Genes, The Brain, and Behavior

Part 1: Genes, the Brain and Behavior

00:00:00.00 Hi, I'm Cori Bargmann,
00:00:02.15 I'm a professor at the Rockefeller University in New York,
00:00:05.10 and an Investigator of the Howard Hughes Medical Institute.
00:00:08.12 I'm going to talk to you today about how we can use genes to understand the brain and behavior.
00:00:14.09 I'll discuss that in the context of our magnificent human brain, and also in the context of simpler brains,
00:00:20.05 brains that range from the brains of worms to flies to mice to dogs.
00:00:27.20 So, why should we think that we can understand behavior by studying genes?
00:00:32.20 And why do we think it's important to understand behavior studying genes?
00:00:37.04 To illustrate and answer those points, I'd like to use this first slide to tell you about the familial risk of important psychiatric illnesses.
00:00:45.19 If one member of a pair of identical twins suffers from the neurodevelopmental disorder autism,
00:00:51.29 the identical twin has about a 70% chance of having the same disorder.
00:00:56.23 This is vastly higher than the risk of this disorder in a sibling,
00:01:01.06 or in the general population, where it's less than 1%.
00:01:05.02 Now, the fact that this risk is so high in identical twins but much lower in non-identical twins
00:01:11.02 tells us that there is likely to be a genetic contribution to this important psychiatric disorder.
00:01:17.11 The same is seen when other important neurological or psychiatric disorders,
00:01:22.15 including the disorders of schizophrenia, bipolar disorder, depression, or anxiety disorders.
00:01:28.26 These are disorders that collectively affect millions of people.
00:01:33.05 They can be severely disabling, in fact, severely disabling even to the level of shortening the lifespan of the people who are affected.
00:01:41.04 It's very important to us to try to understand what is occurring to allow genes to go wrong and to interact
00:01:48.10 with environmental risks to generate these kinds of problems.
00:01:53.18 So, how do we understand what genes can do?
00:01:56.28 What can we learn from studying genes about different kinds of disorders?
00:02:01.12 Well, the very first genetically defined brain disorder, called phenylketonuria, or PKU,
00:02:08.12 was identified in 1934, and it already provided for us important information about how understanding brain disorders
00:02:17.02 and the genes behind brain disorders, we can intervene productively to improve the lives of people who suffer from these disorders.
00:02:26.02 So phenylketonuria is a very severe developmental disorder.
00:02:29.24 Children with phenylketonuria are mentally delayed and retarded, they have delayed social skills,
00:02:36.00 they're hyperactive, they have movement disorders, they have severe seizures.
00:02:40.08 And all of these result from a single change in a single gene:
00:02:43.28 The gene for phenylalanine hydroxylase, a metabolic gene that converts the amino acid
00:02:49.17 L-phenylalanine to L-tyrosine. Why does the absence of this enzyme cause this severe disorder?
00:02:58.13 This information, this chemical information, propagates from the level of the gene to the level of the individual.
00:03:06.16 The gene, a mutation in phenylalanine hydroxylase, leads to the production of toxic products.
00:03:14.23 These toxic products accumulate in neurons, and because of those toxic products, neurons, which are supposed to have elaborate structures,
00:03:22.15 instead are smaller and simpler in their structure, and many of the neurons die.
00:03:27.23 As a result, the brain of these children has altered function,
00:03:31.27 and the behavior and their medical disorders result.
00:03:35.23 So, all of this is a form of toxicology, but once we understood what the gene was,
00:03:40.23 it was immediately clear that this was something that could also be treated,
00:03:45.11 because phenylalanine is a chemical that is present in our diet.
00:03:50.11 And simply by limiting the amount of phenylalanine in the diet of children with PKU,
00:03:55.07 it's possible to limit many of the effects of this very severe disorder.
00:04:00.03 So, intervening at an environmental level can lead to great improvements in the health of these individuals.
00:04:08.14 Now, for most brain disorders that I mentioned in the first slide, we don't have anything like this ability to intervene.
00:04:15.10 We don't know the genes as well, we don't know their effects on the brain,
00:04:18.29 and we don't have anything as simple as a dietary fix.
00:04:21.28 But this is our goal: Is to be able to understand brains well enough to intervene in each brain disorder,
00:04:28.28 whether at a genetic level, an environmental level, a cellular or a brain level,
00:04:34.05 to try to improve the disorder and the lives of the people suffering from it.
00:04:40.03 So, what are the tools we can use to understand these disorders?
00:04:44.12 Well, we believe that these many disorders and many processes of the brain have a biological origin.
00:04:51.12 And that therefore, like all biological processes, they are under the control of our genes.
00:04:58.23 When we look at the genes in the human genome, we find, much to our surprise, that while humans are unique,
00:05:04.19 and the human brain is unique, the human genes are not unique.
00:05:08.22 Most human genes, the overwhelming majority, are shared with other animals.
00:05:13.24 Only about 1% of all human genes can be considered unique to the human.
00:05:19.24 Another 20% are present in humans and all other vertebrates, although not in simpler animals.
00:05:26.10 Almost half of all human genes are shared between humans and all animals, including butterflies and snails and worms.
00:05:34.12 An additional large fraction are shared even with unicellular organisms, like yeasts.
00:05:40.00 And finally, there's a large fraction that are shared even by bacteria and humans.
00:05:44.13 So when we look at this big pie chart, we realize that most of the time, we can understand genes by studying them in much simpler organisms,
00:05:52.25 and we can then take our knowledge of these genes from simple organisms, and try to return them to understanding the complex human brain.
00:06:02.18 Now, what about the brain itself? What about this complex structure?
00:06:07.10 Many of you who've seen images of the human brain, as shown here at the top...
00:06:11.03 Now the human brain is very complex, but when we look at the brains of simpler animals, we see that the human brain has
00:06:18.03 evolved from them gradually by changing the size and the placement of common brain regions,
00:06:24.06 and that diverse animals share common brain regions, again suggesting that we can study them in simpler animals, not just in humans.
00:06:32.19 In fact, we can see, when we compare the human and the monkey, how similar they are.
00:06:38.07 We can see in the rat and the mouse that some of the same regions are sort of changed in location and changed in size.
00:06:44.14 If we go all the way down to the shark brain, we see something that looks on the outside very different in structure from the human brain below,
00:06:52.05 but by understanding what the different brain regions are, we can see that in fact the parts of the shark brain and the parts of the human brain are rather similar,
00:07:01.00 that even the higher processing centers are present in the shark, along with regions that control things like movement and learning.
