5 research outputs found
Understanding visual map formation through vortex dynamics of spin Hamiltonian models
The pattern formation in orientation and ocular dominance columns is one of
the most investigated problems in the brain. From a known cortical structure,
we build spin-like Hamiltonian models with long-range interactions of the
Mexican hat type. These Hamiltonian models allow a coherent interpretation of
the diverse phenomena in the visual map formation with the help of relaxation
dynamics of spin systems. In particular, we explain various phenomena of
self-organization in orientation and ocular dominance map formation including
the pinwheel annihilation and its dependency on the columnar wave vector and
boundary conditions.Comment: 4 pages, 15 figure
Coverage, Continuity and Visual Cortical Architecture
The primary visual cortex of many mammals contains a continuous
representation of visual space, with a roughly repetitive aperiodic map of
orientation preferences superimposed. It was recently found that orientation
preference maps (OPMs) obey statistical laws which are apparently invariant
among species widely separated in eutherian evolution. Here, we examine whether
one of the most prominent models for the optimization of cortical maps, the
elastic net (EN) model, can reproduce this common design. The EN model
generates representations which optimally trade of stimulus space coverage and
map continuity. While this model has been used in numerous studies, no
analytical results about the precise layout of the predicted OPMs have been
obtained so far. We present a mathematical approach to analytically calculate
the cortical representations predicted by the EN model for the joint mapping of
stimulus position and orientation. We find that in all previously studied
regimes, predicted OPM layouts are perfectly periodic. An unbiased search
through the EN parameter space identifies a novel regime of aperiodic OPMs with
pinwheel densities lower than found in experiments. In an extreme limit,
aperiodic OPMs quantitatively resembling experimental observations emerge.
Stabilization of these layouts results from strong nonlocal interactions rather
than from a coverage-continuity-compromise. Our results demonstrate that
optimization models for stimulus representations dominated by nonlocal
suppressive interactions are in principle capable of correctly predicting the
common OPM design. They question that visual cortical feature representations
can be explained by a coverage-continuity-compromise.Comment: 100 pages, including an Appendix, 21 + 7 figure