Event Abstract Back to Event Emerging Representational Geometry for Objects Predicts Reaction Time for Categorization J.Brendan Ritchie1, 2*, David A. Tovar3 and Thomas A. Carlson1 1 Macquarie University, Department of Cognitive Science, Australia 2 University of Maryland, College Park, Department of Philosophy, United States 3 Vanderbilt University, School of Medicine, United States i. Background: Human and primate neurophysiological studies have characterized a representational geometry for visual objects in inferior temporal cortex (ITC), in which individual object exemplars can be discriminated and cluster based on category (e.g. faces). Two outstanding questions are: when does this representational geometry emerge; and how does the structure of this geometry relate to behavior? Two recent findings make important progress on these questions. First, the emerging representational geometry of objects can be resolved with high temporal resolution using multivariate pattern analyses in conjunction with Magnetoencephalography (MEG decoding). Second, it has been shown that reaction times (RT) for object categorization are predicted by the structure of ITC’s representation of objects using fMRI in humans. In the present study we extend these findings to show RTs for object categorization can be predicted by the geometry of the brain’s representation of objects shortly after the presentation of a visual stimulus. ii. Methods: 32 subjects were shown 24 object exemplar images, which they categorized as either animate or inanimate, while their brain activity was recorded using MEG. Time-resolved MEG decoding was used to reconstruct the brain’s representational geometry of these object exemplars on a moment to moment basis (20ms resolution). For each time point, we used linear discriminant analysis to determine the decision boundary in representational space for classification of the exemplars into the categories of animacy and inaninmacy. We then computed the distance of individual exemplar representations from the decision boundary. Classical signal detection theory (SDT) predicts a negative relationship between distance from the boundary and RT. iii. Results: In accordance with the prediction from SDT, and previous findings using fMRI, we found that distance from the decision boundary negatively correlated with RTs at 200 post-stimulus onset. iv. Discussion: The present results show that the structure of the brain’s emerging representational geometry of objects predicts behavioral RTs, supporting the contention that “representing” is constitutive of decision-making for object categorization. Keywords: Object Categorization, neural decoding, Magnetoencephalography, Decision Making, Reaction Time Conference: ACNS-2013 Australasian Cognitive Neuroscience Society Conference, Clayton, Melbourne, Australia, 28 Nov - 1 Dec, 2013. Presentation Type: Poster Topic: Sensation and Perception Citation: Ritchie J, Tovar DA and Carlson TA (2013). Emerging Representational Geometry for Objects Predicts Reaction Time for Categorization. Conference Abstract: ACNS-2013 Australasian Cognitive Neuroscience Society Conference. doi: 10.3389/conf.fnhum.2013.212.00029 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: 15 Oct 2013; Published Online: 25 Nov 2013. * Correspondence: Mr. J.Brendan Ritchie, Macquarie University, Department of Cognitive Science, Sydney, Australia, john.ritchie@mq.edu.au 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 J.Brendan Ritchie David A Tovar Thomas A Carlson Google J.Brendan Ritchie David A Tovar Thomas A Carlson Google Scholar J.Brendan Ritchie David A Tovar Thomas A Carlson PubMed J.Brendan Ritchie David A Tovar Thomas A Carlson 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.