00:07:10.04 So we believe that we can study brain regions across different species and understand fundamental principles about how brains work.
00:07:21.11 What do we want to know about behavior? What are the organizing principles of behavior?
00:07:26.14 The way that this is studied, traditionally, is using another science that goes back to the 1930s, a science called neuroethology.
00:07:35.16 Neuroethology is the study of animal behavior, trying to understand common principles and rules that underlie behavior.
00:07:43.04 And a variety of principles have emerged from studying behaviors of many animals.
00:07:47.08 I'll illustrate them here with a few colorful examples.
00:07:50.09 Here, the work of Niko Tinbergen in stickleback fish, was used to establish the principle
00:07:55.20 that animals have stereotyped behaviors in response to sensory stimuli,
00:08:00.18 that they had innate behaviors that can be reliably observed in all individuals when they encounter certain features of their environments.
00:08:08.27 Now, their examples of innate behaviors might include courtship or aggression behaviors,
00:08:14.04 they would also include things like food search behaviors.
00:08:19.21 A second principle that emerged from neuroethology is the recognition that the brain does not exist just to respond to the outside world.
00:08:27.22 The brain has its own internal drives that organize behaviors.
00:08:31.26 And a lovely example of this, from the work of Konrad Lorenz, is the fact that newborn birds,
00:08:37.03 such as ducks and geese, have an internal drive to attach to the first moving object they see.
00:08:44.09 Now, normally this would be their mother, whom they would follow around throughout their young lives.
00:08:49.14 The mother would then bring them to the right foraging grounds and protect them from danger.
00:08:54.03 Now in this particular case, these geese saw Konrad Lorenz as the first thing when they hatched;
00:08:58.25 they are now following him around his garden.
00:09:01.06 And this process of imprinting, and other kinds of special learning processes,
00:09:05.29 are observed with respect to these internal drives that animals show, to have certain kinds of behaviors.
00:09:14.10 A third principle that emerged from neuroethology is the importance of social behavior
00:09:20.06 and the fact that social behavior is widespread among animals.
00:09:24.03 The most dramatic demonstration of this was the work of Karl von Frisch, who worked on honeybees,
00:09:29.07 simple insects, and showed that they have incredibly elaborate forms of communication and social behaviors.
00:09:36.07 So even insects can show elaborate social structures.
00:09:40.03 For example, the waggle dance that the honeybees use to signal to each other about the presence of food.
00:09:45.16 Or their use of pheromones to interact with each other and with their queen.
00:09:50.25 So I'm going to try to illustrate these classical questions from neuroethology,
00:09:56.19 in the context of modern day genetics and modern day nervous system methods,
00:10:01.17 to think of a framework for behavior that incorporates genes, neurons, and brains.
00:10:09.07 This framework here is cartooned on the left, a cartoon that will appear multiple times.
00:10:14.01 We think of environmental cues as leading to perception, decision, and action.
00:10:20.01 And this left side here relates to the basic processes of how animals generate innate responses to an environmental cue.
00:10:28.28 But, we also have to think that behaviors can be internally generated by internal states and motivation,
00:10:35.00 and that things like memory of course will modify all of these outcomes.
00:10:38.17 And I will illustrate how genes affect this right-hand side of the equation as well.
00:10:45.03 So, I will talk about three different topics today, using examples from animals to illustrate
00:10:50.22 how this framework for behavior can be used to understand how genes affect neurons, which affect brains, which affect behavior.
00:10:58.27 And the three examples will be:
00:11:00.12 One example, on the left side, moving from sensation to action, and the innate responses to environmental cues;
00:11:08.27 the second will be an example of internal motivation, using sleep and circadian rhythm as an example;
00:11:15.04 and the third will address the question of why we don't all behave, where variation comes from that gives rise to different behaviors in different individuals.
00:11:27.01 Now, in each of these three sections, I'm going to talk about one particular class of genes, not because it's the
00:11:33.01 only class of genes that affects behavior, but because it is an important class of genes that affects behaviour.
00:11:39.04 And it serves to illustrate these principles very beautifully.
00:11:42.19 And that class of genes are the genes that encode G protein-coupled receptors.
00:11:47.27 G protein-coupled receptors are molecules that sit on the cell surface of neurons and also of other non-neuronal cells.
00:11:55.21 They detect stimuli outside the cell and then propagate a signal to the inside of a cell that causes biochemical changes in the cell:
00:12:04.05 Classically, the production of signal transduction second messengers, like cyclic AMP or inositol trisphosphate.
00:12:12.18 Now, I'm not going to talk about their signaling in detail.
00:12:15.18 What I'm going to point out is that, by transmitting signals from outside the cell to the inside of the cell,
00:12:21.03 G protein-coupled receptors are able to interface with many of the important kinds of systems that regulate behavior.
00:12:28.28 Let's start on the left here with environmental stimuli.
00:12:32.05 G protein-coupled receptors on your sensory neurons are critical for the detection of odors, tastes, and light.
00:12:40.05 When you smell a barbeque, or you taste a cookie, or you see someone walking across the room,
00:12:45.23 the first event that happens in your nervous system is the activation of the G protein-coupled receptor
00:12:51.00 on an olfactory neuron, a taste cell, or a photoreceptor.
00:12:57.04 In addition to their important role in detecting environmental stimuli,
00:13:01.07 G protein-coupled receptors inside the body detect signals that pass from one cell in the body to another cell in the body.
00:13:08.01 These are internal signals. So for example, adrenaline:
00:13:11.27 the speedy heartbeat and sweating that occurs when you're exciting,
00:13:15.23 occurs because G protein-coupled receptors recognize adrenaline that's been secreted into the bloodstream,
00:13:21.15 and tell different cell types that something has happened and cause them to change their behavior appropriately.
00:13:27.16 Dopamine, a small molecule that's used to signal reward or the anticipation of reward,
00:13:32.29 and is implicated in important processes like drug addiction,
00:13:36.01 also signals through G protein-coupled receptors on neurons that detect this molecule.
00:13:42.23 I'm going to start my talk today with talking about the response to external, environmental stimuli, and particularly about the sense of smell.
00:13:51.00 The sense of smell begins with G protein-coupled receptors in the olfactory neurons of the nose.
00:13:56.23 Large families of these receptors detect different chemicals in the environment.
00:14:01.04 Different neurons express different receptors to detect different chemicals, and my favorite of all the
00:14:06.02 G protein-coupled odorant receptors is a molecule called ODR-10, which detects diacetyl, a buttery smell.
