Cross-correlation analysis reveals circuits and mechanisms underlying direction selectivity.

Abstract

Event Abstract Back to Event Cross-correlation analysis reveals circuits and mechanisms underlying direction selectivity. Pamela M. Baker1* and Wyeth Bair1 1 University of Oxford, Department of Physiology, Anatomy and Genetics, United Kingdom Cross-correlation of spike trains from pairs of neurons has proved valuable for investigating functional connectivity in the visual system. It has revealed the specific functional connections between the lateral geniculate nucleus (LGN) and simple cells in primary visual cortex (V1) [1], and exposed properties of simple cells that drive complex cells [2]. Direction selectivity is a fundamental physiological property that arises from V1 circuitry yet basic questions of how direction selective (DS) receptive fields are constructed remain unanswered. To guide experiments for uncovering cortical mechanisms of direction selectivity, we implemented a set of plausible network models of DS neurons. We demonstrate how cross-correlation analysis can reveal the circuitry and mechanisms generating DS cells, including the nature of the DS nonlinearity and the stage in the visual pathway where the time delay, inherent to motion detection, originates. Our models consisted of LGN cells, V1 simple and complex DS cells that were spiking, conductance-based integrate and fire units with physiologically-realistic intrinsic currents connected by AMPA and GABA-A synapses. We tested model architectures where DS neurons are built directly from LGN inputs or indirectly via orientation-tuned simple cells. In some models, the time delay was implemented via temporal diversity in LGN inputs, in others it was ascribed to dendritic mechanisms in the DS neuron. Both have received recent attention experimentally [3,4]. We also varied whether the DS interaction was facilitatory or suppressive. We computed shuffle-corrected cross-correlograms (CCGs) of spike trains from pairs of units that are accessible to extracellular recording in vivo. We tested the models with visual stimuli employed experimentally, including sinusoidal gratings and flashed dots. We found that cross-correlation is well-suited to determine where the DS time delay arises. In models where temporally-offset inputs synapse onto the DS unit, the peak in the CCG between any non-DS input and the DS cell occurred at the time lag typical of monosynaptically connected cells. In models where the delay was generated in dendritic subunits within the DS cell, the CCG peak shifted systematically to reflect the postsynaptic delays. Cross-correlation revealed the nature of the DS nonlinearity, with facilitatory and suppressive DS mechanisms generating distinct shapes in CCGs. We also identified key factors that determine whether connections between non-DS and DS cells are revealed in CCGs. For example, suppressive mechanisms may only become apparent in CCGs if stimuli that drive the cell in the anti-preferred direction are used. This stimulus dependence reflects the selectivity of the DS mechanism, not the input cells themselves, and is thus independent of network architecture. We explored how the magnitude of peaks and dips in the CCG change as strength and number of inputs to the DS cell vary. We address how these factors create challenges for employing this analysis in electrophysiological recording. Overall, our results suggest that CCGs from simultaneously recorded pre- and post-synaptic non-DS and DS cells, respectively, are necessary and likely sufficient for solving long-standing problems of circuitry and mechanisms underlying cortical direction selectivity. Conference: Computational and Systems Neuroscience 2010, Salt Lake City, UT, United States, 25 Feb - 2 Mar, 2010. Presentation Type: Poster Presentation Topic: Poster session II Citation: Baker PM and Bair W (2010). Cross-correlation analysis reveals circuits and mechanisms underlying direction selectivity.. Front. Neurosci. Conference Abstract: Computational and Systems Neuroscience 2010. doi: 10.3389/conf.fnins.2010.03.00332 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: 08 Mar 2010; Published Online: 08 Mar 2010. * Correspondence: Pamela M Baker, University of Oxford, Department of Physiology, Anatomy and Genetics, Oxford, United Kingdom, pb2001@gmail.com Login Required This action requires you to be registered with Frontiers and logged in. To register or login click here. 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