Two dimensions for the price of one: the efficient encoding of vertical disparity

Abstract

Event Abstract Back to Event Two dimensions for the price of one: the efficient encoding of vertical disparity Jenny Read1* 1 Newcastle University, Institute of Neuroscience, United Kingdom Usually, in order to encode information about a stimulus property X, one needs a population of neurons tuned to a range of values of X. For example, in order to encode information about photons' wavelength, the retina has to contain cones tuned to long, medium and short wavelengths; people with only a single cone type are color-blind. Here, I present an interesting example of a situation where this does not quite hold. Binocular disparity is a two-dimensional quantity, with components H and V representing the horizontal and vertical differences between where an object projects to in the two eyes. Humans are sensitive to both components, using them to deduce information about 3D scene structure and object distance. Here, I consider a neuronal population of disparity sensors based on the highly successful stereo energy model. I show that a population tuned to a range of different H pref, but all tuned to the same V pref, can nevertheless encode values of V away from V pref, including both their magnitude and sign. This is of interest because in natural images, the range of vertical disparities encountered at any point on the retina is typically very narrow, much less diverse than the range of horizontal disparities. One would therefore expect the brain to contain a much narrower range of vertical disparity tuning than of horizontal disparity tuning: SD(V pref) << SD(H pref). My results show that, in fact, SD(V pref) can be reduced to right down to zero while still retaining information about V. Potentially, this would enable the brain to represent 2D disparity very efficiently, encoding 2D disparity with a purely 1D population (in the sense that the distribution of preferred disparities, (H pref,V pref), lies along a line). This apparent paradox arises because for cells tuned to oblique orientations, the response surface F(H,V) is inseparable. Thus, while the cell responds best to V=V pref when probed at its optimal horizontal disparity H=H pref, at non-optimal horizontal disparities it responds best to vertical disparities on either side of V pref. It has been suggested that these inseparable response surfaces are later converted to separable ones during the cortical processing of disparity, but the present work suggests that the initial, inseparable response may have a role to play in enabling an efficient encoding of 2D disparity. Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010. Presentation Type: Poster Presentation Topic: Poster session I Citation: Read J (2010). Two dimensions for the price of one: the efficient encoding of vertical disparity. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00105 Copyright: The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers. They are made available through the Frontiers publishing platform as a service to conference organizers and presenters. The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated. Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed. For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions. Received: 21 Feb 2010; Published Online: 21 Feb 2010. * Correspondence: Jenny Read, Newcastle University, Institute of Neuroscience, Newcastle upon Tyne, United Kingdom, nemoABS01@frontiersin.org Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. Abstract Info Abstract The Authors in Frontiers Jenny Read Google Jenny Read Google Scholar Jenny Read PubMed Jenny Read Related Article in Frontiers Google Scholar PubMed Abstract Close Back to top Javascript is disabled. Please enable Javascript in your browser settings in order to see all the content on this page.