00:14:15.28 ODR-10 is a molecule that is found in the nematode worm, Caenorhabditis elegans.
00:14:21.16 C. elegans, as it is known to its friends, is an organism that's been very valuable for studying the nervous system,
00:14:27.20 as well as other biological processes, because it's easy to grow in the lab and easy to manipulate at a genetic level.
00:14:34.25 C. elegans, which is just a millimeter long, detects many different odors,
00:14:40.00 and it responds to them, showing innate preferences for different odors.
00:14:43.21 So for example, the smell of diacetyl is released by some of C. elegans' natural food sources.
00:14:50.11 And therefore, when C. elegans smells this odor, it approaches it, it's attracted to the odor.
00:14:56.24 Conversely, when C. elegans smells certain kinds of toxic odors,
00:15:00.00 like nonanone, it's repelled by those odors, and it goes away from them.
00:15:04.26 Diacetyl is detected by ODR-10, the G protein-coupled receptor I mentioned before.
00:15:10.29 The G protein-coupled receptor is expressed in a pair of neurons in the tip of the worm's nose, these blue neurons here.
00:15:18.27 They're exposed to the environment, and they detect diacetyl in the environment to initiate the odor preference behavior.
00:15:26.02 Another pair of neurons right next to them, in red, detect repulsive odors.
00:15:31.15 So you could think of ODR-10 as a gene for a behavior.
00:15:35.23 ODR-10 is certainly required for the worm's response to diacetyl.
00:15:40.13 So, that's illustrated by comparing panels 1 and panel 2 here.
00:15:45.20 A wild-type worm, or a wild-type group of worms, when placed in an environment with diacetyl at one location,
00:15:51.24 will quickly approach the diacetyl and accumulate at the source of this delicious odor.
00:15:57.01 If the ODR-10 gene is absent, if there's no receptor, the animals now ignore the odor.
00:16:02.17 They'll scatter at random across the environment, as if nothing was happening.
00:16:06.29 So that tells us that ODR-10 is required for detection of the odor, but there's a more important question, and that is:
00:16:13.25 How do you go from that question of detection, to the process of attraction?
00:16:18.08 How do you generate the behavior of approach?
00:16:21.25 That could be because the receptor itself somehow drove the animal to approach the odor.
00:16:28.10 It could be because the animal had learned about the odor.
00:16:31.02 Or it could be because something about the interaction of the receptor and the neuron in which it was expressed was important.
00:16:38.28 To test these different hypotheses, Emily Troemel did an experiment
00:16:43.11 in which she moved the ODR-10 receptor from its normal location, in the AWA neuron,
00:16:48.28 to an abnormal location, in the red neuron, AWB, which normally detects repellents.
00:16:55.22 So, this was done using a combination of the mutant and transgenic technology,
00:17:00.08 which enables us to manipulate the site of expression of any gene within this animal.
00:17:05.10 She then asked whether these animals responded to diacetyl,
00:17:08.19 and they did, but they responded inappropriately.
00:17:12.11 They were repelled by diacetyl instead of being attracted.
00:17:15.21 Moving the receptor to a cell involved in avoidance transformed the behavior from attraction to avoidance.
00:17:23.26 And what this experiment tells you is that the neurons are what determine whether a response is attractive or repulsive,
00:17:31.05 that the sensory neurons are encoding behavioral responses.
00:17:35.05 They're starting the anatomical process of generating different innate responses.
00:17:40.01 The blue AWA neuron encodes approach responses,
00:17:43.27 and receptors expressed on this neuron will drive attraction.
00:17:47.14 The red AWB neuron encodes avoidance responses,
00:17:51.04 and receptors expressed on this neuron will drive repulsion.
00:17:55.23 This example of an innate behavior comes from a very simple animal, but as we move up the evolutionary ladder,
00:18:02.08 we see that similar principles apply in much more complex nervous systems, including mammalian nervous systems.
00:18:09.26 For example, mammals like sweet foods or foods with amino acids that contain valuable nutrients.
00:18:17.24 Mammals avoid toxins and alkaloids; we perceive them as bitter.
00:18:22.25 And work from Charles Zuker, Nick Ryba, and their colleagues, has demonstrated that these mammalian taste responses
00:18:29.10 are hard-wired using exactly the same principle that hardwires worm attraction and avoidance responses.
00:18:36.16 There are different kinds of taste cells in the tongue:
00:18:40.19 T1R taste cells detect these attractive tastants, T2R taste cells detect bitter compounds.
00:18:48.04 Each expresses certain G protein-coupled receptors that detect these molecules in your diet.
00:18:54.29 Now, to ask whether the cells can drive these innate, hard-wired behaviors,
00:19:00.28 the Zuker and Ryba Labs did the following experiment:
00:19:03.26 They took a receptor called a RASSL receptor. It's a receptor that's not found in nature;
00:19:08.22 it's engineered in the laboratory, and it detects a compound that's not found in nature, that's only found in the laboratory.
00:19:15.28 They put the RASSL receptor either on the T2R cells, that sense bitter compounds,
00:19:22.16 or they put it on the T1R cells that sense sweet compounds, and they asked the mice:
00:19:28.02 What do you think about this RASSL ligand?
00:19:31.13 Naive mice that have never seen a RASSL ligand don't respond to it one way or another,
00:19:36.14 but if they have this receptor on their bitter cells, they reject the RASSL ligand; they perceive it as bitter.
00:19:44.27 And if they have this receptor on their sweet cells, they drink the ligand; they perceive it as sweet.
00:19:51.07 So the conclusion from this is that our basic acceptance of sweet and rejection of bitter substances is encoded by neural pathways,
00:20:00.16 and this idea was intuited hundreds of years ago by the French philosopher and mathematician, RenÃ© Descartes,
00:20:08.11 who in this illustration here showed that a person putting their foot near a fire
00:20:13.26 would generate a nerve signal up an innate pathway that would cause them to remove their foot from the fire.
00:20:19.20 They didn't have to think about this stimulus, they didn't have to learn about this stimulus,
00:20:24.07 they had an anatomical pathway for an innate preference that told them that this fire was too hot.
00:20:30.22 And so by understanding genes, neurons, and brains,
00:20:34.03 we can see the beginning of a principle for one idea about how behaviors emerge,
00:20:40.04 and particularly how innate behaviors are built into a nervous system
00:20:44.10 to help an animal respond sensibly to its environment, from its moment of birth.
