Computational Neuroscience

Semester plan

1. Semester 127 ECTS requiredAcquisition and Analysis of Neural Data · Machine Intelligence · Models of Higher Brain Functions · Models of Neural Systems · Programming Course and Project

   • Acquisition and Analysis of Neural DataSummary by OWWZ: Students explore methods for recording cellular and large-scale brain signals through practical work. Analysis covers spike statistics, neural coding, information theory, EEG processing, spatial filtering and classification.Semesters 1–2Exam (in German): Mündliche Prüfung, 20–60 Min.12 ECTS
   • Machine IntelligenceSummary by OWWZ: Machine learning is studied through neural networks, support vector machines, probabilistic models and reinforcement learning. Dimensionality reduction, clustering and stochastic optimization complement exercises in implementation and critical evaluation.Semesters 1–2Exam (in German): Mündliche Prüfung, 20–60 Min.12 ECTS
   • Models of Higher Brain FunctionsSummary by OWWZ: Cognitive neuroscience and computational models explain perception, attention, memory, decisions and motor control. Analytical exercises and Python simulations develop skills in evaluating models and applying them to new experiments.Semesters 1–2Exam (in German): Mündliche Prüfung, 20–60 Min.12 ECTS
   • Models of Neural SystemsSummary by OWWZ: Biophysical and mathematical models describe neuronal membranes, synapses and networks. Analytical exercises and simulations examine spike propagation, synaptic plasticity, learning rules and the dynamics of neural systems.Semesters 1–2 · winter semester onlyExam (in German): Mündliche Prüfung, 20–60 Min.12 ECTS
   • Programming Course and ProjectSummary by OWWZ: A substantial software project develops structured Python programming and collaborative development skills. Students practise version control, testing, documentation, debugging and optimization, and review one another’s code.Semesters 1–2 · summer semester onlyExam (in German): Studienbegleitende Prüfungsleistungen, unbenotet6 ECTS
2. Semester 230 ECTS requiredEthical Issues and Implications for SocietyContinues: Acquisition and Analysis of Neural Data, Machine Intelligence, Models of Higher Brain Functions, Models of Neural Systems, Programming Course and Project

   • Ethical Issues and Implications for SocietySummary by OWWZ: Students examine ethical issues in animal experiments, stem-cell research, clinical studies and mental privacy. Group discussions address practical dilemmas alongside good scientific practice, data protection and computer security.winter semester onlyExam (in German): Studienbegleitende Prüfungsleistungen, unbenotet3 ECTS
3. Semester 323 ECTS required · 1 elective catalogueLab Rotation · Lab Rotation · Lab Rotation · Required elective from Vertiefungsthemen

   • Lab RotationSummary by OWWZ: Three research projects introduce different research groups and combine experimental and theoretical approaches. Topics and work plans are agreed with the mentor and supervisor and approved by the examination board.Exam (in German): Studienbegleitende Prüfungsleistungen, unbenotet9 ECTS
   • Lab RotationSummary by OWWZ: Three research projects introduce different research groups and combine experimental and theoretical approaches. Topics and work plans are agreed with the mentor and supervisor and approved by the examination board.Exam (in German): Studienbegleitende Prüfungsleistungen, unbenotet9 ECTS
   • Lab RotationSummary by OWWZ: Three research projects introduce different research groups and combine experimental and theoretical approaches. Topics and work plans are agreed with the mentor and supervisor and approved by the examination board.Semesters 3–4Exam (in German): Studienbegleitende Prüfungsleistungen, unbenotet9 ECTS

   Required elective from Vertiefungsthemen5 modules · choose 10 ECTS

   • Mathematics Prep-Course for Computational NeuroscienceSummary by OWWZ: This preparatory course reviews calculus, linear algebra, complex numbers, Fourier transforms, differential equations and probability. Daily exercises strengthen mathematical methods for neural modelling and data analysis.Semesters 3–4 · winter semester onlyExam (in German): Unbenotete Klausur.4 ECTSRequired elective
   • Neurobiology Preparatory CourseSummary by OWWZ: Cellular and neural physiology, brain anatomy and circuitry provide biological foundations for computational models. Topics include sensory processing, learning, memory and experimental approaches such as electrophysiology and imaging.Semesters 3–4 · winter semester onlyExam (in German): Unbenotete Klausur.2 ECTSRequired elective
   • Neural Noise and Neural Signals - Spontaneous Activity and Information Transmission in Models of Single Nerve CellsSummary by OWWZ: Stochastic models describe spontaneous neural activity and information transfer. Noise sources, spike variability, integrate-and-fire neurons, resonance and adaptation are analysed using nonlinear dynamics, stochastic processes and information theory.Semesters 3–4 · summer semester onlyExam (in German): Benotete mündliche Prüfung.6 ECTSRequired elective
   • Stochastic Partial Differential EquationsSummary by OWWZ: Stochastic evolution equations model spatially extended neural systems subject to noise. Gaussian measures and stochastic integration in Hilbert spaces underpin reaction-diffusion systems, continuum limits, and analytical and numerical investigation.Semesters 3–4 · summer semester onlyExam (in German): Benotete mündliche Prüfung.10 ECTSRequired elective
   • Stochastic Processes in NeuroscienceSummary by OWWZ: Brownian motion and stochastic calculus support the study of noisy neuron models. Coupled neurons, synchronization, stability and travelling waves in neural fields are investigated through qualitative and quantitative analysis and simulation.Semesters 3–4 · winter semester onlyExam (in German): Benotete mündliche Prüfung.10 ECTSRequired elective
4. Semester 425 ECTS requiredMaster ThesisContinues: Lab Rotation

   • Master ThesisSummary by OWWZ: The thesis independently investigates a scientific question in a chosen research area. Topics may be interdisciplinary and build on a lab rotation; results are reported according to good scientific practice and defended publicly.ThesisExam (in German): Benotete Masterarbeit mit öffentlicher Verteidigung.20 ECTS

Topic profile

ECTS by topic from the curriculum’s modules; together at most the programme’s ECTS.RequiredElective

• Neuroscience12 ECTS: 11 required, 1 elective12 ECTS
• Programming7 ECTS: 7 required7 ECTS
• Differential equations6 ECTS: 4 required, 2 elective6 ECTS
• Machine learning6 ECTS: 6 required6 ECTS
• Dynamical systems5 ECTS: 4 required, 1 elective5 ECTS
• Probability and stochastics5 ECTS: 3 required, 2 elective5 ECTS
• Biological psychology and neuropsychology4 ECTS: 4 required4 ECTS
• Neural networks and deep learning3 ECTS: 3 required3 ECTS

Curriculum sources

• Studienordnung – Computational NeuroscienceStudy regulations · Version Vom 26. September 2005 · checked 15 October 2026
• Prüfungsordnung – Computational NeuroscienceExamination regulations · Version Vom 26. September 2005 · checked 15 October 2026
• Course Catalogue – Computational NeuroscienceModule handbook · Version 04.03.2022 · checked 17 October 2026