A model for the economical encoding of the visual image in cerebral cortex

We propose a model for the first stage of the cortical transformation of the visual image based on the principle that the cortex encodes the information with the minimum number of channels mathematically needed. We restrict our model to be consistent with the data on size adaptation, the known relationships of acuity and the inverse of magnification factor with eccentricity, and the electrophysiological findings on the physiological uniformity of the striate cortex. Assuming that each hypercolumn analyzes a limited spatial domain, we apply the sampling theorem to show that only 16 channels, composed of 4 sizes, are needed for one dimension. The extension to 2 dimensions leads to a possible scheme for the number, spacing, and orientational disposition of the elements, together with predictions about the number of inputs from the eyes and the total number of hypercolumns. Since all these predictions are consistent with physical and neural estimates, we conclude that the cortex may analyze the image along the lines we suggest.Supported by NIH grants EY 03412 and EY 02621     

A recurrent system incorporating characteristics of the visual system: a model for the function of backward neural connections in the visual system

A recurrent system is constructed in order to investigate the role of the backward neural connections found in the primate visual system. The system incorporates a layer to perform localized spatial frequency analysis of input images, a function which has been assumed to take place in the primary visual cortex. The function of the system is examined by simulation. The results show that the system can separate an object pattern from its background, irrespective of its precise position. The acceptable displacement range for input images is determined from the width of the window function used to calculate the local Fourier transform. A multilayer version of the above recurrent system is also constructed.     

A miniscule optimized visual system in the Lower Cambrian

Simultaneously with the development of animal body plans, probably before the Precambrian, there was an explosive diversification of visual systems. Competition of performance in these visual systems was a critical factor in the evolution of life systems.
Here we analyse the visual system in the lobopod Miraluolishania haikouensis ( Liu et al ., 2004 ) from the Lower Cambrian Chengjiang Lagerstätte, Kunming, China. It consists of a very small eye with a miniscule lens. A physical problem lies in the fact that due to the usual refractive conditions of such a lens, it hardly represents an improvement of the visual quality over the basal pit- or pinhole camera eyes. To develop such a lavish visual system, however, would not have been of any value, if it achieved no more than an equal level or represented even a retrograde step in evolutionary progress. We show how this system may have allowed pattern recognition even under poor light conditions. Optimization of such a tiny eye is costly but is not 'a wasted effort' in evolution. In M. haikouensis ( Liu et al. , 2004 ), an excellently adapted miniscule visual system has become possible.     

A model for processing of movement in the visual system

Processing of spatio-temporal information in the human visual system has been investigated thoroughly during the past decade, but is still far from being properly understood. Moreover, the theory of separation of information by means of sustained and transient channels already at the retinal level is not satisfactory, as experimental results indicate that these two types of channels span a continuum of temporal characteristics. It is however obvious, that the process of pattern recognition and velocity perception calls for their separation at some level of the hierarchy. In this communication, we extend our model of three-dimensional spatio-temporal frequency expansion in the visual system (Gafni and Zeevi, 1977) to show how velocity-information extraction channels, sensitive to direction and velocity exclusively, can be formed by simple summation of signals from well-defined sets of channels representing points in the frequency space. Correspondence of these channels to characteristics of the cortical neurons is discussed.     

Representation of three-dimensional visual space in the cerebral cortex

This article reviews two issues relevant to the topic of how three-dimensional space is represented in the cerebral cortex. The first is the question of how individual neurons encode information that might contribute to stereoscopic estimation of visual depth. Particular attention is given to the current understanding of the neural representation of motion through three-dimensional space and to the complexities that arise in interpreting neuronal responses to this complex stimulus parameter. The second issue considered is the disorderlines that exists in the retinotopic mapping of the visual field in some cortical visual areas. Several extrastriate areas have been found to contain maps of the contralateral visual hemifield that are disorderly in the sense that the representation of various parts of the visual field are often misplaced or grossly over-or under-represented. It is suggested that this disorderlines may in some cases represent adaptations to facilitate certain types of visual functions.     

Horseradish peroxidase study of the associative connections of the motor region of the cerebral cortex in cats

Somatotopic organization of the body representation in the motor cortex of the cat's brain and a high degree of differentiation in the organization of associative projections between the motor and the somatosensory cortex was shown by means of retrograde transport of horse-radish peroxidase. Pyramid and stellate neurones of the second and the third cortical layers participate in the formation of these projections and interconnections.     

A ratio model of perceived speed in the human visual system

The perceived speed of moving images changes over time. Prolonged viewing of a pattern (adaptation) leads to an exponential decrease in its perceived speed. Similarly, responses of neurones tuned to motion reduce exponentially over time. It is tempting to link these phenomena. However, under certain conditions, perceived speed increases after adaptation and the time course of these perceptual effects varies widely. We propose a model that comprises two temporally tuned mechanisms whose sensitivities reduce exponentially over time. Perceived speed is taken as the ratio of these filters' outputs. The model captures increases and decreases in perceived speed following adaptation and describes our data well with just four free parameters. Whilst the model captures perceptual time courses that vary widely, parameter estimates for the time constants of the underlying filters are in good agreement with estimates of the time course of adaptation of direction selective neurones in the mammalian visual system.