00:20:52.15 So we're turning to our framework of behavior, we can now begin to see what's happening on the left side of this diagram,
00:20:58.13 about how environmental cues and perception can lead to distinct actions by propagating information through different parts of the nervous system.
00:21:07.09 Let's think now about the right-hand side of this diagram,
00:21:10.19 and think about internal states that can motivate behavior.
00:21:14.17 And for that, I will talk about important internal states of sleep and arousal.
00:21:20.22 Sleep is one of the important activities that humans do and that animals do.
00:21:27.03 Humans sleep about eight hours a day, usually at night.
00:21:31.20 Some animals sleep in the night, some animals sleep in the day, but as we examine other animals,
00:21:36.14 we see that even animals as simple as fruit flies can show sleep-like behavior and waking-like behavior.
00:21:43.21 We can see this just by monitoring their activity levels:
00:21:46.23 If we look at a fruit fly at light or in dark,
00:21:50.06 we see that they move around a lot during the the light, and they rest during the dark.
00:21:55.02 Interestingly, if you change a fruit fly from light-dark cycles into constant darkness,
00:22:00.21 you see that it still follows a 24-hour rhythm.
00:22:04.11 It moves for about 12 hours and then it rests for about 12 hours.
00:22:08.18 This indicates that it has an internal biological rhythm, which is called the "circadian clock."
00:22:15.09 Seymour Benzer and Ron Konopka decided to look for genes that affected the circadian clock in fruit flies,
00:22:21.29 and they did this by searching for fruit flies whose 24-hour cycle was abnormal,
00:22:27.12 and they were able to identify many classes of mutant fruit flies with abnormalities.
00:22:32.05 Fruit flies, for example, that had no rhythm at all,
00:22:34.18 that would just sort of fly around or sit still at random during the day and the night.
00:22:38.23 Also, fruit flies that had a short cycle; when placed in constant darkness,
00:22:43.21 instead of cycling over 24 hours, they would cycle over as few as 19 hours.
00:22:49.18 And conversely, fruit flies whose cycle was long,
00:22:53.03 where instead of cycling over 24 hours, they might cycle over 28 hours or more.
00:22:57.27 So you can think of these 19 hours as "early risers,"
00:23:01.14 and these 28-hour guys as the flies who like to stay up late.
00:23:05.26 Remarkably, all three of these mutations affected a single gene.
00:23:11.07 There was one gene that, because of different kinds of changes in its activity,
00:23:16.03 could either completely disrupt the rhythm, make it shorter, or make it longer.
00:23:21.18 And that pointed to the fact that this gene must have a key role in determining the running of the circadian clock,
00:23:29.01 and this gene is called "per," for "period."
00:23:32.20 A series of molecular studies from many different labs has led to the elucidation of this circadian clock.
00:23:40.22 Indeed, the per gene is an important element of the circadian clock,
00:23:44.21 but there are other molecules that are involved as well.
00:23:48.03 These molecules function within the cell to regulate patterns of gene expression,
00:23:52.19 and they regulate each other's gene expression through a negative feedback loop.
00:23:58.14 So, how this feedback loop works is that, during the night,
00:24:02.22 a transcription factor named "clock" drives the expression of the per gene identified from that early fly screen.
00:24:11.15 Early in the night, per is unstable,
00:24:13.18 but over time it becomes more and more stable and builds up.
00:24:17.03 Its buildup during the night causes it to eventually accumulate at sufficient levels,
00:24:21.27 that it can enter the nucleus early in the day.
00:24:24.14 And when per enters the nucleus, what it does is to inhibit the clock gene that is turning per on.
00:24:31.14 Well, eventually that means that per is going to run down again
00:24:34.24 because the clock gene is no longer leading to its transcription.
00:24:38.07 And so as the day wears on, per becomes less active, and clock becomes active again,
00:24:43.08 so at night, clock can begin to make per again.
00:24:47.01 This feedback loop between these transcriptional regulators, and other regulators that determine their levels,
00:24:53.27 is similar all the way from flies to humans.
00:24:56.25 Within the nuclei of our cells are the same kinds of transcriptional regulators oscillating in the same patterns
00:25:04.13 between night and day, as are observed in the fruit fly.
00:25:12.11 How do these genes affect our behavior?
00:25:15.13 Why are we active at different times?
00:25:18.15 It turns out that, in humans, although many cells have these clock genes and have their own circadian clocks,
00:25:25.13 there are specific brain regions in which these clock genes are important to dominate behavior.
00:25:31.21 And these brain regions are buried deep within the brain in an area called the hypothamalus,
00:25:38.06 and in particular, in a region of the hypothalamus called the suprachiasmatic nucleus.
00:25:43.07 This is what you might think of as the "master clock."
00:25:46.10 The activity of the clock genes in the suprachiasmatic nucleus regulates the physiology and behavior of animals.
00:25:53.20 And so we have here the per and the clock gene oscillating in one region of the brain,
00:25:59.01 to then affect the outcome at the level of the whole organism.
00:26:03.23 Per and clock were discovered initially in flies and mice, but remarkably,
00:26:10.19 in humans, the exact same genes can lead to changes in human behavior.
00:26:15.19 So there's a sleep disorder called "advanced sleep phase syndrome,"
00:26:19.14 in which people have what might think of as an extreme, early morning lark behavior.
00:26:25.13 They get up earlier and earlier every morning, they can't stay up late at night, they keep falling asleep.
00:26:30.21 The reason is that these people have mutations in human per genes that cause their clock to run too fast.
00:26:36.26 They think that the day is only 22 hours long instead of 24 hours long deep within their hypothalamus,
00:26:42.22 and no amount of conscious control can help them to regulate all of their behavior accordingly.
00:26:50.03 So, if the hypothalamus keeps a clock, it must be regulating lots of different behaviors as well.
00:26:56.23 How does it go about transforming this information into different kinds of output behaviors?
00:27:02.02 Well, again, focusing specifically on sleep, I'd like to tell you about
00:27:05.27 a disorder of humans that's a complex and fascinating sleep disorder, called "narcolepsy with cataplexy."
00:27:13.23 In narcolepsy with cataplexy, you can think of the sleep state as "invading" the waking state.
00:27:21.13 So people with this disorder tend to fall asleep very quickly, and at inappropriate times.
00:27:27.12 They have hallucinations when they're awake, sometimes because they're dreaming when they're awake;
00:27:32.22 a sleep-appropriate response is appearing while they're awake.
00:27:36.09 And, they can lose their muscle control very suddenly,
00:27:39.18 so their bodies relax in the same way you relax when you're asleep.
