A model for the development of simple cell receptive fields and the ordered arrangement of orientation columns through activity-dependent competition between ON- and OFF-center inputs

Abstract

Neurons in the primary visual cortex of higher mammals respond selectively to light/dark borders of a particular orientation. The receptive fields of simple cells, a type of orientation-selective cell, consist of adjacent, oriented regions alternately receiving ON-center and OFF-center excitatory input. I show that this segregation of inputs within receptive fields can occur through an activity-dependent competition between ON-center and OFF-center inputs, just as segregation of inputs between different postsynaptic cells into ocular dominance columns appears to occur through activity-dependent competition between left-eye and right-eye inputs. These different outcomes are proposed to result, not from different mechanisms, but from different spatial structures of the correlations in neural activity among the competing inputs in each case. Simple cells result if ON-center inputs are best correlated with other ON-center inputs, and OFF with OFF, at small retinotopic separations, but ON-center inputs are best correlated with OFF-center inputs at larger separations. This hypothesis leads robustly to development of simple cell receptive fields selective for orientation and spatial frequency, and to the continuous and periodic arrangement of preferred orientation across the cortex. Input correlations determine the mean preferred spatial frequency and degree of orientation selectivity. Estimates of these correlations based on measurements in adult cat retina (Mastronarde, 1983a,b) produce quantitative predictions for the mean preferred spatial frequencies of cat simple cells across eccentricities that agree with experiments (Movshon et al., 1978b). lntracortical interactions are the primary determinant of cortical organization. Simple cell spatial phases can play a key role in this organization, so arrangements of spatial phases

A neural network model for the development of simple and complex cell receptive fields within cortical maps of orientation and ocular dominance

“…The Self-Organizing Cortical Map (SOCM) model developed in this study extends earlier work on map formation (von dcr Malsburg, 1973;Grossberg, 1976a, b;Will shaw and von dcr Malsburg, 1976;Bienenstock eta!., 1982;Kohonen, 1989;Miller eta!., 1989;Schwartz, 1989, 1990;Miller, 1992Miller, , 1994Grossberg and Olson, 1994;Sirosh and Miikkulaincn, 1994) and orientation tuning development (Linsker, 1986a, b, c;Miller, 1994) to show how neighboring simple cells that arc sensitive to opposite contrast polarities can self-organize as part of the developmental process that generates cortical maps of orientation and ocular dominance. In addition to the source of noise, band pass filter, and response normalization that arc present in other models, the current model makes use of cell dynamics to control map development.…”

“…To simulate map formation at the same cortical resolution presented by Miller (1994) requires 32 x 32 dipoles in the system, each with 6 clements (2 x's, 2 y's, and 2 z's), for a total of 6144 elements. Numerically integrating a system of 6144 variables using an adaptive stepsize algorithm such as the Runge-Kutta method would be possible, but somewhat inconvenient, except for the fact that the system is stiff (Press ct a!., 1992).…”

Linsker-type Hebbian Learning: A Qualitative Analysis on the Parameter Space

“…Biologically, the spontaneous firing of ganglion cells, the correlated patterns of activity in the afferents, the lateral intralayer interaction, the feedforward synaptic arbor density function, and parallel ON-, OFF-arrays are all thought t o contribute to the symmetry-breaking mechanism by which oriented aRFs and orientation dominance maps can arise. A considerable number of analyses and simulations [3,4,8,9,19,28,29,30,31,32,33,38, 411 on the self-organization in visual system have recently expanded Linsker's ideas by introducing more biological1:r-motivated factors, and in particular, by including lateral intralayer interactions. Our approach can be adapted t o explicitly analyze the role played by the lateral intralayer interaction, in the same way that we deal with the interlayer connection density (i.e., SDFs) [34].…”

The emergence of linguistic form in time

“…Each cortical area has many substructures that differ in their connectivity and cytoarchitectonics (Buck et al 1998). Emergentist accounts hold that much of this differentiation is dependent on general principles of induction (Miller 1994), plasticity (Quartz andSejnowksi 1997, Booth et al 2001) and gene expression (Murray 1988) during epigenesis. Moreover, the brain retains plasticity throughout development.…”