Kevan A.C. Martin: Katalogdaten im Frühjahrssemester 2018

Auszeichnung: Die Goldene Eule
NameHerr Prof. em. Dr. Kevan A.C. Martin
Adresse
Institut für Neuroinformatik
ETH Zürich, Y55 G 27
Winterthurerstrasse 190
8057 Zürich
SWITZERLAND
Telefon+41 44 635 30 51
E-Mailmartink@ethz.ch
DepartementInformationstechnologie und Elektrotechnik
BeziehungProfessor emeritus

NummerTitelECTSUmfangDozierende
227-1034-00LComputational Vision (University of Zurich) Information
No enrolment to this course at ETH Zurich. Book the corresponding module directly at UZH.
UZH Module Code: INI402

Mind the enrolment deadlines at UZH:
Link
6 KP2V + 1UD. Kiper, K. A. Martin
KurzbeschreibungThis course focuses on neural computations that underlie visual perception. We study how visual signals are processed in the retina, LGN and visual cortex. We study the morpholgy and functional architecture of cortical circuits responsible for pattern, motion, color, and three-dimensional vision.
LernzielThis course considers the operation of circuits in the process of neural computations. The evolution of neural systems will be considered to demonstrate how neural structures and mechanisms are optimised for energy capture, transduction, transmission and representation of information. Canonical brain circuits will be described as models for the analysis of sensory information. The concept of receptive fields will be introduced and their role in coding spatial and temporal information will be considered. The constraints of the bandwidth of neural channels and the mechanisms of normalization by neural circuits will be discussed.
The visual system will form the basis of case studies in the computation of form, depth, and motion. The role of multiple channels and collective computations for object recognition will
be considered. Coordinate transformations of space and time by cortical and subcortical mechanisms will be analysed. The means by which sensory and motor systems are integrated to allow for adaptive behaviour will be considered.
InhaltThis course considers the operation of circuits in the process of neural computations. The evolution of neural systems will be considered to demonstrate how neural structures and mechanisms are optimised for energy capture, transduction, transmission and representation of information. Canonical brain circuits will be described as models for the analysis of sensory information. The concept of receptive fields will be introduced and their role in coding spatial and temporal information will be considered. The constraints of the bandwidth of neural channels and the mechanisms of normalization by neural circuits will be discussed.
The visual system will form the basis of case studies in the computation of form, depth, and motion. The role of multiple channels and collective computations for object recognition will
be considered. Coordinate transformations of space and time by cortical and subcortical mechanisms will be analysed. The means by which sensory and motor systems are integrated to allow for adaptive behaviour will be considered.
LiteraturBooks: (recommended references, not required)
1. An Introduction to Natural Computation, D. Ballard (Bradford Books, MIT Press) 1997.
2. The Handbook of Brain Theorie and Neural Networks, M. Arbib (editor), (MIT Press) 1995.
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:
Link
0 KP1KS.‑C. Liu, R. Hahnloser, V. Mante, K. A. Martin
KurzbeschreibungThe colloquium in Neuroinformatics is a series of lectures given by invited experts. The lecture topics reflect the current themes in neurobiology and neuromorphic engineering that are relevant for our Institute.
LernzielThe goal of these talks is to provide insight into recent research results. The talks are not meant for the general public, but really aimed at specialists in the field.
InhaltThe topics depend heavily on the invited speakers, and thus change from week to week. All topics concern neural computation and their implementation in biological or artificial systems.