Neuronal mechanisms for detection of motion in the field of view

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Abstract

The visual system cannot rely only upon information from the retina to perceive object motion because identical retinal stimulations can be evoked by the movement of objects in the field of view as well as by the movements of retinal images self-evoked by eye movements. We clearly distinguish the two situations, perceiving object motion in the first case and stationarity in the second. The present work deals with the neuronal mechanisms that are likely involved in the detection of real motion.

In monkeys, cells that are able to distinguish real from self-induced motion (real-motion cells) are distributed in several cortical areas of the dorsal visual stream. We suggest that the activity of these cells is responsible for motion perception, and hypothesize that these cells are the elements of a cortical network representing an internal map of a stable visual world. Supporting this view are the facts that: (i) the same cortical regions in humans are activated in brain imaging studies during perception of object motion; and (ii) lesions of these same regions produce selective impairments in motion detection, so that patients interpret any retinal image motion as object motion, even when they result from her/his eye movements.

Among the areas of the dorsal visual stream rich in real-motion cells, V3A and V6, likely involved in the fast form and motion analyses needed for visual guidance of action, could use real-motion signals to orient the animal’s attention towards moving objects, and/or to help grasping them. Areas MT/V5, MST and 7a, known to be involved in the control of pursuit eye movements and in the analysis of visual signals evoked by slow ocular movements, could use real-motion signals to give a proper evaluation of motion during pursuits.

Introduction

Visual perception of motion is clearly related to the movement of retinal images of objects present in our field of view. However, similar movements of retinal images can be evoked by eye movements, while the objects are still in the visual scene. How do we distinguish actual movements from the image movements self-induced by the movement of the eyes? The purpose of the present work is to try to answer this question taking into account the neuronal mechanisms that are likely involved in the detection of motion.

Experimental data obtained in paralyzed animals showed that many neurones of the visual system are sensitive to the movement of visual stimuli, and several cells of the visual cortex are able to encode the speed of motion over large ranges of velocities (Orban, 1984; Riva Sanseverino, Galletti, Maioli, & Squatrito, 1979). One could believe that all these neurones, being sensitive to various speeds of motion, are able to encode the movement occurring in the visual field, but this is clearly not the case. In physiological conditions, contrary to what happens in paralyzed animals, the animal moves the eyes, so the images of motionless objects move on the retina, exactly as the images of moving objects do. How can motion-sensitive neurones recognize the real movement of objects in the visual field?

In physiological conditions, the images of objects motionless in the visual field move on the retina even when the animal maintains a steady fixation, owing to eye micromovements (drifts and flicks). As the velocity of these micromovements is such as to activate many cells in paralyzed animals (drifts: <1° s−1, flicks: ∼10° s−1; see Carpenter, 1988), these cells will be activated by motionless objects as well as by objects moving slowly in the visual field during steady fixation; but, again, they will not able to discriminate between these two situations.

Fig. 1 shows the visual responses to stimuli moving at different speeds, and the velocity tuning curves, of cells recorded in the primary visual cortex of awake macaque monkey during steady fixation. The cell shown in Fig. 1 gave transient on–off responses to stationary stimuli and good responses to slow velocities of stimulus movement (from 1 to 20° s−1); at speeds higher than 50° s−1, the activity of the cell was not significantly modified by the visual stimulation. Fig. 1E shows the velocity tuning curve of this cell and that of another cell that was sensitive to high speeds of motion. Both cells were activated by moving objects, though they preferred different speeds of motion. According to their tuning curves, we could predict that they would be also activated by stationary objects when the eyes move, as the image of these objects sweeps across the cell’s receptive fields each time the eyes move. Cells preferring high velocities would be activated by saccadic eye movements (velocities>100° s−1), and cells sensitive to slow speeds of motion by pursuit eye movement (1–50° s−1), as well as by flicks and drifts during steady fixation. If this were the case, we would perceive a shift of the visual world each time we make a saccade, and we would perceive as in motion the motionless objects the image of which is moving on the retina owing to pursuit eye movements. As this is not the case, it means that the movement of the retinal image per se is not sufficient to evoke a sensation of movement of the object in the visual field. This sensation is evoked when the movement on the retina is due to a real motion of the object, and is not evoked when the retinal image movement is self-induced by the movement of the eyes.

Section snippets

Perception of real motion

In order to give a proper evaluation of motion, the visual system takes into account the movement of the eyes besides that of retinal images. For instance, long-lasting afterimages, as well as phosphenes evoked by cortical stimulation, appear as motionless when they are viewed in complete darkness and the eyes are moved passively, but these afterimages appear to be moving when the eyes move actively, either for saccadic or slow pursuit movements (Brindley & Lewin, 1968; Grusser &

Correct evaluation of motion during tracking eye movement

During steady fixation, as an object moves in the visual field its image moves on the retina and we soon perceive the object as in motion. During visual tracking of a moving object, conversely, the image of the followed object is quite still on the retina while the images of motionless visual world around the moving object are in motion. Despite this, everyone clearly perceives the object as in motion and the visual world as motionless.

The stability of perception of the visual world during

Cortical stream for real motion detection

An increasing percentage of cells in areas V1, V2 and V3A responds better to externally-induced retinal image slip than to image slip self-induced by the eye movement (10, 15 and 41%, respectively; Battaglini et al., 1986, Galletti et al., 1984, Galletti et al., 1988, Galletti et al., 1990). Many cells in area MT/V5 (Erickson & Thier, 1991; Thiele et al., 2002), and the great majority in areas MST and 7a (Erickson & Thier, 1991; Sakata et al., 1985, Thiele et al., 2002), show the real-motion

An internal map of visual world for motion detection

The real-motion cells are able to distinguish whether a movement of a retinal image is due to a real movement in the visual field or is self-induced by a movement of the eyes. These cells allow one to recognize the actual movement of an object across a structured or non-patterned visual background, as well as in complete darkness. They could act as ‘sensors’ of real movement in a neural network that subserve an internal, objective map of the visual field. Such an internal representation of the

Conclusions

Cells able to distinguish real from self-induced motion (real-motion cells) are distributed in several cortical areas in the brain. This cortical network, that seems to exist also in the human brain, could be responsible for the proper evaluation of motion and the stability of visual perception despite eye movements.

Real-motion cells are distributed in areas of the dorsal visual stream that are strongly influenced by the magnocellular input. Among these areas, V3A and V6 are likely involved in

Acknowledgements

This work was supported by Grants from Ministero dell’Istruzione, dell’Universita’ e della Ricerca, Italy.

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