00:27:43.01 This happens sometimes with excitement.
00:27:46.01 Now, very little was understood about the biology of human narcolepsy
00:27:50.10 until certain dog owners noticed that their dogs had a disorder very much like human narcolepsy,
00:27:57.04 that they fell asleep inappropriately and that they would collapse sometimes when they were excited.
00:28:02.03 And Emmanuel Mignot, studying these dogs,
00:28:05.05 was able to trace down the genetic changes that caused these dogs to have abnormal sleep-waking behavior.
00:28:13.15 And what he found is that these dogs had a deficiency in a particular brain chemical called hypocretin,
00:28:22.14 that signals through a G protein-coupled receptor called the hypocretin-2 receptor.
00:28:28.29 Building out from this discovery, and similar discoveries in mouse,
00:28:33.23 we were able to make the discovery in humans that the exact same biological system is involved in human narcolepsy-cataplexy,
00:28:42.10 as is involved in the dog disorder and in the mouse disorder.
00:28:47.12 So, there are neurons in the brain that make hypocretin.
00:28:51.19 In human patients with narcolepsy and cataplexy, these neurons are typically lost through autoimmune destruction,
00:28:58.21 leading to the loss of this peptide.
00:29:01.06 The mouse mutants that I didn't tell you about, that also have narcolepsy,
00:29:05.10 have a defect in the hypocretin gene itself.
00:29:08.26 The dog mutant that I did tell you about, these rare dogs that have narcolepsy,
00:29:13.11 have defects in the hypocretin-2 receptor.
00:29:17.15 So, what is this G protein-coupled receptor, and what is the signal that it detects?
00:29:23.06 The signal it detects is something called a neuropeptide,
00:29:26.14 a peptide made by one neuron to communicate with other neurons.
00:29:31.08 Neuropeptides represent one of the three different ways that neurons communicate with each other.
00:29:37.06 So neurons can communicate with each other at synapses,
00:29:40.08 through the process of fast chemical transmission that causes them to excite or inhibit each other locally and strongly.
00:29:47.17 They can communicate with each other through electrical connections, or gap junctions.
00:29:51.22 And they can communicate with each other through these secreted neuropeptides.
00:29:56.14 Now, neuropeptides, like classical transmitters, are secreted by one neuron
00:30:01.07 and affect another, but they have certain differences.
00:30:04.18 Classical transmitters are very fast, neuropeptides are slower.
00:30:08.29 Classical transmitters act at one synapse, neuropeptides can act at a distance...
00:30:13.18 they can broadcast information from one part of the brain to another.
00:30:18.04 And while there are only a few classical transmitters that are used over and over again,
00:30:23.21 they are many neuropeptides, and so individual neuropeptides, like hypocretin,
00:30:28.10 can have rather specific functions, like regulation of sleep and waking.
00:30:34.10 When we look at sleep behavior and its regulation by hypocretin, we see that,
00:30:40.04 within the human brain with its billions of neurons, there are just 2000 hypocretin-producing neurons.
00:30:46.11 These are the neurons that are required to prevent sleep from invading the waking state.
00:30:51.19 They're found deep in the hypothalamus, and they're closely connected with the neurons that drive the circadian clock,
00:30:58.13 so the circadian clock in the hypothalamus communicates with other neurons in the hypothalamus
00:31:05.09 that drive individual functions associated with the circadian clock, like sleep and waking.
00:31:11.01 And then these neurons broadcast information all throughout the brain to many regions involved in sleep and arousal,
00:31:17.13 in part by sending long processes to different regions,
00:31:20.09 and in part because their neuropeptide products can actually diffuse some distance from the site of production.
00:31:27.25 So sleep is an internally generated behavior that we can understand in the context of molecules for the circadian clock,
00:31:35.05 molecules for hypocretin, circuits that regulate the circadian clock and that interact with the neurons that produce hypocretin,
00:31:43.24 and also, in terms of the brain and the behavior of the whole animal.
00:31:50.10 So this is one example of an internal state and a motivation for behavior.
00:31:55.11 In my final example of a framework for behavior,
00:31:58.09 I'm going to talk about social behavior as a motivation for behavior.
00:32:02.17 Now, social behavior is a characteristic of all animals.
00:32:07.06 All animals must interact with other members of their species at certain key moments,
00:32:11.09 for example, during mating behaviors that are required for reproduction.
00:32:15.20 But social behavior, although it's widespread in animals, is also different in different animals,
00:32:21.22 so that, for example, animals recognize their own species but not other species,
00:32:26.17 and also, so that animals in different species behave differently from one another in their social contexts.
00:32:35.07 Moreover, even within the same species, animals will show different social behaviors
00:32:39.29 depending on things like their age, their sex, their reproductive status, and those of the organisms around them.
00:32:47.24 So this is an example of a behavior that shows variability, not just constancy.
00:32:54.12 Now, a nice example of social behavior's variability is illustrated by the behavior of different rodents,
00:33:01.10 that are sometimes called polygamous and monogamous rodents.
00:33:05.12 These are two different kinds of rodents, they're called voles,
00:33:08.07 and if you encounter them, they would look very similar to you, as shown by these different kinds of photographs.
00:33:14.01 But, if you examine their behaviors, you would see that these animals have really different social strategies.
00:33:19.22 Meadow voles are what are called polygamous voles.
00:33:23.09 These voles are largely solitary in their lifestyle.
00:33:26.28 Single males and females will mate briefly and then scatter.
00:33:31.11 There's very limited maternal care of offspring and no paternal care at all.
00:33:35.11 And they also differ in other social behaviors:
00:33:37.20 They're not territorial, and they're not aggressive.
00:33:40.13 By comparison, prairie voles are voles that will form pair bonds that will last for the entire life of
00:33:47.03 a male and a female after a single mating.
00:33:50.13 They live in large colonies, the mothers take very good care of the pups, and so do the fathers...
00:33:55.28 they show paternal care of their offspring.
00:33:58.04 In addition to their pair-bonding, they also show territorial and aggressive behavior,
00:34:02.13 distinguishing those within their own group from those of other groups.
00:34:07.10 So, these closely related rodents provide a way to think about what kinds of genetic changes
00:34:13.09 might evolve to allow these two different species to have such different social behaviors,
00:34:18.28 and that has been the mission of Tom Insel, Larry Young, and their colleagues at Emory University.
00:34:24.22 What they found is that these differences in social behaviors
00:34:28.01 were related to the functions of other important neuropeptides in the mammalian brain.
