Nonlinear receptive field mapping reveals two subpopulations of orientation selective neurons in V2.

Abstract

Event Abstract Back to Event Nonlinear receptive field mapping reveals two subpopulations of orientation selective neurons in V2. Primary visual cortex (V1) mainly extracts oriented luminance boundaries, while secondary visual cortex (V2) detects more complex boundaries, including texture boundaries. Detection of texture boundaries requires that neurons respond in a nonlinear way to combinations of stimulus components. Such nonlinear interactions have previously been investigated primarily in V1, using stimuli consisting of multiple spots or bars. Here we investigate these interactions in V1 and V2, using stimuli consisting of multiple patches of oriented gratings. Because V1 neurons provide the main input for V2 neurons, understanding these complex responses promises insight into how one cortical region transforms the output of another. We recorded responses from single neurons in V1 and V2 of anesthetized monkeys. Stimuli consisted of a 4 by 5 or 6 by 6 grid of adjacent rectangular regions, covering the classical and non-classical receptive field. Each region contained sinusoidal gratings with either the preferred orientation or the non-preferred orthogonal orientation controlled by m-sequences (frame rate 20 ms). The m-sequences were designed to enable extraction of the first- and second-order response kernels in space as well as time. V1 neurons all have monophasic first-order kernels, and their timing is very consistent across the population. In contrast, V2 neurons have two distinct patterns of responses: some are biphasic, with an initial peak width narrower than the V1 responses (‘transient V2 neurons’); others are monophasic, but with a broader peak than the V1 responses (‘sustained V2 neurons’). The biphasic response pattern indicates dynamic orientation tuning: there are some time lags for which the response to the non-preferred orientation is larger than the response to the preferred orientation. These responses predict that the optimal stimulus within a patch is the non-preferred orientation followed by the preferred orientation. The spatial second-order kernels – how the response to a pair of regions differs from the sum of the responses to the two regions presented independently – enforce the distinctions between V1 and the two V2 subpopulations. Neurons in V1 have nonlinear interactions consistent with cross-orientation suppression. Transient V2 neurons exhibit the opposite: nonlinear interactions that result in cross-orientation facilitation. Sustained V2 neurons show no measurable nonlinear spatial interaction. The temporal second-order kernels – the response to combinations of orientations in subsequent frames – also distinguish the V1 and the two V2 subpopulations. Neurons in V1 mainly sum supralinearly over time, leading to augmentation of responses for prolonged presentations of the same orientation. Transient V2 neurons on the other hand have a preference for changing orientation over time. Sustained V2 neurons show no temporal interaction. This study shows, firstly, how non-linear as well as linear responses of neurons in V1 differ from V2 responses. Secondly, using nonlinear receptive field mapping, we identified two different classes of orientation selective V2 neurons. These results suggest a conceptual model for how V1 outputs are processed to make V2 responses. The transient V2 neurons differentiate the V1 input in space and time and therefore respond well to changes in orientation. Sustained V2 neurons pool the V1 input and respond better to constant orientation signals. Conference: Computational and systems neuroscience 2009, Salt Lake City, UT, United States, 26 Feb - 3 Mar, 2009. Presentation Type: Oral Presentation Topic: Oral Presentations Citation: (2009). Nonlinear receptive field mapping reveals two subpopulations of orientation selective neurons in V2.. Front. Syst. Neurosci. Conference Abstract: Computational and systems neuroscience 2009. doi: 10.3389/conf.neuro.06.2009.03.193 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: 03 Feb 2009; Published Online: 03 Feb 2009. 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 Google Google Scholar PubMed 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.