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CNS*2021 Workshop on Methods of Information Theory in Computational Neuroscience

Information in the brain. Modified from an original credited to dow_at_uoregon.edu (distributed without restrictions)

06-07 July, 2021

Online

CNS*2021

Aims and topics

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.

Registration and Access

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).

Time

The workshop will take place on the 6th and 7th of July. The exact time and sessions will be annouced later.

Awards

We would like to thank the Entropy journal for sponsoring our Best Presentation Award for ECRs Best presentation award sponser: Entropy

Organising committee

Speakers

The following are invited speakers for the workshop. We will add contributed short talks closer to the event (as per below).

Call for short talks

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 (abdullah.alimakkeh@uni-goettingen.de).

Program

To be announced!

Abstracts

To be announced!

CNS*2021 Related Tutorials

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, li.zhaoping@tuebingen.mpg.de

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:

Please email Li Zhaoping at zhaoping.li.admin@tuebingen.mpg.de for enquiries.

Previous workshops

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:

  1. CNS*2020 Workshop, July 21-22, 2020, Online!
  2. CNS*2019 Workshop, July 16-17, 2019, Barcelona, Spain.
  3. CNS*2018 Workshop, July 17-18, 2018, Seattle, USA.
  4. CNS*2017 Workshop, July 19-20, 2017, Antwerp, Belgium.
  5. CNS*2016 Workshop, July 6-7, 2016, Jeju, South Korea.
  6. CNS*2015 Workshop, July 22-23, 2015, Prague, Czech Republic.
  7. CNS*2014 Workshop, July 30-31, 2014, Québec City, Canada.
  8. CNS*2013 Workshop, July 17-18, 2013, Paris, France.
  9. CNS*2012 Workshop, July 25-26, 2012, Atlanta/Decatur, GA, USA.
  10. CNS*2011 Workshop, July 27-28, 2011, Stockholm, Sweden.
  11. CNS*2010 Workshop, July 29-30, 2010, San Antonio, TX, USA.
  12. CNS*2009 Workshop, July 22-23, 2009, Berlin, Germany.
  13. CNS*2008 Workshop, July 23-24, 2008, Portland, OR, USA.
  14. CNS*2007 Workshop, July 11-12, 2007, Toronto, Canada.
  15. CNS*2006 Workshop, June 19-20, 2006, Edinburgh, U.K.

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