurila Petri
- Teacher: Seppänen Aarni
- Teacher: Tiihonen Jussi