The Vertebrate Retina, Photoreceptors, and Color Vision
Transcript of Part 1: Photoreceptors and Image Processing I
00:00:05.22 I'm Jeremy Nathans, I'm a professor at the John Hopkins Medical School, 00:00:09.22 an investigator of the Howard Hughes Medical Institute. 00:00:12.22 This is the first of three lectures on the vertebrate retina, 00:00:15.20 its structure, function, and evolution. 00:00:19.01 In this first part, we're going to look at photoreceptors and image processing. 00:00:22.27 Let's start with a look at the visual system in its entirety. 00:00:26.14 It consists, of course, of the eye and a significant fraction of the brain, 00:00:32.15 as indicated by these arrows. 00:00:34.11 That's really too much for three lectures, and so we're going to concentrate 00:00:37.29 just on the eye and the inner workings of the retina within it. 00:00:41.16 Let's have a closer look at the vertebrate eye. 00:00:44.10 Light enters the vertebrate eye by refraction at the cornea-air interface, 00:00:50.11 and again by the lens, and then the image is formed on the back wall of the eye 00:00:54.11 lined by a thin layer of neural tissue, called the retina. 00:00:57.24 Now, a comparison between the eye and a camera is irresistible. 00:01:03.01 You can see that many of the components are the same. 00:01:05.22 They both have an aperture, they have a lens, the image is formed on the back wall 00:01:11.10 of both the camera at the film, and on the back wall of the eye, at the retina, 00:01:17.16 It's inverted, of course, by the action of refraction at the cornea and the lens, 00:01:24.01 but there's a critical difference and that is that the retina 00:01:27.21 doesn't just capture the image, the way the film does. 00:01:29.29 It processes it and it extracts from it those aspects of the visual world 00:01:35.22 that are most important to the organism. 00:01:37.13 Now, this remarkable piece of engineering has captured 00:01:43.18 the imagination of scientists for centuries. 00:01:45.29 The performance of the retina is really quite remarkable. 00:01:49.01 For example, the retina performs...the whole visual system performs 00:01:53.01 extremely well on a moonless night and also extremely well on a sunny afternoon 00:01:59.04 when the ambient light levels differ by a million fold. 00:02:02.08 The retina is also capable of discriminating objects that differ 00:02:06.12 in their angular position by only one percent of one degree... 00:02:10.29 an amazing performance. 00:02:13.08 In fact, that performance gave Charles Darwin a bit of a nightmare. 00:02:18.21 He had written in his Origin of Species a critical chapter 00:02:24.23 which he called "Problems with the Theory" 00:02:27.01 in which he examined what he called organs of extreme perfection. 00:02:31.23 And by this he meant organs which had achieved such remarkable abilities 00:02:37.06 that they seemed to fly in the face of his simple idea of evolution by stepwise change. 00:02:43.13 The star witness for this collection of organs of extreme perfection was the eye. 00:02:49.26 At the end, Darwin concluded that perhaps the eye could have evolved stepwise, 00:02:54.15 but I think it gave him a bit of a headache. 00:02:56.28 Now, we're going to talk mostly about the vertebrate eye, 00:03:00.14 but I want, just for completeness to note 00:03:02.06 this is not the only structure that evolution has come up with 00:03:05.27 to capture light and to analyze it. 00:03:09.06 Insects have an anatomically quite different arrangement. 00:03:12.26 Here's a Drosophila. It has a characteristic pair of eyes on either size of the head, 00:03:20.26 but they're really a collection of hundreds of little eyes called ommatidia. 00:03:26.07 And that anatomic difference, for many years, was thought to reflect 00:03:32.11 a really rather different evolutionary pathway to the production of an eye. 00:03:39.22 But, interestingly, in recent years, it's become apparent 00:03:43.11 that a number of the molecular players are similar... 00:03:46.21 virtually identical between insects and vertebrates, 00:03:50.27 although the overall anatomy is quite different. 00:03:53.12 So, for example, the light-sensing proteins 00:03:55.15 which we'll talk about in detail in a few minutes 00:03:58.05 are nearly identical between insects and vertebrates. 