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<font face="Arial, Helvetica, sans-serif">Understanding principles
of efficient coding can enable you to answer questions such as:
why should the input contrast response function of a neuron take
its particular form? Why do retinal ganglion cells have
center-surround receptive fields? How correlated or uncorrelated
should the visual responses from different retinal ganglion cells
be? Why do receptive fields of retinal ganglion cells increase
their sizes in dim light? How could visual coding depend on animal
species? Why are color selective V1 neurons less sensitive to
visual motion signals? How can one predict the ocular dominance
properties of V1 neurons from developmental conditions? How should
neurons adapt to changes in visual environment? <br>
<br>
This tutorial guides you on how to answer such questions. <br>
<br>
It contains:<br>
(1) A list of 45 short video lecture clips (about 10 minutes each
on average) on YouTube, see <a class="moz-txt-link-freetext"
href="http://www.lizhaoping.org/zhaoping/EfficientVisualCoding_Playlist.html">http://www.lizhaoping.org/zhaoping/EfficientVisualCoding_Playlist.html</a><br>
(2) In addition to (1), you can join CNS *2021 (see <a
class="moz-txt-link-freetext"
href="https://www.cnsorg.org/cns-2021-tutorials#T3">https://www.cnsorg.org/cns-2021-tutorials#T3</a>
), which enables social interactions with the lecturer and other
students via Discord, and on July 3rd (the tutorial day) for
highlights, Q&As, and discussions<font size="2">.<br>
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best,<br>
<br>
Li Zhaoping</font><font face="Arial, Helvetica, sans-serif"><font
size="2"><br>
PS: we also have positions for Human visual psychophysics
postdoc/Ph.D. students and others, see <br>
<a class="moz-txt-link-freetext" href="http://www.lizhaoping.org/jobs.html">http://www.lizhaoping.org/jobs.html</a><br>
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<pre class="moz-signature" cols="72">--
Li Zhaoping, Ph.D.
Prof. of Cognitive Science, University of Tuebingen
Head of Department of Sensory and Sensorimotor Systems,
Max Planck Institute of Biological Cybernetics
Author of "Understanding vision: theory, models, and data", Oxford University Press, 2014
<a class="moz-txt-link-abbreviated" href="http://www.lizhaoping.org">www.lizhaoping.org</a></pre>
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