Reactor description

6

U-zu-maki Glasses by the artist/scientist Akiyoshi Kitaoka: ‘U’ means rabbits, ‘zu’ means ‘figure’,

‘maki’ means rotation, and ‘Uzumaki’ means spirals or swirls. Yellow represents the colour of the Moon in Japan and it is imagined (though not seriously) that rabbits live in the Moon and make mochi (food made from rice). Such images appear to move each time you make an eye movement.

The explanation is quite complex—but here goes. There are three key things to notice about the effect. First, the patterns only move when you blink or move your eyes; second, the effect is seen best in peripheral vision; and third, the arrangement of the backgrounds of the ‘rabbits’ determines which way the patterns rotate. Now each time your eyes move you get a fresh image. Some parts of the image are of high contrast—they differ a lot from their background—such as the white ears on the red background. Other parts of the image are of low contrast, for example the white ears on the yellow background. Note that in the right-hand image all the high-contrast edges are on the left side of the rabbits’ ears while the low-contrast edges are all on the right side of the rabbits’

ears. The reverse is true in the left-hand image. We know that high-contrast information is trans-mitted up the visual pathway faster than low contrast and hence the motion detectors in the cor-tex receive signals from some bits of the image before others. The sorts of movement detectors we shall describe in this chapter respond to these signals arriving at different times as if they are detecting real motion, and when their responses are pooled together, the illusory motion is seen.

Because information is pooled over large areas in the peripheral retina, the illusion is most striking there. The explanation is a bit more complicated really—but enough for now.

CHAPTER OVERVIEW

Imagine a world in which there is no colour. It may be dull, but it is easy enough to conceive of such a place. Now try to imagine a world in which there is no motion. This seems like an impossible task, but for a small number of individuals with brain damage their world has become devoid of such motion information. Tasks such as crossing the road or filling a glass with wine take on a difficulty (and in some cases terror) that is all too hard to appreci-ate. We believe that these individuals have damage in a small area of the brain that is devoted to analyzing the movements of objects. In this chapter, we describe how we might build detectors that could signal the direction and speed of objects in motion and how, in turn, these can explain why we see movement from a set of stationary pictures such as when we watch television or go to the movies. Finally, we discuss the problem of deciding what is moving—after all, if the something appears to be moving it could be because it is moving, or it could be because we are moving. As we shall see, we do not always solve this rather important problem correctly!

Two ways of seeing movement

Movement seems (and is) vital for our perception of the world. And how we detect movement in the world is one of the greatest achievements of our perceptual systems.

Let’s take the easy case first. Suppose THAT our eyes are held still and a spot of light moves across our field of view (Figure 6.1). A moving image crosses the retina and we perceive movement. No problem. (Actually quite a big problem, but we’ll come back to that.) But what happens if we let our gaze follow the moving spot of light? This action is called ^tracking, which we achieve with smooth pursuit eye movements. Now, because the spot of light is kept on the fovea (our central vision) at all times, there is no movement of the spot across our retina—and yet we still see the spot as moving. Aha, you cry, but if the moving spot is tracked by the eye then there is still movement on the retina—of the actually stationary background moving in the opposite direction to that of the spot (see Figure 6.1). This is true (and very clever of you to spot it), but what if we can repeat the experiment, tracking a moving dot against a totally dark back-ground? The spot still appears to move. So we must have two routes to perceiving movement, one that detects movement across the retina (we shall term this the ^retinal movement system), and one that detects movements of the eyes in the head (we shall term this the eye–head movement system).

Just as we can experience movement without retinal movement (tracking the spot in darkness), we can also experience no movement when there is movement across the ret-ina. Try moving your eyes across a stationary scene. Now as your eyes move, the scene must move across the retina; fortunately, the scene appears to stay still. So the retinal movement system and the eye–head movement system must talk to each other to work out just what’s going on in the world. This question of why the world stays still when we move our eyes was of immense interest to scientists in the 19th century and to two giants in the field in particular, the English physiologist Sir Charles Sherrington and the great Prussian physiologist Hermann von Helmholtz (Grüsser, 1986).