00:04:01.26 And, perhaps more surprising, the genes that control 00:04:06.15 the development of the vertebrate eye... one in particular called Pax6, 00:04:10.12 a master regulator gene of vertebrate eye development, 00:04:13.11 and eyeless (and its close cousin, twin of eyeless) in insects 00:04:18.24 function in largely the same ways, and these genes have dramatic effects 00:04:23.17 on the controlled development of the eye. 00:04:27.03 Let me just show you one example of how dramatic that effect is. 00:04:31.04 This is an experiment in which either eyeless or the twin of eyeless gene 00:04:36.20 has been overexpressed in incorrect locations within a fruit fly. 00:04:41.21 On the left, here, we have its overexpression on the legs, 00:04:46.09 and here this red patch on both legs 00:04:50.13 left and right, is an eye which has developed on the leg, 00:04:53.29 simply because that gene was overexpressed. 00:04:56.09 On the right, we see a fly, where, on the antenna, where there shouldn't be an eye, 00:05:00.13 now an eye has appeared. 00:05:02.16 Now, we're not going to say anything more about invertebrate vision. 00:05:07.09 At this point, we'll return to the vertebrate retina 00:05:09.29 which is really the object of our lectures today 00:05:12.20 Let's just look at its overall structure. 00:05:16.11 It's a layered structure, it's rather thin -- 00:05:19.07 substantially less than a millimeter in thickness, 00:05:21.28 and in the outermost layer are the photoreceptor cells, the rods and cones. 00:05:27.07 These are up here. 00:05:28.22 The rods are thin cells... these vertical cells... the more numerous cells, 00:05:34.01 and the cones are the thicker ones. 00:05:35.21 And then there's a second layer of intervening neurons: 00:05:39.25 the bipolar, horizontal, and amacrine cells, 00:05:41.16 and finally, at the bottom, there's an output layer of cells, 00:05:46.13 which send their axons to the brain. These are the retinal ganglion cells, 00:05:49.28 the final arbiters of information that will flow to the brain. 00:05:54.22 Let's have a slightly closer look at the photoreceptor cells. 00:05:58.27 Here's a scanning electron micrograph showing 00:06:01.19 the rods and cones in a salamander retina, 00:06:03.21 and you can see that they're quite unusual looking cells. 00:06:07.13 The cones are the little ones with these cone-shaped tips, 00:06:11.03 and the rods are the big ones with these barrel, so-called rod-shaped outer parts. 00:06:17.05 Each cell has one of these specialized appendages, and they're called outer segments, 00:06:23.11 which really are modified cilia and hold all of the light-sensitive machinery 00:06:29.26 and the enzymes that transduce the light information following capture. 00:06:35.07 Let's look again, at even higher power at the internal structure 00:06:39.19 of one of these outer segments. 00:06:41.27 Here is a transmission electron micrograph. 00:06:45.07 What we see is that the outer segment is filled... just chock full of membranes 00:06:50.25 and they're layered like stacks of pancakes. 00:06:53.18 There's about a thousand of these flattened membrane sacks 00:06:58.25 within a single outer segment. 00:07:01.19 Why is it built this way? Why are all of these membranes present, 00:07:05.14 and why are they stacked in this configuration? 00:07:09.23 The answer is that the light-sensing protein, generically called visual pigment, 00:07:15.24 (rhodopsin, in the case of rods - the specific name) 00:07:18.23 is an integral membrane protein, and it sits in this membrane. 00:07:24.06 In fact, the membrane is virtually a liquid crystal of the visual pigment. 00:07:29.02 Here is the 3D structure of the pigment... this is bovine rhodopsin. 00:07:33.29 You can see it has seven transmembrane domains. 00:07:36.17 Those are these cylindrical objects, passing through the membrane, 00:07:42.27 which is in the horizontal plane here. 00:07:44.29 It is a G-protein-coupled receptor. All visual pigments are G-protein-coupled receptors, 00:07:49.14 and they act by catalyzing the activation of a G-protein which then 00:07:55.26 transmits the signal further within the cell. We'll discuss that in a minute. 00:08:00.01 So, one can ask, though, what part of the protein actually absorbs light? 00:08:05.18 Now, protein side chains in general do not absorb visible light. 00:08:09.19 They absorb in some cases in the ultraviolet. 00:08:11.21 The thing that absorbs visual light, which is shown here in red 00:08:15.28 is the chromophore, 11-cis-retinal. It's a different compound 00:08:19.20 that's joined covalently to the receptor protein. 