Event Abstract Back to Event Multimodal map formation without visual teacher: A dynamical model for the blind Mexican cavefish Astyanax Mexicanus. Matthias Krippner1, Julie Goulet1* and J. Leo Van Hemmen1 1 Technical University Munich, Physik, Germany About fifty percent of all vertebrates are fish. Since fish live in water where quite often light (and therefore vision) is not a useful signal they should rely on other sensory inputs. One of them is water motion that they can detect through their lateral-line system. The mechanosensory lateral line, unique to aquatic vertebrates, is divided into two subsystems, viz., superficial (SN) and canal neuromasts (CN) that both exhibit different response properties to hydrodynamic stimuli. Previous studies have shown that SNs encode water velocity, CNs respond to its first derivative, namely, water acceleration. From previous work we also know the spatiotemporal distribution of firing rates for SNs and CNs based on the hydrodynamics of a sphere moving along the fish's lateral-line system. The key question we now investigate is how fish can use CN and SN input modalities to build an internal representation of a moving object positioned at a certain position and distance. We show that a simple two-layer network is capable to extract the position information with high precision not only from ideal sensory input, but also for very noisy input and signals with different offset and amplitude. The integration of both SN and CN signals within a multimodal map on the one hand further stabilizes the localization, but it is also crucial to the learning process. Particularly, animals such as the blind Mexican cavefish (Astyanax Mexicanus), which lack visual input as a distinctive teacher, need to strongly exploit correlations between different modalities of the rather blurred lateral-line input and the feedback coming from higher brain area to still be able to learn a precise map. By applying stability analysis to the dynamic we describe the actual map formation and derive a suitable Hebbian learning rule. Finally, we study the associated stable manifold to get possible initial conditions that enable multimodal integration in a neuronal system such as the lateral-line system of fish. *The contribution of the first two authors is equal. Keywords: Learning and plasticity, Lateral Line, Hebbian plasticity, Nonlinear Dynamics, Feedback Conference: Bernstein Conference 2012, Munich, Germany, 12 Sep - 14 Sep, 2012. Presentation Type: Poster Topic: Learning, plasticity, memory Citation: Krippner M, Goulet J and Van Hemmen J (2012). Multimodal map formation without visual teacher: A dynamical model for the blind Mexican cavefish Astyanax Mexicanus.. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference 2012. doi: 10.3389/conf.fncom.2012.55.00027 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: 02 Jun 2012; Published Online: 12 Sep 2012. * Correspondence: Dr. Julie Goulet, Technical University Munich, Physik, Munich, 85748, Germany, julie@ph.tum.de 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 Matthias Krippner Julie Goulet J. Leo Van Hemmen Google Matthias Krippner Julie Goulet J. Leo Van Hemmen Google Scholar Matthias Krippner Julie Goulet J. Leo Van Hemmen PubMed Matthias Krippner Julie Goulet J. Leo Van Hemmen 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.