Event Abstract Back to Event Responses to complex novel stimuli can be predicted by a simple neuron model of spike generation Henriette Walz1*, André Longtin2 and Jan Benda1 1 Ludwig-Maximilians-Universität München, Department Biologie II, Germany 2 University of Ottawa, Physics, Canada Sensory neurons have to encode stimuli that are drawn from distributions that considerably vary in their mean, standard deviation, spectral content, etc. depending on, for example, task or time of day. This potentially implies that a receptor neuron is driven in different dynamical regimes and that the neuron adapts on longer time scales to accommodate itself to such changes in the input statistics. Therefore, stimuli from all relevant statistics should be used when characterizing a neuron's responses. Alternatively, one can select a smaller set of stimulus classes for a characterization in form of, for example, a computational model and then probe different dynamical regimes of the neuron to challenge this characterization. We exemplify the latter approach on the example of electroreceptive neurons of weakly electric fish. Weakly electric fish use their electric organ discharge (EOD) for electrolocation as well as for communication. Amplitude modulations (AM) of the fish's EOD are encoded in electroreceptors (p-units). Behaviorally relevant AMs result in communication contexts from the interaction with other fish, or in hunting tasks from prey. The receptor cells respond phase-locked and probabilistically to each EOD cycle and show prominent negative serial correlations between successive interspike intervals. We built a simple leaky integrate-and-fire model with adaptation current (LIFAC) and constrained its operating point and intrinsic noise strength by the baseline statistics of measured p-units, while we set its sensitivity and adaptation properties to match responses to step stimuli. This model then not only reproduces the baseline ISI distributions and serial correlations, but also successfully predicts the spike responses to AMs from communication contexts. Interactions of two fish produce sinusoidal beats of a given frequency that are transiently modulated by communication signals. Therefore, the stimuli we used to probe our model, contain more complex dynamics than those the model is adjusted for. The generalizing properties of such a single cell model are based on the use of canonical models for the spike-generation and adaptation dynamics. By using established measurements to determine the parameters of the different processes, the model then captures the dynamics of the measured neuron for a large range of different stimulus classes. Therefore, we have shown that a simple model of spike generation can reproduce the behavior of a receptor cell to statistically different stimuli even when only constrained to its baseline statistics and step responses. Keywords: sensory processing Conference: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011, Freiburg, Germany, 4 Oct - 6 Oct, 2011. Presentation Type: Poster Topic: sensory processing (please use "sensory processing" as keyword) Citation: Walz H, Longtin A and Benda J (2011). Responses to complex novel stimuli can be predicted by a simple neuron model of spike generation. Front. Comput. Neurosci. Conference Abstract: BC11 : Computational Neuroscience & Neurotechnology Bernstein Conference & Neurex Annual Meeting 2011. doi: 10.3389/conf.fncom.2011.53.00130 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: 23 Aug 2011; Published Online: 04 Oct 2011. * Correspondence: Miss. Henriette Walz, Ludwig-Maximilians-Universität München, Department Biologie II, Martinsried, 82152, Germany, walz@bio.lmu.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 Henriette Walz André Longtin Jan Benda Google Henriette Walz André Longtin Jan Benda Google Scholar Henriette Walz André Longtin Jan Benda PubMed Henriette Walz André Longtin Jan Benda 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.