00:08:23.10 And this is what it looks like in schematic form. 00:08:25.27 It's a vitamin A derivative. We don't make it ourselves. We have to eat it. 00:08:30.10 It comes from a variety of plant sources... carrots are a good source. 00:08:34.25 It's bound covalently to the terminal amino group of a lysine that is part of the apo protein. 00:08:43.01 Now, light does only one thing in all of vision. 00:08:48.03 It isomerizes retinal from cis to trans. 00:08:51.27 That is, in the dark state, in the unexcited state, there's one double bond 00:08:56.07 in the cis configuration... this 11-12 double bond. 00:08:59.24 And photoisomerization, as shown by this transition from the upper to the lower 00:09:05.29 structure converts that cis bond to a trans bond. 00:09:10.08 That's it. Light does nothing else in all of vision. 00:09:13.00 And that happens in about 10 picoseconds from the time of photo-capture. 00:09:18.13 Everything else that happens, in terms of receiving and amplifying the signal, 00:09:23.15 happens as a consequence of this isomerization. 00:09:26.26 And what does this do to the protein? 00:09:29.12 Well, if you think like a pharmacologist, you can conceptualize the dark form... 00:09:36.08 the 11-cis form of retinal as an antagonist that sits in the binding pocket 00:09:42.14 and it keeps the protein in the off configuration... keeps it silent. 00:09:46.18 And this isomerization, which converts the 11-cis to all-trans form of the chromophore 00:09:53.24 then activates a series of conformational changes in the attached apo protein 00:09:58.25 and turns it into the on state. 00:10:01.22 Now there's one new player in the photo-sensing world that has just emerged in the last decade, 00:10:09.24 and that is yet an additional light-sensing pigment that is in the vertebrate eye 00:10:17.13 but not in the rods or cones. This came as quite a surprise. 00:10:20.22 This is a pigment which we call melanopsin. 00:10:25.16 It resides in intrinsically photosensitive retinal ganglion cells... 00:10:29.14 that third and output layer of the retina where one might not 00:10:33.28 have expected direct photosensitivity. 00:10:36.14 But, it turns out that a tiny subset of those cells have a response 00:10:40.22 that's shown as exemplified here by this very slow time course of response, 00:10:46.22 and down below we see the pulse of light (the square wave is the pulse of light)... 00:10:50.22 And this very slow response is typical for these intrinsically photoreceptive ganglion cells. 00:10:56.21 Now that's way too slow a response to be useful for image-forming vision 00:11:01.20 of the sort that allows us to play tennis or walk around. 00:11:04.29 It is, however, just the sort that is useful for rather slower responses. 00:11:11.02 For example, constriction of the pupil. When the ambient light increases or decreases, 00:11:16.15 your pupil constricts or dilates accordingly. 00:11:18.24 Or, for example, in training neural rhythms to the light and dark variation 00:11:26.08 that occurs over 24 hours... the so-called circadian rhythm. 00:11:29.29 And, in fact, these intrinsically photoreceptive ganglion cells mediate exactly those two functions. 00:11:36.09 Now let's ask a question which has been asked by many vision scientists for a very long time. 00:11:44.03 And that is, what is the absolute threshold of human vision? 00:11:47.25 That is, what is the dimmest light that we can see? 00:11:51.11 This is a question which has been of interest, not only to vision scientists, 00:11:55.07 but, for example, to astronomers for a long time. 00:11:58.03 In the days before electronic detectors and film, an astronomer like Keppler or Galileo or Newton 00:12:05.18 would look through the telescope with his naked eye, 00:12:08.21 and so the question actually arose, How good is the eye? 00:12:13.11 Are there, for example, stars out there that are so dim that we can't see them 00:12:17.23 because the eye isn't sufficiently sensitive? 00:12:19.21 Of course, we know the answer is yes, there are stars that are far dimmer 00:12:23.13 than can be seen with the naked eye. 00:12:25.19 And so, in addressing this question, you might think that it's not that difficult experimentally 00:12:33.24 to obtain an answer. We could simply start with a calibrated light source. 00:12:38.18 We know how many photons it's delivering per unit time. 00:12:41.24 It delivers some stimulus to the eye, and we'll just simply calculate the number of photons. 00:12:48.04 To first approximation, that is the way the experiment is done, 00:12:51.24 and if you do it with all due preparations... 