00:34:34.06 In mammals, social behavior is regulated by two neuropeptides that are related to each other,
00:34:40.03 called "oxytocin" and "vasopressin."
00:34:43.13 Oxytocin is strongly implicated in maternal behaviors,
00:34:47.11 as well as certain forms of maternal physiology, like nursing.
00:34:51.20 Vasopressin is related to male behaviors.
00:34:55.05 So each of these peptides exists in the brain,
00:34:58.07 each of them has its own specialized receptors that detect them.
00:35:03.21 What is the difference between polygamous voles and monogamous voles in these systems that allows them to behave differently?
00:35:13.01 Well, both polygamous and monogamous voles have oxytocin and vasopressin,
00:35:19.13 and both have receptors for oxytocin and vasopressin.
00:35:22.24 So it's not the existence of these genes that differs.
00:35:25.29 Instead, it's the way these genes are deployed in the brain
00:35:30.11 that's different in species that show different behaviors.
00:35:33.28 The difference between monogamous and polygamous voles comes when you examine the
00:35:39.10 vasopressin and oxytocin receptors in the brains of these animals and look at where in the brains these receptors are deployed.
00:35:48.04 So, this slide here shows sections through the brains of a monogamous vole and a polygamous vole.
00:35:55.27 These are both males, and they're sections of the same location of the brain.
00:35:59.13 The bright colors, the greens and reds and yellows,
00:36:02.10 illustrate locations at which the vasopressin V1 receptor is being expressed.
00:36:08.11 And what's evident from looking at this is that, while both of these species have the vasopressin receptor,
00:36:14.20 they utilize the vasopressin receptor in different brain regions.
00:36:20.01 The monogamous vole, shown at top, expresses the vasopressin receptor in regions that are involved in reward,
00:36:26.24 and the rewarding presence of this receptor helps the vole to generate
00:36:30.24 what you might think of as a positive association with its mate, that promotes the formation of a pair bond.
00:36:37.19 The polygamous vole, shown at bottom, does express a vasopressin receptor,
00:36:41.28 but it expresses it in different brain regions that would not allow this animal to form a rewarding memory.
00:36:47.20 And so the utilization of these receptors in different brain regions
00:36:51.28 causes different kinds of associations to be built and different behaviors to result.
00:36:57.13 So, we're turning to the framework for behavior.
00:37:00.20 I've tried to illustrate with a few examples how we can look at behaviors that are interesting between different animals,
00:37:08.18 and also behaviors that are shared by different animals, and think about them in the context of genes, brains, and behavior.
00:37:16.27 Our challenge now, as neuroscientists, is to ask how all of these processes
00:37:21.02 (environmental perception, decision-making, action, memory, internal states, and motivation)
00:37:28.06 relate to the functions of different genes;
00:37:30.15 how those genes relate to the functions, the development, and the flexibility of different parts of the brain;
00:37:37.07 and how those brain systems work together to generate the behavior of an animal, and ultimately, the human.
00:37:43.00 Thank you.

Part 2: Cracking the Circuits for Olfaction: Odors, Neurons, Genes and Behavior

00:00:00.00 Hi, I'm Cori Bargmann,
00:00:03.25 from the Rockefeller University in New York,
00:00:05.29 and the Howard Hughes Medical Institute.
00:00:08.02 And I'm going to talk today about work that we've been doing to try to crack circuits for olfaction,
00:00:13.27 to understand how you go from odors to neurons to genes to behavior.
00:00:19.24 Now, I'm going to talk about this in the context not of the noble human brain,
00:00:24.20 but of the noble brain of the nematode worm, Caenorhabditis elegans.
00:00:28.20 Why would we study a simple animal instead of studying humans?
00:00:31.29 The reason is that the human brain is almost unimaginably complex:
00:00:36.14 it has billions of neurons that are connected to each other by trillions of synapses.
00:00:42.03 By contrast, the nervous system of the nematode worm C. elegans has only 302 neurons
00:00:47.27 that are connected by 7000 synapses, and another 600 or so gap junctions.
00:00:54.15 Now, this much simpler nervous system nonetheless shares many components with the nervous system of a human.
00:01:01.19 So whereas humans have about 25,000 genes,
00:01:04.09 worms have about 20,000 genes,
00:01:06.09 many or which are shared between the species.
00:01:08.20 And when we look at the properties of the nervous system,
00:01:11.01 we find that many features of the nervous system are similar,
00:01:14.22 that worms use similar neurotransmitters, channels, and developmental genes, as humans.
00:01:20.07 Therefore, we think that some of the principles that underlie the function of the brain
00:01:24.08 and the function of brain circuits in behavior will also be similar between simpler animals like the worm
00:01:30.06 and complex animals like ourselves.
00:01:34.17 Now, with C. elegans, we also have, from the work of John White and his colleagues,
00:01:39.06 knowledge of how those 302 neurons communicate with each other, through a wiring diagram.
00:01:45.05 This wiring diagram contains only 6000 or 7000 connections,
00:01:48.26 but that's still too many, as you can see in this illustration,
00:01:52.24 to really understand the flow of information.
00:01:55.05 We need to directly test what the connections do,
00:01:57.28 we need to test what the neurons do, in order to understand behavior.
00:02:03.28 And the way that we try to understand behavior is using the behavior of the entire animal,
00:02:10.29 the functions of individual genes, and the functions of neurons,
00:02:14.18 and relate those to each other vertically, from the level of molecules
00:02:18.23 to the level of the entire organism.
00:02:21.07 Now, the starting point for this set of studies will be the fact that worms respond to odors
00:02:27.15 with robust behavioral responses,
00:02:29.24 that pose a set of questions we can ask about how behavior is generated.
00:02:33.24 So, if you put a lot of worms down in an environment where there's no odor,
00:02:36.27 they'll scatter around.
00:02:38.24 But if you them in an environment where there's a good odor on one side,
00:02:41.25 they'll quickly move to the source of that good odor and accumulate there.
00:02:46.29 Conversely, if you put them in an environment with a bad odor,
00:02:49.06 they'll go as far from it as they possibly can.
00:02:51.25 So we can see attraction, repulsion, or neutral responses in the behavior of the animal.
00:02:57.21 We can then ask: What parts of the worm brain are required for these different kinds of behaviors?
00:03:04.15 And we can ask this question through different kinds of approaches,
00:03:08.22 either loss-of-function approaches or gain-of-function approaches,
00:03:12.01 and both of those converge on the same answer,
00:03:15.03 which is that specific neurons detect odors and initiate behaviors in the animal,
00:03:20.20 and that the neurons that do this are reliably similar from worm to worm.
