Reorganization of columnar architecture in the growing visual cortex

Abstract

Many cortical areas increase in size considerably during postnatal development, progressively displacing neuronal cell bodies from each other. At present, little is known about how cortical growth affects the development of neuronal circuits. Here, in acute and chronic experiments, we study the layout of ocular dominance (OD) columns in cat primary visual cortex during a period of substantial postnatal growth. We find that despite a considerable size increase of primary visual cortext, the spacing between columns is largely preserved. In contrast, their spatial arrangement changes systematically over this period. Whereas in young animals columns are more band-like, layouts become more isotropic in mature animals. We propose a novel mechanism of growth-induced reorganization that is based on the "zigzag instability," a dynamical instability observed in several inanimate pattern forming systems. We argue that this mechanism is inherent to a wide class of models for the activity-dependent formation of OD columns. Analyzing one representative of this class, the Elastic Network model, we show that this mechanism can account for the preservation of column spacing and the specific mode of reorganization of OD columns that we observe. We conclude that column width is preserved by systematic reorganization of neuronal selectivities during cortical expansion and that this reorganization is well described by the zigzag instability. Our work suggests that cortical circuits may remain plastic for an extended period in development to facilitate the modification of neuronal circuits to adjust for cortical growth.cortical growth | ocular dominance columns | postnatal development | critical period | zigzag instability

Mechanisms for Stable, Robust, and Adaptive Development of Orientation Maps in the Primary Visual Cortex

“…This linear relation gives a consistent number of pinwheels per hypercolumn area (⌳ 2 ), implying a constant pinwheel density when averaged over sufficiently large cortical areas. This dimensionless, statistical measure of pinwheel distribution is thought to reflect a universal constant of map organization, converging to across carnivorans, primates, cats, and tree shrews (Kaschube et al, 2010;Keil et al, 2012). This value was predicted by a theoretical model of map organization and has strong empirical evidence, with a mean pinwheel density across four species (tree shrew, galago, cat, and ferret) statistically indistinguishable from (Kaschube et al, 2010); see data from three species in Figure 3D.…”

“…Accordingly, we developed a new map-quality metric based on the empirical observation that pinwheel count in biological orientation maps scales linearly with hypercolumn size across many different species (Kaschube et al, 2010). This linear relation gives a consistent number of pinwheels per hypercolumn area (⌳ 2 ), implying a constant pinwheel density when averaged over sufficiently large cortical areas.…”

“…For simulated maps using uniform random input statistics, a single number is sufficient to characterize the Fourier plots: the radius of the isotropic ring, computed using the methods described in the study by Kaschube et al (2010). To eliminate disruptions in hypercolumn size due to border effects at the sheet edges, only the central 1.0 ϫ 1.0 area from a simulated V1 sheet of area 1.5 ϫ 1.5 is analyzed for all model maps presented.…”

“…Orientation-selective neurons in carnivoran and primate primary visual cortex (V1) form systematic topographic maps organized by preferred retinal location and orientation (Blasdel, 1992a,b;Kaschube et al, 2010). Optical imaging studies in ferrets indicate that these orientation maps develop in a stable way, with a high similarity in the spatial layout between the weakly selective initial maps and the final highly selective configuration (Chapman et al, 1996;Gödecke et al, 1997).…”

Evolutionary constraints on visual cortex architecture from the dynamics of hallucinations

“…Here we show that V1 is specially configured to avoid the formation of visual hallucinations and remain stable under typical operating conditions in the visual state. Together with recent reports of developmental plasticity in V1 (8), and the apparent universality of the self-organizing principles behind the structure of its orientation columns (9), our results imply strong constraints on the key features and evolution of its global architecture at intermediate length scales.…”