00:12:58.02 That is, you have the subject fully dark-adapted 00:13:00.02 (the person sits in a completely pitch black room for half an hour or so) 00:13:04.14 Then if you deliver a very brief and very tiny flash of light, that's the best stimulus. 00:13:12.02 And you deliver it to the most rod-rich region of the retina, 00:13:15.17 because the rods are more sensitive to dim light than are cones... 00:13:19.02 You can get a calibrated answer, and the answer turns out to be 00:13:24.25 a rather small number of photons. 00:13:26.28 It's about 100 that must be delivered to the cornea 00:13:29.22 for the person to say, "Yes, I saw that flash of light." 00:13:33.07 Now that's an impressively small number... it's an impressive answer. 00:13:39.21 But it doesn't get fully at the question because what we'd really like to know 00:13:43.29 is how many photons must be captured by the photoreceptor cells 00:13:50.25 to initiate the visual act. Not how many hit the eye from the outside world 00:13:56.07 because many of those might not be used at all. 00:13:58.17 They may be thrown away. They may, for instance, pass through the retina unabsorbed. 00:14:01.20 And, in fact, that is the case. The eye is not 100% efficient 00:14:06.10 in its ability to capture and utilize light information. 00:14:10.05 And so, in the quest to figure out exactly how many photons need to be absorbed 00:14:18.07 to initiate a visual act, Selig Hecht, one of the great visual scientists, 00:14:22.26 thought of an extremely clever approach to this question 00:14:28.05 which would use the statistical variation in the number of photons delivered to the eye 00:14:35.13 in one of those flashes from trial to trial 00:14:38.14 as a way of determining that number of photons that are required to see. 00:14:44.18 Let's just follow this experiment. 00:14:47.05 So, imagine I'm going to give you two numerical examples which will illustrate the method. 00:14:51.22 Imagine that we're delivering, in the upper example here, 00:14:57.26 a certain number of photons per flash, and we'll say that the average number is 3. 00:15:04.28 So, every time a shutter opens, on average, 3 photons strike the eye 00:15:11.02 as a result of that 1 millisecond flash. 00:15:14.23 And let's also imagine, for the sake of this argument, that 5 or more photons 00:15:18.22 are required to allow the person to actually see the flash of light. 00:15:24.14 That is to say, 5/3 as many as are delivered on average per flash. 00:15:29.05 Now, if one is delivering on average 3 photons per flash... 00:15:32.26 And recall that, photons emerge from a filament of a light bulb independently and at random, 00:15:38.22 so, this number will vary in a Poisson manner (that is, a random manner). 00:15:43.25 And so, the variation in number of photons delivered on different stimulus occasions 00:15:50.20 will have this bell-shaped curve, as shown here, 00:15:54.27 which in some instances deliver the average, 3, 00:15:58.29 some deliver more (say 4 or 5), some deliver fewer (2 or 1). 00:16:02.22 And because of this variation, it will only be the occasional, let's say, 00:16:07.22 1 in 20 flashes which happens to deliver 5 or more photons per flash. 00:16:13.18 So, the individual will say perhaps 1 out of 20 times, "Yes, I saw something." 00:16:17.28 Now, let's look at this lower example. 00:16:21.20 Suppose the experimental setup is essentially the same, 00:16:24.26 but the only difference is that one requires 50 or more photons to see the flash. 00:16:30.08 And that on average, 30 are delivered. 00:16:32.24 How will that change the outcome of the experiment? 00:16:36.00 It will change it in the following manner... 00:16:38.03 Because photons emerge from the filament at random, 00:16:41.28 and because that random process has this sort of bell-shaped curve, 00:16:48.11 if the number is larger, that curve will necessarily be narrower... 00:16:54.07 That is, the relative fluctuation about the mean for larger numbers of events 00:17:01.24 will be less than it will for smaller numbers. 00:17:05.03 So, even though the number of photons required 00:17:08.04 for the person to say, "Yes, I saw something" 00:17:10.21 is still 5/3 the average number that were delivered, 00:17:15.24 the fraction of the time that large number is delivered to the eye... 00:17:22.12 that is, 50 or more photons delivered to the eye 00:17:24.23 will be far less. It might be 1% or less than 1% of the time 00:17:30.21 And it's that difference which then Hecht set out to measure. 