00:03:25.23 So, one way to determine that is to eliminate the functions of single neurons,
00:03:29.27 which we can do by killing them with a laser microbeam,
00:03:32.13 and when we do that, for example, for this neuron shown here in blue, the AWC neuron,
00:03:37.13 we find that the animals become defective in their ability to chemotax
00:03:40.26 to certain attractive odors and to search for food.
00:03:44.15 Now, if we kill the neuron right next to AWC, this red neuron, ASH,
00:03:48.20 there's no defect in odor chemotaxis and food search.
00:03:51.14 But now instead, there's a defect in nociception
00:03:55.16 and escape behavior that is triggered by noxious compounds that the worm hates.
00:04:00.20 So this tells us these neurons are required for different behaviors.
00:04:04.08 We can complement this loss-of-function analysis by gain-of-function analysis,
00:04:08.19 where we activate these neurons artificially and ask what behaviors the animal generates.
00:04:14.15 And the method that's used to do that currently in neuroscience
00:04:18.07 is to use a molecule called channelrhodopsin.
00:04:21.03 It's a light-activated ion channel from a unicellular organism.
00:04:25.23 The gene for channelrhodopsin can be introduced into different neurons in different animals,
00:04:30.25 and it will then make those neurons responsive to light,
00:04:33.15 so that when you shine light on them, the neurons become active.
00:04:36.15 You can then ask, in this gain-of-function configuration,
00:04:39.20 what happens when you activate one of these neurons?
00:04:42.26 And so for, example, as is shown in this movie here, when you activate the ASH
00:04:47.24 nociceptive neuron that mediates escape behaviors simply by turning a light on
00:04:52.26 and activating channelrhodopsin, the worm generates a reversal.
00:04:57.01 This is an escape behavior associated with a change of direction
00:05:00.16 that's exactly like what would happen if ASH detected one of its normal,
00:05:05.04 noxious stimuli that would also direct an escape behavior.
00:05:09.12 And so we can say here that ASH is both necessary and sufficient for generating escape behaviors.
00:05:18.13 Now, explaining escape behavior is pretty straightforward.
00:05:22.17 Escape behavior is deterministic;
00:05:24.26 that means that, when a worm encounters a noxious substance,
00:05:28.09 as illustrated by this series of panels, every worm generates a reliable response
00:05:33.09 to that noxious substance, in a way that's quite predictable,
00:05:37.08 where it will back up, turn away, and move in a new direction.
00:05:41.04 But when we try to understand chemotaxis behavior, we see that it has different properties.
00:05:46.01 It's a probabilistic behavior,
00:05:48.08 and what I mean by that is that,
00:05:49.29 while all of the worms will eventually reach the odor,
00:05:53.12 they get to the odor by what seems to be an unpredictable path.
00:05:57.00 Every worm seems to follow a different path to reach the odor source.
00:06:01.09 How can we explain this more complex trajectory,
00:06:04.21 which doesn't look like the reflex or deterministic action?
00:06:07.26 What we need is some kind of a model that would explain
00:06:11.00 how animals can approach an odor.
00:06:13.29 And in fact, exactly such a model was developed by Shawn Lockery and colleagues,
00:06:19.05 and what they showed was that worms approach the odor using a strategy
00:06:24.01 called a "biased random walk," which is the same strategy that bacteria use
00:06:29.06 to detect attractive chemicals in their environment.
00:06:32.12 A biased random walk occurs through a fascinating strategy where
00:06:37.19 animals don't point their nose straight up toward the odor like a weather vane;
00:06:42.11 instead, they simply move through their environment,
00:06:45.17 waiting to see whether conditions are changing, and if so,
00:06:51.05 whether they're getting better or worse.
00:06:53.18 And what the animals do is that they turn, changing directions,
00:06:56.29 at some constant rate in constant conditions.
00:06:59.25 But if conditions get better, if the odor increases,
00:07:05.23 then they make fewer turns.
00:07:08.04 If the conditions get worse, if the odor decreases,
00:07:11.12 they make more turns.
00:07:12.27 And the effect of this, is that animals will move in a good direction
00:07:17.00 where odors are increasing for a longer period of time,
00:07:21.04 and they'll move in a bad direction where odors are decreasing
00:07:24.00 for shorter periods of time.
00:07:25.20 And eventually, just changing direction at random,
00:07:28.15 this will lead them to accumulate at the odor through what appears to be a
00:07:32.13 more-or-less random path.
00:07:34.14 So the key feature of this strategy is that the animals aren't detecting the absolute levels of odors,
00:07:40.01 they're detecting the change in an odor level...
00:07:42.27 are things getting better or are things getting worse?
00:07:46.03 They're looking at the change in concentration over time.
00:07:51.05 So, we would like to test this model.
00:07:53.14 How do you go about testing a model like this, about odor concentrations over time?
00:07:58.20 The way you have to test this model is to generate a temporal gradient,
00:08:03.12 an odor environment that changes only over time and not over space,
00:08:08.12 to test the predictions of this particular quantitative model.
00:08:12.13 And the way that this can be done is by generating small chambers
00:08:16.11 in which animals can be exposed to odors flowing past them rapidly,
00:08:20.13 and then examine for their different kinds of behavioral responses.
00:08:24.07 And a chamber to carry out this task was designed by Dirk Albrecht.
00:08:30.05 So, what Dirk did was to find a small environment in which he could provide pulses of odors
00:08:35.20 at a known concentration at a known schedule,
00:08:38.10 and examine the responses of the worms in these environments.
00:08:41.23 And as is seen in the movie here, when you watch worms moving through this chamber,
00:08:46.02 sometimes they move in straight lines, and sometimes they change directions,
00:08:49.11 generating different kinds of turns.
00:08:51.28 Now, this light color here are worms in the absence of an odor.
00:08:55.12 Some of them are turning, some of them are moving in straight lines.
00:08:58.07 When the dark color appears, that will signal the appearance of an attractive odor.
00:09:02.25 When the light colors appears, the odor will disappear.
00:09:05.25 And what you should be able to see is that,
00:09:07.17 when the odor appears, the worms move in long, straight lines,
00:09:11.08 and when the odor disappears, they turn, they change direction.
00:09:15.02 Again, attractive odor... long, straight lines.
00:09:18.28 Disappearance... turning.
