title: Random Wiring, Ganglion Cell Mosaics, and the Functional Architecture of the Visual Cortex.
abstract: The architecture of iso-orientation domains in the primary visual cortex (V1) of placental carnivores and primates apparently follows species invariant quantitative laws. Dynamical optimization models assuming that neurons coordinate their stimulus preferences throughout cortical circuits linking millions of cells specifically predict these invariants. This might indicate that V1's intrinsic connectome and its functional architecture adhere to a single optimization principle with high precision and robustness. To validate this hypothesis, it is critical to closely examine the quantitative predictions of alternative candidate theories. Random feedforward wiring within the retino-cortical pathway represents a conceptually appealing alternative to dynamical circuit optimization because random dimension-expanding projections are believed to generically exhibit computationally favorable properties for stimulus representations. Here, we ask whether the quantitative invariants of V1 architecture can be explained as a generic emergent property of random wiring. We generalize and examine the stochastic wiring model proposed by Ringach and coworkers, in which iso-orientation domains in the visual cortex arise through random feedforward connections between semi-regular mosaics of retinal ganglion cells (RGCs) and visual cortical neurons. We derive closed-form expressions for cortical receptive fields and domain layouts predicted by the model for perfectly hexagonal RGC mosaics. Including spatial disorder in the RGC positions considerably changes the domain layout properties as a function of disorder parameters such as position scatter and its correlations across the retina. However, independent of parameter choice, we find that the model predictions substantially deviate from the layout laws of iso-orientation domains observed experimentally. Considering random wiring with the currently most realistic model of RGC mosaic layouts, a pairwise interacting point process, the predicted layouts remain distinct from experimental observations and resemble Gaussian random fields. We conclude that V1 layout invariants are specific quantitative signatures of visual cortical optimization, which cannot be explained by generic random feedforward-wiring models.
authors.affiliation: Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.|Bernstein Center for Computational Neuroscience, Göttingen, Germany.|Bernstein Focus for Neurotechnology, Göttingen, Germany.|Faculty of Physics, University of Göttingen, Göttingen, Germany.|Institute for Theoretical Physics, University of Würzburg, Würzburg, Germany.
authors.forename: Manuel
authors.initials: M
authors.lastname: Schottdorf
authors.affiliation: Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.|Bernstein Center for Computational Neuroscience, Göttingen, Germany.|Bernstein Focus for Neurotechnology, Göttingen, Germany.|Faculty of Physics, University of Göttingen, Göttingen, Germany.|Center for Studies in Physics and Biology, The Rockefeller University, New York, New York, United States of America.
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Keil
authors.affiliation: Department of Biology, Randolph-Macon College, Ashland, Virginia, United States of America.
authors.forename: David
authors.initials: D
authors.lastname: Coppola
authors.affiliation: Department of Orthopaedic Surgery, Duke Institute for Brain Sciences, Duke University, Durham, North Carolina, United States of America.
authors.forename: Leonard E
authors.initials: LE
authors.lastname: White
authors.affiliation: Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.|Bernstein Center for Computational Neuroscience, Göttingen, Germany.|Bernstein Focus for Neurotechnology, Göttingen, Germany.|Faculty of Physics, University of Göttingen, Göttingen, Germany.|Kavli Institute for Theoretical Physics, Santa Barbara, California, United States of America.
authors.forename: Fred
authors.initials: F
authors.lastname: Wolf
mesh_terms: D000818:Animals; D019295:Computational Biology; D008322:Mammals; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology; D012165:Retinal Ganglion Cells / Q000502:physiology*; D014793:Visual Cortex / Q000166:cytology* / Q000502:physiology*