00:17:35.06 Now let's look at two related curves. 00:17:38.20 These show the fraction of trials in which the subject reported seeing a flash of light. 00:17:45.05 as a function of the average number of photons captured per trial. 00:17:49.16 And I think we can see in this pair of curves (and these really are 00:17:54.00 the experimental curves that would come from doing the experiment that Hecht did) 00:17:58.24 that if a small number is required, say 5 or more, 00:18:04.12 that curve is a rather shallow curve. It's a broad S-shaped curve because 00:18:09.14 if we deliver somewhat fewer than five, or somewhat more than five, 00:18:16.05 there will be a gradual increase in the probability that 5 or more photons are acquired 00:18:21.01 because the spread in the number of photons that are issued per trial 00:18:26.14 has this rather large variation. 00:18:29.00 On the other hand, if a larger number, say 50 or more photons is required per trial, 00:18:35.03 the curve is somewhat steeper. 00:18:38.12 So, I think you can see that there's a sharper cutoff, where below the average of 50, 00:18:44.15 it's rather unlikely that a sufficient number will be delivered to the retina 00:18:49.22 and above 50, say 60 or 70 or 80, it's very, very likely 00:18:54.20 that above that number will be delivered to the retina... 00:18:57.29 Hence, the steepness of the curve. 00:18:59.22 And therefore, based simply on how shallow or steep the response curve is, 00:19:06.06 Hecht was able to determine how many photons are required to see a flash of light. 00:19:12.25 The answer, remarkably is only 5-7 photons, a very small number. 00:19:18.23 So, even though 100 photons strike the cornea, only 5-7 of them 00:19:24.23 are actually used to initiate the visual sense at absolute threshold. 00:19:29.22 5, 6, or 7 photons corresponds to an extremely small amount of energy. 00:19:36.02 Let's get a sense of how small that energy is, and we'll compare it to the energy 00:19:41.02 that's lost by dropping a dime 1mm in the Earth's gravitational field. 00:19:46.06 So, I have a dime here, and I'm just going to drop it 1mm onto the palm of my hand, 00:19:50.25 and it makes a little thud. 00:19:52.10 I can certainly feel it, but it's not a big stimulus. 00:19:55.17 And, let's ask, suppose we convert that amount of energy into photons... 00:20:01.23 We can ask how many photons would that give us? 00:20:04.27 That's a very straightforward calculation. 00:20:07.14 Here, we've just calculated the weight of the dime: 10^-3 kg, 00:20:11.29 the acceleration in the Earth's gravitational field: 9.8m/s^2, 00:20:17.17 and the distance dropped: 10^-3 meters, 00:20:21.20 The product of those gives us 9.8*10^-6 joules. 00:20:25.22 That's how much energy was lost when we dropped the dime 1 mm, 00:20:29.19 and that, of course, was the energy that hit the palm of my hand. 00:20:34.00 Now, let's figure out the amount of energy per 500nm photon. 00:20:38.27 This would be a wavelength right in the middle of the visual spectrum. 00:20:43.17 And, of course, energy for photons = h * nu. 00:20:48.01 h is Planck's constant, nu, the frequency is the speed of light over wavelength. 00:20:53.20 We can plug in the numbers as shown down here. 00:20:56.04 We end up with 4*10^-19 joules per photon. 00:21:02.17 Now, comparing this number to the number that we calculated for dropping that dime 1 mm, 00:21:08.20 we see that the energy equivalent to dropping a dime 1 mm in the Earth's gravitational field 00:21:14.28 corresponds to 2*10^13 photons. 00:21:20.11 That is, that energy, if divided into flashes of light and delivered to every person on the planet, 00:21:27.29 would give a very bright and easily detectible flash. 00:21:31.25 That means that the visual system is extremely sensitive at absolute threshold. 00:21:37.24 A remarkable property. 00:21:40.05 Now let's ask if it's possible to look at the single-cell level 00:21:45.00 and see the single-cell correlate of this incredible sensitivity. 00:21:49.04 At this point, I should mention that the flash of light that's used 00:21:53.22 for an experiment of the sort that Hecht did 00:21:55.23 lands on the retina over an area that encompasses roughly 500 photoreceptor cells. 00:22:01.15 Why 500? Because that's the region that is summed 00:22:05.20 by a single ganglion cell and affects its output. 