[visionlist] Call for Papers | Journal of Vision | Special Issue: Deep Neural Networks and Biological Vision

Andrew Watson abwatson at me.com
Wed Oct 9 20:05:38 -04 2019

Journal of Vision
Special Issue
Deep Neural Networks and Biological Vision 

Deep learning is very important today as a tool to study neural circuits and as a model for visual perception. As a powerful new machine learning tool, it can be used to make sense of complex neural data of various kinds.  Deep networks can also serve as abstractions of the visual processing hierarchy, which after training can be analyzed in very much the same way a biological circuit or intact observer would be. The successes and failures of this process teach us potentially important lessons about how natural visual input statistics interact with architectural and task constraints to yield neural representations, and ultimately behavior. The complexities entailed in trying to understand emerging representations in such large yet fully observed systems, can also illustrate the limitations of our traditional approaches, arguing for the need of new tools and conceptual frameworks for thinking about brain computations. 

For this special issue we invite not only research papers but also opinion pieces and papers summarizing and arguing for or against the relevance of deep learning for vision science. We welcome explanations of how these tools can help. Authors may use any of the available article types, including regular, Review, Comment, Emerging trends in Vision Science, and Perspective.

Feature Editors:

Nikolaus Kriegeskorte	Columbia University 
Denis Pelli	New York University
Cristina Savin	New York University
Felix Wichmann	University of Tübingen

Submissions Accepted through December 31, 2020. Accepted papers will be published as ready in the current monthly issue as well as presented together as a special issue on the JOV website.

Journal of Vision is an online, open access, peer-reviewed scientific journal devoted to all aspects of visual function in humans and other organisms. The journal is published exclusively in digital form: full-text articles may be accessed for free via the internet. The journal encourages the effective use of color, multimedia, hyperlinks, program code, and other digital enhancements. Journal of Vision is published by the Association for Research in Vision and Ophthalmology (ARVO). To submit a paper to this special issue please follow the Instructions for Authors <http://journalofvision.org/info/info_for_authors.aspx> at http://journalofvision.org/ <http://journalofvision.org/>. All papers will be subject to peer review.

Andrew B. Watson
Journal of Vision   http://journalofvision.org/

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