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Basically, if we want to be able to move our eyes around without the world appear-ing to whizz around, we have to keep track of our eye movements. The question is how we do this. Sherrington proposed that we monitor the movements of our eye muscles and, by comparing retinal image motion with eye muscle movement, we can determine whether objects in the real world have moved. Helmholtz proposed a subtly different model of what was going on (which had the distinct advantage of being right). Helmholtz proposed that rather than comparing image motion on the retina with eye muscle movement, the comparison should be made with the signal from the brain that tells the eye muscle to move. So Helmholtz proposed that we take a copy of the signal to move our eyes (sometimes known as an efferent copy or collorary discharge) and compare this with any retinal image motion. Sherrington’s theory is also known as the ‘inflow’ theory and Helmholtz’s as the ‘outflow’ theory, but we keep forgetting which is which so we shall not mention this again.

Let us consider how the two models work (see Figure 6.2) and make some predictions.

x

Figure 6.1 Motion can be sensed in two ways. On the left side, the viewer fixates on a stationary object and the moving object therefore moves across the retina. On the right side, the viewer ‘tracks’

the moving object hence the moving object remains stationary upon the retina and the stationary background moves in the opposite direction across the retina. Both situations give us the perception of a moving object on a stationary background.

1 Track a moving object. This provides no problem to either model. In each case there is no retinal motion signal, but there is a signal from the eye muscles (Sherrington) and a command is sent to the eye muscles (Helmholtz), so in both cases we should perceive the object as moving even though it is stationary on the retina. Score: Helmholtz 1 – Sherrington 1.

2 Stare at a bright light, or look into the camera when a fl ash is used. This will produce an after-image that is ‘burnt’ onto your retina. If you now move your eyes, this after-image will appear to move (even though it is stationary on your retina). No problem here either. There is no retinal movement of the after-image, but the eyes are told to move (Helmholtz) and do move (Sherrington), so the movement of the after-image is perceived. Score: Helmholtz 2 – Sherrington 2.

3 Staring at the stationary world, give your eyeball a sharp poke. The world moves. Try it for yourself. A gentle push through the eyelid should suffi ce for this demonstration. Sharp sticks should be avoided. What you have done here is to move the eye and therefore you have stretched the eye muscle, but no efferent signal was sent by the brain to tell the muscle to move. According to Sherrington the eye muscle movement is the important thing; it doesn’t matter if it is moved by pushing with your fi nger, a pointed stick, or an efferent signal. But it does matter to Helmholtz—only an efferent signal from the brain will do. So in this example the world should stay still for Sherrington and move for Helmholtz. And the Earth does move (perceptually at least). Score:

Helmholtz 3 – Sherrington 2.

4 If the Earth moved for you that time, try it with an after-image, preferably in the dark. Stare at a bright light for a while, or a camera fl ash, to get an after-image. It moves around when you move your eyes as expected (see 2 above).

Now keep your eyes still and push the eyeball through the eyelid, with your eyelids closed (to make things dark). Does the after-image move? According to Sherrington it should: there’s no retinal movement, but there is eye muscle movement. However, according to Helmholtz it shouldn’t: no retinal movement

Eye muscle signal theory

Figure 6.2 In Sherrington’s inflow theory, the signals about eye movements come from the eye, whereas in Helmholtz’s outflow theory they come from the brain.

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and no eye movement signal either. The after-image doesn’t move. Score:

Helmholtz 4 – Sherrington 2.

5 Now for one you shouldn’t try at home. What if we tell our eyes to move but we actually prevent the eyeball from moving? Helmholtz predicts that the stationary world will appear to move because the eye movement signal is not cancelled by the expected retinal movement. Sherrington predicts no movement because there will be no retinal movement and no eye muscle movement. Good predictions, but how do we do the experiment? Well, there are two ways. First, we can physically prevent the eyes from moving in their orbits by stuffi ng putty behind the eyes. Very nasty. Second, we can paralyze the eye muscles with a drug like curare. This sounds neater, but unfortunately curare paralyzes much of the nervous system and, although your heart will keep beating, you can’t breathe and you will suffocate. Nonetheless, the experiment has been done both ways and the world does move (Stevens et al., 1976), giving Helmholtz a well-deserved 5–2 victory which is a fairly typical result when Germany play England.

Of course, such a theory requires us to have a good signal about our eye movements so that we can compensate for them. In some unfortunate individuals the signal about eye movement fails and the world appears to move with each eye movement (Haarmeier et al., 1997).

