227-0395-00L  Neural Systems

SemesterSpring Semester 2018
LecturersR. Hahnloser, M. F. Yanik, B. Grewe
Periodicityyearly recurring course
Language of instructionEnglish



Courses

NumberTitleHoursLecturers
227-0395-00 VNeural Systems2 hrs
Mon09:15-11:00LFV E 41 »
R. Hahnloser, M. F. Yanik, B. Grewe
227-0395-00 UNeural Systems1 hrs
Mon11:15-12:00LFV E 41 »
R. Hahnloser, M. F. Yanik, B. Grewe
227-0395-00 ANeural Systems1 hrsR. Hahnloser, M. F. Yanik, B. Grewe

Catalogue data

AbstractThis course introduces principles of information processing in neural systems. It covers basic neuroscience on a level suitable for engineering students. The course introduces neuroscientific techniques used in studies of both animal behaviors and their underlying neural mechanisms. Students learn about neural signaling principles gained from experimental data.
ObjectiveThis course introduces
- Methods for monitoring of animal behaviors in complex environments
- Information-theoretic principles of behavior
- Methods for performing neurophysiological recordings in intact nervous systems
- Methods for manipulating the state and activity in selective neuron types
- Methods for reconstructing the synaptic networks among neurons
- Information decoding from neural populations, and
- Neurobiological principles for machine learning.
ContentFrom active membranes to propagation of action potentials. From synaptic physiology to synaptic learning rules. From receptive fields to neural population decoding. From fluorescence imaging to connectomics. Methods for reading and manipulation neural ensembles. From classical conditioning to reinforcement learning. From the visual system to deep convolutional networks. Brain architectures for learning and memory. From birdsong to computational linguistics.
Prerequisites / NoticeBefore taking this course, students are encouraged to complete "Bioelectronics and Biosensors" (227-0393-10L)

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits6 credits
ExaminersR. Hahnloser, B. Grewe, M. F. Yanik
Typesession examination
Language of examinationEnglish
RepetitionThe performance assessment is offered every session. Repetition possible without re-enrolling for the course unit.
Mode of examinationwritten 120 minutes
Written aidsnone (closed book exam)
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

No public learning materials available.
Only public learning materials are listed.

Groups

No information on groups available.

Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Electrical Engineering and Information Technology BachelorThird Year Core CoursesWInformation
Health Sciences and Technology MasterElective Courses IIWInformation
Neural Systems and Computation MasterSystems NeurosciencesWInformation
Neural Systems and Computation MasterElectivesWInformation
Neural Systems and Computation MasterNeural Computation and Theoretical NeurosciencesWInformation
Physics MasterGeneral ElectivesWInformation