00:22:09.03 If it's spread over a much larger region of retina, 00:22:12.08 the sensitivity will go down because the information will be carried 00:22:16.04 by different channels that are not as effectively integrated. 00:22:20.14 But, if we look at a region of just 500 photoreceptor cells, 00:22:25.09 and we deliver the flash of light to just that region, 00:22:28.20 then those signals will impinge on a single ganglion cell 00:22:32.02 or a small number of ganglion cells and the signal will be optimally delivered to the brain. 00:22:36.25 Now, the fact that we can see as few as 5-7 photons reliably, 00:22:44.12 over an area that is encompassed by 500 photoreceptors must mean that, 00:22:49.24 in general, a single photoreceptor is responding to a single photon. 00:22:55.08 Of course, most of the photoreceptors are capturing no photons. 00:22:57.15 The occasional photoreceptor is capturing only one, and very rarely 00:23:02.28 -- hardly ever -- is a photoreceptor capturing more than one in that circumstance. 00:23:06.18 So, this would predict that photoreceptors can, in fact, 00:23:10.20 capture and amplify the signal from a single photon. 00:23:14.29 The predicted single photon response has, in fact, been measured in photoreceptor cells, 00:23:21.24 and it's done by recording the current flowing into a single rod outer segment 00:23:27.15 using the recording arrangement shown here. 00:23:30.19 This large object is a glass electrode. This is its tip. 00:23:37.19 It has an opening down at the bottom, and within that opening is a single rod outer segment... 00:23:44.15 (You can just barely see it) 00:23:46.01 ...drawn up from this little chunk of retina, 00:23:48.18 where there are many other outer segments sticking out. 00:23:51.16 And, this horizontal yellow line is the exciting beam... 00:23:57.14 the beam of light which is going to stimulate that photoreceptor outer segment. 00:24:01.17 Using this apparatus, where the seal between the outer segment 00:24:07.12 and the recording pipette is extremely snug at the bottom allows one 00:24:12.12 to measure the current that flows in the top, into the cell, and then out the bottom. 00:24:18.16 And what one observes with this sort of recording setup 00:24:25.22 is that a response to a brief flash of light, 00:24:29.05 and that's shown here in this middle trace here, this little blip is the light stimulus. 00:24:36.16 The response to that brief flash has a characteristic shape and duration. 00:24:42.21 If the flash is very bright, as we see with the highest of these response curves, 00:24:47.27 the response rises quite rapidly to a final saturating level. 00:24:53.25 It's maintained at that level and then it returns back to baseline. 00:24:58.01 As the light gets dimmer and dimmer and dimmer, as we see in this family of response curves, 00:25:03.09 the response correspondingly goes down. 00:25:05.22 At some point, the response is quite small. 00:25:08.13 And as the light gets ever dimmer, we see that the response is either there or not there. 00:25:16.19 It's quantized. 00:25:17.11 That is the response to single photons, where the capture of a photon 00:25:24.07 occurs only rarely per trial, and when it does occur, it's almost always a single one. 00:25:30.07 Occasionally, there are two, and one can see that as a response 00:25:32.29 that's roughly twice the size of the single photon response. 00:25:37.28 Now if that's all there was to it, you might wonder, 00:25:42.02 well why can't the brain just see a single photon? Why do we need 5-7 photons? 00:25:48.28 And the answer is that this is not the entire story. 00:25:53.11 If you look at the response properties of a rod cell, 00:25:58.21 in complete darkness, what you see is that there are electrical events that resemble... 00:26:04.19 in fact, are indistinguishable from single photon events. 00:26:08.11 So, here's a series of traces. The upper three traces show 00:26:12.28 the responses of a single rod outer segment 00:26:16.16 to complete darkness. So, in theory, there should be no activity whatsoever. 00:26:23.14 But, in fact, you see that there's first a little rumbly background. 00:26:27.13 It's not a completely smooth baseline. 00:26:29.08 But, most strikingly, there are a series of occasional responses - little blips - 00:26:34.24 which in fact resemble in every respect the response to single photons. 00:26:39.12 Now this is not just noise in the recording apparatus. 00:26:42.28 How do we know that? 00:26:44.19 Because in this lowest trace, the same rod has been exposed to very bright light 00:26:49.16 and the very bright light saturates the response, and as you can see, it's quite smooth... 