Home > Conferences > CNS*2021-ITW
06-07 July, 2021
Methods originally developed in Information Theory have found wide applicability in computational neuroscience. Beyond these original methods there is a need to develop novel tools and approaches that are driven by problems arising in neuroscience.
A number of researchers in computational/systems neuroscience and in information/communication theory are investigating problems of information representation and processing. While the goals are often the same, these researchers bring different perspectives and points of view to a common set of neuroscience problems. Often they participate in different fora and their interaction is limited.
The goal of the workshop is to bring some of these researchers together to discuss challenges posed by neuroscience and to exchange ideas and present their latest work.
The workshop is targeted towards computational and systems neuroscientists with interest in methods of information theory as well as information/communication theorists with interest in neuroscience.
For the program of the past IT workshops see the Previous workshops section.
The workshop will be held as a part of the wider CNS*2021 online meeting. Please see the CNS*2021 website for registration to the workshops (this is required to attend).
The workshop will take place on the 6th and 7th of July. The exact time and sessions will be annouced later.
We would like to thank the Entropy journal for sponsoring our Best Presentation Award for ECRs
The following are invited speakers for the workshop. We will add contributed short talks closer to the event (as per below).
In addition to our invited speakers, we will issue a call for short talks in June. If you would like to be notified when the call is made, please email Abdullah Makkeh (firstname.lastname@example.org).
To be announced!
We are happy to point out for a CNS*2021 Tutorial which looks at the Visual Cortex from an Information processing lens
Title: Understanding early visual receptive fields from efficient coding principles
Organizers Li Zhaoping, Max Planck Institute for Biological Cybernetics, University of Tuebingen, Germany, email@example.com
Tutorial format: half-day
Description: 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 decorrelated 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? This tutorial guides you on how to answer such questions. The detailed content can be seen from the titles of the video clips at this link.
Depending on the learning effort invested, the following are possible outcomes after the tutorial: (1) participants can get a gist of, or an introduction to, this topic; (2) participants can learn enough to collaborate with experts on this topic, whether as an experimentalist collaborating with a theorist/modeler, or as a modeler/theorist collaborating with an experimentalist, (3) participants can learn enough to become independent researchers on this topic.
The tutorial material is based largely on chapter 3 (and some of chapter 4) of the textbook "Understanding vision: theory, models, and data" published by Oxford University Press. This book is available in many university libraries (in ebook form, hard copy, or paper back), see for more information. Since the video clips are quite detailed, it is also feasible (although less convenient) to learn without having the textbook.
This tutorial has the following parts:
This workshop has been run at CNS for over a decade now -- links to the websites for the previous workshops in this series are below:
Image modified from an original credited to dow_at_uoregon.edu, obtained here (distributed without restrictions); modified image available here under CC-BY-3.0