A motion detector

That was a lot of work just to figure out that the world seems to stay still when it doesn’t move. But we have some important elements in our model (see Figure 6.2) that we should try to unpack. Consider the line labelled ‘retinal motion’. How do we know if movement across the retina is up or down or left or right? How can we construct a

‘movement detector’? And if we do construct one, will it behave like movement detec-tors in our visual system? Things could get complicated here, so let’s start with a sim-ple examsim-ple.

If we want to tell the difference between a spot of light moving to the left and one moving to the right, what should we do? Imagine that a spot of light moves from A to B (see Figure 6.3, top left). What might be useful is to have something that can detect the spot when it is at A, and one that detects the spot at B (two receptive fields would do the trick). We can then say that we require that both the receptor with a receptive field at A and the one with a receptive field at B must fire within a certain time period—

so if our spot moves from A to B within this time period we get firing and we have detected motion—hurrah! Unfortunately this detector would respond just as well to a spot of light moving to the left (B to A) as to the right (A to B). Clearly, we must make our detector asymmetrical, and the easiest way to do this is by introducing a time delay (Figure 6.3, top right). The logic here is that if the spot moves from A to B it will excite receptor A before receptor B. If we put a time delay on the output signal from A,

A B

Figure 6.3 How to build a motion detector.

The key components in many motion models are two spatially separated detectors with a time delay between their responses. See text for further details.

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then it will arrive at the comparison box, the detector, at the same time as the not-delayed signal from B, provided that the delay is as long as the time taken to travel from A to B. Movement from B to A will excite detector B first; some time later, when the spot has moved to A, detector A will fire. Its response will then be delayed and there is no chance of the activities from A and B reaching the detector at the same time.

With such a scheme, we can ensure that movement from A to B will excite the detector but movement from B to A will not. Of course, this will only work if the speed of the spot is neither too fast nor too slow.

This simple model is often termed a delay-and-compare detector. This is not, by any means, the only way that we can make a directionally selective device, but the general principle of sampling from two different points in space with a time delay is at the heart of many more sophisticated models of motion (Borst and Egelhaaf, 1989).

Examples of such schemes do not only exist in biological systems. Figure 6.4 shows an increasingly familiar object in many countries—the speed trap. Some of these things work by bouncing radar waves off moving vehicles, but although this may work, the trouble is that there is no documentary evidence of the alleged offence. It would be suf-ficient for the speeding driver to demonstrate that these things can be unreliable in order to be acquitted.

So the device in Figure 6.4 has an additional feature, which works rather like our motion detector above. The box contains a camera which is activated by an initial

‘Hey there’s a speeding car’ signal from the radar system. The camera takes two pic-tures a known time apart. Lines, a bit like a ruler, are painted on the road. The speed of the car is then simply worked out by the distance travelled in this known time period. If the car has moved more than some distance in the time between the pictures, then it is going too fast, and the photos exist to prove it. Of course, if you drive very fast, by the time the second picture is taken your car will have gone out of shot.

However, we think that you’d have to be going at about 200 mph (320 km/h) to achieve this, so don’t try it.

Let’s elaborate our model with one further step. The top right of Figure 6.3 shows our simple left-to-right detector. Clearly, it would be just as simple to make a right-to-left detector (Figure 6.3, lower right-to-left), and equally it is simple to combine both detectors so that only two sensors are used overall (Figure 6.3, lower right). Many models also then include a later stage that compares the output of left and right detectors in an antagonistic manner (such as subtracting one from the other). This means that any-thing that excites them both equally does not produce any signal after this subtraction.

Is there any evidence that such movement detectors exist in biological systems? The very fact that we can tell rightward movement from leftward movement suggests that somewhere in our heads we can do this, but it doesn’t tell us where in the system such devices might be found. In primates, it has been found that neither ganglion cells nor LGN cells can tell left from right, and that the first signs of direction selectivity arise in the primary visual cortex (area V1). In area V5 (also known as MT) it appears that nearly every cell has this property of directional selectivity (see Figure 6.5) (Albright, 1984). However, in frogs, rabbits, and many other species, direction-selective cells can

➾See Chapter 3

➾See p.187

Figure 6.4 Speed traps. The upper part shows the speed camera. The lower parts show how it calculates speed by taking two pictures at slightly different times. The distance travelled can be calculated from the number of lines on the road the car has traversed between the taking of the pictures. Speed is calculated by the distance travelled divided by the time difference between taking the pictures.

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