00:26:54.27 relatively smooth. It clearly lacks these individual blips up and down. 00:27:01.12 And therefore, this alone says that the noise that we're seeing comes from the rod, 00:27:06.24 and it comes from the dark-adapted rod, and it's completely suppressed 00:27:11.01 in the presence of saturating light. 00:27:12.29 Now, what's the origin of these little responses that look like single-photon responses? 00:27:18.18 Well these are thermal isomerizations of the visual pigment, rhodopsin. 00:27:25.02 That is, occasionally, the 11-cis-retinal, even in the absence of light 00:27:30.24 will spontaneously isomerize to all-trans. 00:27:33.18 On a per-molecule basis, it only happens about once every 100 years. 00:27:38.01 But, there are a very large number of these molecules per photoreceptor cell, 00:27:42.19 so in a given cell, one of those events happens roughly every minute or so 00:27:48.22 or every half-minute. 00:27:51.05 So that makes the problem from the point of view of the ganglion cell, 00:27:55.02 more complicated. What does this thermal isomerization mean 00:28:00.20 from the point of view of the signal that's being sent from the retina to the brain? 00:28:04.22 Recall that the ganglion cells that are sending this signal 00:28:09.23 are in charge of roughly 500 photoreceptors each. 00:28:12.25 Now that ganglion cell has the task of distinguishing signal - true signal 00:28:18.21 (that is, a light-induced response) from the thermal noise. 00:28:23.16 Now, we saw that the thermal noise consists of spontaneous events 00:28:27.21 at a frequency of roughly 1 or 2 per minute per photoreceptor cell. 00:28:33.01 And so the ganglion cell is being bombarded with perhaps 5 or 10 00:28:37.27 of these false signals every second. 00:28:40.18 I think you can see immediately why a true signal consisting only of a single photon 00:28:46.01 absorbed could never be seen over that background. 00:28:48.21 What the ganglion cell is looking for, then, is a small number or more 00:28:55.28 of responses over a very small time interval. 00:29:00.01 Say, ten or so milliseconds, that would be a signal that rises above that noise. 00:29:06.24 So, if we see, for example, in this central panel, here just drawn schematically, 00:29:12.12 what the ganglion cell input looks like. 00:29:15.04 It's this noisy signal coming from these many photoreceptor cells. 00:29:20.03 But, if there's a flash of light as shown in this upper trace here 00:29:24.11 at one moment in time, which induces a series of photoreceptor responses 00:29:30.04 which bring that input to the ganglion cell above the noise 00:29:34.03 by some criterion, then the ganglion cell will respond by firing action potentials 00:29:40.19 (a couple of action potentials are shown here) 00:29:42.26 which, upon receipt in the brain, may register in consciousness 00:29:47.11 as a signal above noise. Again, at each step, there is a signal to noise issue, 00:29:52.10 because of course, the ganglion cell occasionally 00:29:54.25 fires an action potential when there is no light, because just in response to the random input 00:30:02.03 the threshold has been reached to initiate an action potential. 00:30:06.12 So, really the system is built to be a coincidence detector. 00:30:11.12 And, the five to seven photons are required to bring that signal 00:30:17.03 above the noise to an extent that it is statistically significant. 00:30:21.10 And that's really the very best it can do in the context of photoreceptors 00:30:28.02 that are not completely noiseless. 00:30:29.22 Now let's ask, looking inside the photoreceptor, 00:30:35.16 how it can detect a stimulus as weak as a single photon. 00:30:42.29 This, of course, is by virtue of the quantum nature of light, 00:30:47.15 the smallest possible stimulus that the photoreceptor could detect. 00:30:51.28 And, if we take an engineer's view of signal amplification in sensory receptors 00:30:57.24 we could imagine ways in which the photoreceptor might be built to respond to this signal. 00:31:05.14 And then we can ask, how do those different potential ways 00:31:10.11 measure up in terms of detecting very weak signals? 00:31:13.21 So, on the left here, I've illustrated just the very simplest possible 00:31:18.05 response that one could have, 00:31:19.13 that is the receptor, R, converted to an activated form, R*, 00:31:24.12 which is the entire response. There's nothing more in this instance, 00:31:29.02 and a little flash of light here, shown by this blip, 00:31:31.10 would elicit an essentially immediate response: 00:31:33.10 this step function of receptor being active. 