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Valerio Mante: Katalogdaten im Herbstsemester 2016

NameHerr Valerio Mante
Institut für Neuroinformatik
ETH Zürich, Y55 G 27
Winterthurerstrasse 190
8057 Zürich
DepartementInformationstechnologie und Elektrotechnik

227-1037-00LIntroduction to Neuroinformatics Information 6 KP2V + 1UK. A. Martin, M. Cook, V. Mante, M. Pfeiffer
KurzbeschreibungThe 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.
LernzielUnderstanding 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.
InhaltThis 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.
227-1039-00LBasics of Instrumentation, Measurement, and Analysis (University of Zurich) Belegung eingeschränkt - Details anzeigen
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI502

Mind the enrolment deadlines at UZH:

Registration in this class requires the permission of the instructors. Class size will be limited to available lab spots.
Preference is given to students that require this class as part of their major.
4 KP9VS.‑C. Liu, T. Delbrück, A. Ghosh, R. Hahnloser, G. Indiveri, V. Mante, P. Pyk, W. von der Behrens
KurzbeschreibungExperimental data are always as good as the instrumentation and measurement, but never any better. This course provides the very basics of instrumentation relevant to neurophysiology and neuromorphic engineering, it consists of two parts: a common introductory part involving analog signals and their acquisition (Part I), and a more specialized second part (Part II).
LernzielThe goal of Part I is to provide a general introduction to the signal acquisition process. Students are familiarized with basic lab equipment such as oscilloscopes, function generators, and data acquisition devices. Different electrical signals are generated, visualized, filtered, digitized, and analyzed using Matlab (Mathworks Inc.) or Labview (National Instruments).

In Part II, the students are divided into small groups to work on individual measurement projects according to availability and interest. Students single-handedly solve a measurement task, making use of their basic knowledge acquired in the first part. Various signal sources will be provided.
Voraussetzungen / BesonderesFor each part, students must hand in a written report and present a live demonstration of their measurement setup to the respective supervisor. The supervisor of Part I is the teaching assistant, and the supervisor of Part II is task specific. Admission to Part II is conditional on completion of Part I (report + live demonstration).

Reports must contain detailed descriptions of the measurement goal, the measurement procedure, and the measurement outcome. Either confidence or significance of measurements must be provided. Acquisition and analysis software must be documented.
227-1043-00LNeuroinformatics - Colloquia (University of Zurich)
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI701

Mind the enrolment deadlines at UZH:
0 KP1KS.‑C. Liu, R. Hahnloser, V. Mante, K. A. Martin
KurzbeschreibungDas Kolloquium der Neuroinformatik ist eine Vortragsserie eingeladener Experten. Die Vorträge spiegeln Schwerpunkte aus der Neurobiologie und des Neuromorphic Engineering wider, die speziell für unser Institut von Relevanz sind.
LernzielDie Vorträge informieren Studenten und Forscher über neueste Forschungsergebnisse. Dementsprechend sind die Vorträge primaer nicht fuer wissenschaftliche Laien, sondern für Forschungsspezialisten konzipiert.
InhaltDie Themen haengen stark von den eingeladenen Spezialisten ab und wechseln von Woche zu Woche. Alle Themen beschreiben aber 'Neural computation' und deren Implementierung in biologischen und kuenstlichen Systemen.