Autumn Semester 2020 takes place in a mixed form of online and classroom teaching.
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227-1037-00L  Introduction to Neuroinformatics

SemesterAutumn Semester 2016
LecturersK. A. Martin, M. Cook, V. Mante, M. Pfeiffer
Periodicityyearly recurring course
Language of instructionEnglish



Catalogue data

AbstractThe course provides an introduction to the functional properties of neurons. Particularly the description of membrane electrical properties (action potentials, channels), neuronal anatomy, synaptic structures, and neuronal networks. Simple models of computation, learning, and behavior will be explained. Some artificial systems (robot, chip) are presented.
ObjectiveUnderstanding computation by neurons and neuronal circuits is one of the great challenges of science. Many different disciplines can contribute their tools and concepts to solving mysteries of neural computation. The goal of this introductory course is to introduce the monocultures of physics, maths, computer science, engineering, biology, psychology, and even philosophy and history, to discover the enchantments and challenges that we all face in taking on this major 21st century problem and how each discipline can contribute to discovering solutions.
ContentThis course considers the structure and function of biological neural networks at different levels. The function of neural networks lies fundamentally in their wiring and in the electro-chemical properties of nerve cell membranes. Thus, the biological structure of the nerve cell needs to be understood if biologically-realistic models are to be constructed. These simpler models are used to estimate the electrical current flow through dendritic cables and explore how a more complex geometry of neurons influences this current flow. The active properties of nerves are studied to understand both sensory transduction and the generation and transmission of nerve impulses along axons. The concept of local neuronal circuits arises in the context of the rules governing the formation of nerve connections and topographic projections within the nervous system. Communication between neurons in the network can be thought of as information flow across synapses, which can be modified by experience. We need an understanding of the action of inhibitory and excitatory neurotransmitters and neuromodulators, so that the dynamics and logic of synapses can be interpreted. Finally, the neural architectures of feedforward and recurrent networks will be discussed in the context of co-ordination, control, and integration of sensory and motor information in neural networks.

Performance assessment

Performance assessment information (valid until the course unit is held again)
Performance assessment as a semester course
ECTS credits6 credits
ExaminersK. A. Martin, M. Cook, V. Mante, M. Pfeiffer
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
Additional information on mode of examinationmultiple choice
Written aidsNone
This information can be updated until the beginning of the semester; information on the examination timetable is binding.

Learning materials

 
Main linkInformation
Only public learning materials are listed.

Courses

NumberTitleHoursLecturers
227-1037-00 VIntroduction to Neuroinformatics2 hrs
Thu09-11I03 G 85 »
09-11I35 F 32 »
K. A. Martin, M. Cook, V. Mante, M. Pfeiffer
227-1037-00 UIntroduction to Neuroinformatics1 hrs
Thu11-12I35 F 32 »
K. A. Martin, M. Cook, V. Mante, M. Pfeiffer

Groups

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Restrictions

There are no additional restrictions for the registration.

Offered in

ProgrammeSectionType
Biology MasterElective Compulsory Master CoursesWInformation
Biomedical Engineering MasterTrack Core CoursesWInformation
Biomedical Engineering MasterRecommended Elective CoursesWInformation
Computational Biology and Bioinformatics MasterAdvanced CoursesWInformation
Health Sciences and Technology MasterElective Courses IIWInformation
Computer Science BachelorElectivesWInformation
MAS in Medical PhysicsCore CoursesWInformation
MAS in Medical PhysicsCore CoursesWInformation
Neural Systems and Computation MasterTheoretical NeurosciencesWInformation
Physics BachelorSelection of Higher Semester CoursesWInformation
Physics MasterSelection: NeuroinformaticsWInformation
Computational Science and Engineering BachelorElectivesWInformation
Computational Science and Engineering MasterElectivesWInformation