00:31:36.19 Now that is certainly a possible way to build a receptor. 00:31:40.17 But, it doesn't have an amplification built in, in the sense that a single initiating particle, 00:31:48.03 say a photon, doesn't lead to multiple particles within the responding cell. 00:31:53.02 And so, we just have a 1:1 correspondence between input and output. 00:31:57.14 So, that's an unamplified system. It's rapid, but not particularly sensitive. 00:32:02.23 We could make it more sensitive in this central panel, by imagining 00:32:08.05 that the activated receptor, R*, is a catalyst. 00:32:12.20 This is the classic way that biological systems amplify signals, 00:32:16.18 by initiating the formation or unveiling the formation of a catalyst. 00:32:22.01 And that this catalyzes a reaction, indicated here as A being converted to A*. 00:32:28.09 Now that has a virtue of amplification, because for every catalyst which appears-- 00:32:37.11 the R* which appears in response to the stimulus-- 00:32:41.21 there will be many A to A* conversions. 00:32:46.05 And, I think if we see the time course here, of A* appearing as a function of time 00:32:52.09 (that's this ramp function) 00:32:53.12 after a flash of light, we can appreciate that, although there's a bit of a delay, 00:32:57.07 it takes a while for many of these final activated compounds, A*s, whatever they are, 00:33:04.18 to accumulate, their numbers could accumulate to rather large levels. 00:33:08.28 It could be hundreds, perhaps, or even thousands. 00:33:11.01 And so that would be a way of amplifying the signal on a per-particle basis. 00:33:14.25 Let's just take that logic one step further. 00:33:17.00 Suppose, as shown on the right, A* is itself a catalyst. 00:33:23.16 So, there's an initial catalytic event, converting A to A*, 00:33:26.21 but then A* converts B to B*. 00:33:30.15 Now, we have a second stage of amplification, and if B* is the final signal 00:33:38.17 that activates the cell's response, that would have a time course 00:33:43.04 as shown on the top curve. 00:33:44.16 There would be an even greater delay, 00:33:47.02 because it takes a while for the A*s to accumulate 00:33:49.25 and then for the B*s to accumulate, in turn. 00:33:52.11 But the reward for that delay is an enormous amplification of B*s, 00:33:59.02 perhaps in the thousands, tens of thousands, or hundreds of thousands. 00:34:02.10 So, how does a photoreceptor actually do it? 00:34:05.03 Well, it turns out that this rightmost path is, in fact, 00:34:08.08 the path used in the vertebrate eye. 00:34:10.29 In this case, rhodopsin is the initial catalyst, the G protein-coupled receptor, 00:34:15.13 catalyzes the activation of multiple G-proteins called transducin, shown in green, here. 00:34:23.07 And then the transducins activate a cyclic GMP phosphodiesterase, 00:34:28.09 shown in blue. So, in the dark, the phosphodiesterase is inactive, 00:34:34.28 the transducin is also inactive, the rhodopsin is inactive, 00:34:37.16 and cyclic GMP is present at quite high concentrations. 00:34:42.12 And cyclic GMP, the internal messenger, acts directly on an ion channel in the membrane, 00:34:49.13 a sodium and calcium permeable channel, and maintains it in the open state. 00:34:54.17 The effective light activation of this cell is to activate a rhodopsin, 00:35:00.16 this red ball here, which then activates a series of transducins -- 00:35:05.10 a large number, although only one is drawn here, it's in the hundreds, 00:35:08.14 and each of those transducins then activates a phosphodiesterase, 00:35:13.04 which in turn hydrolyzes hundreds to thousands of cyclic GMPs. 00:35:16.16 So, the cyclic GMP level drops precipitously, 00:35:20.28 and that drop then leads to the closure of the ion channels. 00:35:25.15 In fact, you can even think of the ion channel as, essentially, a catalyst. 00:35:28.16 It's catalyzing the transfer of ions from one side of the membrane to another. 00:35:33.01 A single ion channel, of course, on a per-particle basis, allows the passage of many ions, 00:35:38.15 so really, in a sense, there are three stages of amplification in the system. 00:35:43.05 And this is what has allowed a rod photoreceptor to respond to a single photon-- 00:35:49.23 this enormous per-particle amplification.
