Suchergebnis: Katalogdaten im Frühjahrssemester 2020
|Gesundheitswissenschaften und Technologie Master
|Vertiefung in Neurowissenschaften
|Neural Control of Movement and Motor Learning
|This course extends the students' knowledge regarding the neural control of movement and motor learning. Particular emphasis will be put on those methods and experimental findings that have shaped current knowledge of this area.
|Knowledge of the physiological and anatomic basis underlying the neural control of movement and motor learning. One central element is that students have first hands-on experience in the lab where small experiments are independently executed, analysed and interpreted.
More information at:https://studentservices.uzh.ch/uzh/anonym/vvz/index.html#/details/2019/004/P/01106803
|G. Schratt, Uni-Dozierende
|The lecture series "Clinical Neuroscience" presents a comprehensive, condensed overview of the most important neurological diseases, their clinical presentation, diagnosis, therapy options and possible causes. Patient demonstrations (Übungen) follow every lecture that is dedicated to a particular disease.
|By the end of this module students should be able to:
- demonstrate their understanding and deep knowledge concerning the main neurological diseases
- identify and explain the different clinical presentation of these diseases, the methodology of diagnosis and the current therapies available
- summarize and critically review scientific literature efficiently and effectively
|Modeling and Methods in Human Behavioural Neuroscience
|G. Bertolini, F. Romano
|The course presents models in human behavioral neuroscience and methods to:
1) Adapt the models to embed hypotheses;
2) Make model-based predictions;
3) Use models when designing data collections that verify/disprove predictions
|At the end of this module students should know:
• different types of models used in human behavioral neuroscience, their features and their limits
• how to use models to estimate expected human behavioural outcomes or to interpret behavioural data
• how to implement models and methods via software (Matlab)
|1. Linear time-invariant model and their practical applications on neuroscience systems (e.g. sensory input, motor control). From equations to block diagram representation.
2. Psychophysical methods to test human perceptual response and statistical models of behaviour (e.g. Bayesian model). Examples from tasks probing perceptual responses.
3. How the brain controls our body through internal models (feedforward and feedback). Examples from motor and balance tasks. The optimal observer as a model of how the human brain interprets inputs, plans and compares actions and finally executes them.
The course will combine theoretical and practical knowledge on how to implement models and techniques via software on datasets (Matlab)
|S. Werner, M. Bordoli, W. Kovacs, M. Schäfer, U. Suter, A. Wutz
|This Course introduces principle concepts, techniques, and experimental strategies used in modern Cell Biology. Major topics include: neuron-glia interactions in health and disease; mitochondrial dynamics; stem cell biology; growth factor action in development, tissue repair and disease; cell metabolism, in particular sensing and signaling mechanisms, cell organelles, and lipid metabolism.
|-To prepare the students for successful and efficient lab work by learning how to ask the right questions and to use the appropriate techniques in a research project.
-To convey knowledge about neuron-glia interactions in health and disease.
- To provide information on different types of stem cells and their function in health and disease
-To provide information on growth factor signaling in development, repair and disease and on the use of growth factors or their receptors as drug targets for major human diseases
-To convey knowledge on the mechanisms underlying repair of injured tissues
-To provide the students with an overview of mitochondrial dynamics.
-Providing an understanding of RNA processing reactions and their regulations.
-To provide a comprehensive understanding of metabolic sensing mechanisms occurring in different cell types and organelles in response to glucose, hormones, oxygen, nutrients as well as lipids, and to discuss downstream signaling pathways and cellular responses.
-To provide models explaining how disturbances in complex metabolic control networks and bioenergetics can lead to disease and to highlight latest experimental approaches to uncover the intricacies of metabolic control at the cellular and organismal level.
-Providing the background and context that foster cross-disciplinary scientific thinking.
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