Basic Training

We start with an intensive two weeks course in form of a retreat for everyone. The most important aim of this course is to bring doctoral researchers to an equal state of base knowledge and enable them to understand the language and techniques of the different disciplines. Transdisciplinary training is the key for success in InnoRetVision. Biologists must be introduced to the technical aspects of implant design, and engineers must be familiarized with the basic knowledge in neuroscience. We will tailor the presentations to the fact that trainees will have highly diverse backgrounds to achieve maximal transdisciplinary training. The retreat will cover the following topics:



Content (Supervisor, Duration)

Introduction to Cell Biology

Design and function of higher (eukaryotic) cells with special focus on e.g. membranes, ionic composition, from gene to protein. (Müller; 4 h)

Foundations in Neuroscience

Anatomy and physiology of the nervous system with special focus on the visual system, in particular the retina, retinal signal processing, and the different types of retinal diseases. (Müller, Walter; 10 h)

Foundations in Electrophysiology

Physiology of electrical activity and excitability of neurons. Standard techniques for recording and electrical stimulation like extracellular recording, evoked potentials, multi electrode arrays, patch-clamp technique, interaction of electrical devices with cells and tissue. (Offenhäusser, Ingebrandt, Walter; 12 h)

Basics in Electrical Engineering

Electrical phenomena, physical quantities and units, network concepts and linear passive DC-circuits, electronic devices and simple circuits like transistor or basic operational amplifier circuits. (Mokwa, Ingebrandt; 14 h)

Fundamentals of Electrical Stimulation.

Basics of electrical stimulation in a sub-module. The charge transfer processes from electronics to tissue. Basics of alternating current theory. Measurement methods from electrochemistry. (Kokozinski, Seidl; 3 h)

Scientific Computing, Statistics, and Data Evaluation I

Experimental design, data evaluation and basics of statistics. Quantitative, analytic, and statistical skills as well as data visualization. (Kampa, Merhof; 10 h)

Discussions and Project Plans

Scientific and technical concepts and design of experiments.Basis for individual discussions on PhD thesis projects. (Different PIs; 5 h)