Target Tracking, Navigation, and Decision-Making

This chapter explains why and how tracking of objects moving relative to an observer, and visual optic flow navigation of an observer relative to the world, are controlled by complementary cortical streams through MT--MSTv and MT+-MSTd, respectively. Target tracking uses subtractive processing of visual signals to extract an object’s bounding contours as they move relative to a background. Navigation by optic flow uses additive processing of an entire scene to derive properties such as an observer’s heading, or self-motion direction, as it moves through the scene. The chapter explains how the aperture problem for computing heading in natural scenes is solved in MT+-MSTd using a hierarchy of processing stages that is homologous to the one that solves the aperture problem for computing motion direction in MT--MSTv. Both use feedback which obeys the ART Matching Rule to select final perceptual representations and choices. Compensation for eye movements using corollary discharge, or efference copy, signals enables an accurate heading direction to be computed. Neurophysiological data about heading direction are quantitatively simulated. Log polar processing by the cortical magnification factor simplifies computation of motion direction. This space-variant processing is maximally position invariant due to the cortical choice of network parameters. How smooth pursuit occurs, and is maintained during accurate tracking, is explained. Goal approach and obstacle avoidance are explained by attractor-repeller networks. Gaussian peak shifts control steering to a goal, as well as peak shift and behavioral contrast during operant conditioning, and vector decomposition during the relative motion of object parts.

Receptive Fields of Visual Neurons: The Early Years

This paper traces the history of the visual receptive field (RF) from Hartline to Hubel and Wiesel. Hartline (1938, 1940) found that an isolated optic nerve fiber in the frog could be excited by light falling on a small circular area of the retina. He called this area the RF, using a term first introduced by Sherrington (1906) in the tactile domain. In 1953 Kuffler discovered the antagonistic center—surround organization of cat RFs, and Barlow, Fitzhugh, and Kuffler (1957) extended this work to stimulus size and state of adaptation. Shortly thereafter, Lettvin and colleagues (1959) in an iconic paper asked “what the frog's eye tells the frog's brain”. Meanwhile, Jung and colleagues (1952–1973) searched for the perceptual correlates of neuronal responses, and Jung and Spillmann (1970) proposed the term perceptive field (PF) as a psychophysical correlate of the RF. The Westheimer function (1967) enabled psychophysical measurements of the PF center and surround in human and monkey, which correlated closely with the underlying RF organization. The sixties and seventies were marked by rapid progress in RF research. Hubel and Wiesel (1959–1974), recording from neurons in the visual cortex of the cat and monkey, found elongated RFs selective for the shape, orientation, and position of the stimulus, as well as for movement direction and ocularity. These findings prompted the emergence in visual psychophysics of the concept of feature detectors selective for lines, bars, and edges, and contributed to a model of the RF in terms of difference of Gaussians (DOG) and Fourier channels. The distinction between simple, complex, and hypercomplex neurons followed. Although RF size increases towards the peripheral retina, its cortical representation remains constant due to the reciprocal relationship with the cortical magnification factor (M). This constitutes a uniform yardstick for M-scaled stimuli across the retina. Developmental studies have shown that RF properties are not fixed. RFs possess their full response inventory already at birth, but require the interaction with appropriate stimuli within a critical time window for refinement and consolidation. Taken together these findings paved the way for a better understanding of how objective properties of the external world are encoded to become subjective properties of the subjective, perceptual world.

Inhibition of Return in the Visual Field

Inhibition of return (IOR) as an indicator of attentional control is characterized by an eccentricity effect, that is, the more peripheral visual field shows a stronger IOR magnitude relative to the perifoveal visual field. However, it could be argued that this eccentricity effect may not be an attention effect, but due to cortical magnification. To test this possibility, we examined this eccentricity effect in two conditions: the same-size condition in which identical stimuli were used at different eccentricities, and the size-scaling condition in which stimuli were scaled according to the cortical magnification factor (M-scaling), thus stimuli being larger at the more peripheral locations. The results showed that the magnitude of IOR was significantly stronger in the peripheral relative to the perifoveal visual field, and this eccentricity effect was independent of the manipulation of stimulus size (same-size or size-scaling). These results suggest a robust eccentricity effect of IOR which cannot be eliminated by M-scaling. Underlying neural mechanisms of the eccentricity effect of IOR are discussed with respect to both cortical and subcortical structures mediating attentional control in the perifoveal and peripheral visual field.