00:09:21.13 This is exactly the behavior that is predicted in the biased random walk model:
00:09:26.22 An increase of turning when conditions are getting worse.
00:09:30.14 So here we can see that at a visual level.
00:09:33.05 But in order to understand behaviors, we need to quantify those behaviors,
00:09:37.08 not just look at them qualitatively.
00:09:40.16 And to do that, we can use methods to automatically analyze the turning behaviors
00:09:45.08 using computers to monitor the position of worms over time.
00:09:49.04 We can then assign to each of the worms a description of what it's doing at any particular time:
00:09:54.23 Is it moving forward, here in gray?
00:09:57.02 Is it pausing or reversing, here in black?
00:09:59.24 Or is it generating different kinds of turns, called pirouettes, here in red?
00:10:04.17 This analysis can be done for many hundreds of animals over different kinds of stimulus protocols,
00:10:10.20 leading to the kinds of data shown here, where animals are exposed to pulses of odors in blue,
00:10:17.25 and odor being removed (replaced by buffer) in white.
00:10:21.25 And then here, hundreds of animals are monitored for their behavior in response
00:10:26.04 to that sequence of odor and buffer pulses.
00:10:29.04 Now what you should be able to see is that there's a lot of red and black material in the presence of buffer,
00:10:34.26 but much less when odor is present.
00:10:38.04 These hundreds of traces can then be quantified to generate the one trace underneath,
00:10:42.29 which shows the probability of turning under different conditions.
00:10:47.12 And what you can see is that, when odor is present, as it is here,
00:10:51.08 the probability of turning is quite low, but it's not zero.
00:10:55.04 And when odor is removed, as is shown here,
00:10:57.17 the probability of turning shoots up, but it doesn't go up to 100%...
00:11:02.03 it eventually returns again to the basal probability of turning.
00:11:06.11 So from this we can say a couple of different things:
00:11:08.29 We can confirm the biased random walk model, we can say that, yes,
00:11:12.14 turning rates do change based on odor history,
00:11:16.01 whether odor has been added or removed.
00:11:19.02 And we can also notice that this is indeed a probabilistic behavior,
00:11:23.29 that the probability of turning changes, but it's never 0%, and it's never 100%.
00:11:29.19 To understand behavior, we have to think quantitatively and statistically
00:11:33.28 about what animals are doing at any given time.
00:11:39.17 So, using these kinds of assays and simpler assay that resemble these,
00:11:44.09 it's been possible to map out neurons that are required for odor chemotaxis and food search.
00:11:50.18 I told you that the AWC neuron, an olfactory neuron, is required for odor detection.
00:11:55.23 AWC forms synapses onto three different classes of interneurons,
00:12:00.16 neurons that collect information from a variety of sensory neurons,
00:12:04.23 and these neurons are connected to each other and with a fourth neuron.
00:12:09.04 All four of these neurons, that are one synapse away from the AWC neuron,
00:12:13.26 regulate turning probabilities.
00:12:16.15 Two of them, shown in blue,
00:12:18.15 act to increase the rate of turning when odor is removed, and two of them, show in red,
00:12:24.09 act to decrease the the rate of turning.
00:12:26.14 So they're both positive and negative signals in this circuit that are mediating odor information.
00:12:32.27 Now, once a turn is being generated,
00:12:36.08 the worm has to decide what kind of turn it's going to be.
00:12:39.00 The neurons shown here in gray at the bottom of the slide
00:12:42.02 are neurons that help interpret this turning frequency information and
00:12:45.19 turn it into different kinds of output motor behaviors.
00:12:48.22 I won't talk about those further in this talk.
00:12:51.02 I'll just concentrate on the first step:
00:12:53.08 How is the problem of detecting odor transformed through the neurons
00:12:57.11 that collect this information from the sensory neuron, to regulate turning rates?
00:13:04.28 So, one way to answer that question is to start to get a dynamic picture
00:13:09.18 of what the neurons are doing in response to odors.
00:13:13.10 We want to visualize what's happening in these neurons.
00:13:16.21 So what are the tools we can use to understand when neurons are active?
00:13:20.25 In C. elegans, one of the tools we like to use are genetically encoded calcium indicators.
00:13:27.23 These are fluorescent proteins based on the "green fluorescent protein"
00:13:32.05 that include within them a calcium-binding protein "calmodulin,"
00:13:35.29 as well as a peptide that will bind to calmodulin when calcium is present.
00:13:40.25 Through genetic engineering and biochemical studies,
00:13:43.13 Junichi Nakai and others have generated versions of these proteins that increase fluorescence
00:13:49.06 when they are bound to calcium, and are less fluorescent when they are not bound to calcium.
00:13:53.28 This is useful to us because calcium is a good reporter of when a neuron is active.
00:13:59.20 When neurons are depolarized, they open voltage-gated calcium channels,
00:14:04.07 leading to an increase of calcium within the cell.
00:14:07.03 And therefore, an increase in fluorescence of a protein associated with
00:14:11.07 an increase of calcium will tell you when a neuron is depolarized.
00:14:16.04 To monitor a specific neuron,
00:14:17.27 we then take advantage of the powerful transgenic tools in C. elegans
00:14:22.04 to express this genetically encoded fluorescent protein
00:14:25.02 only in a single kind of neuron of interest,
00:14:27.23 in this case, in the AWC neuron, to ask when that neuron is active.
00:14:35.20 Now there's a third component required to monitor the activity of these neurons,
00:14:39.22 and that is that we need to be able to hold the worm still and
00:14:42.29 deliver odors in precise patterns while monitoring the fluorescence intensity of the AWC neuron.
00:14:50.05 We do that by borrowing a technology back from the engineering,
00:14:54.05 from the silicon chip, industry, into biology, called microfabrication.
00:14:58.23 And we build special worm traps that are worm dimension,
00:15:02.21 that enable us to hold a worm in an optically transparent environment,
00:15:07.23 while restraining it in three dimensions, and then flowing different kinds of fluids
00:15:11.20 past the nose of the worm while monitoring fluorescence intensity.
00:15:15.12 This microfluidic chamber then permits us to combine the genetic tools
00:15:20.00 with chemical tools to monitor neural activity.
00:15:25.13 And that's exactly what's happening in this image here.
00:15:28.17 So this is a single AWC neuron expressing a genetically encoded calcium indicator,
00:15:33.20 and you will see when the movie starts, the neuron starts with a yellow level of fluorescence
00:15:39.05 and a relatively low level of fluorescence in the process of the neuron.
00:15:42.26 Ten seconds into the movie, a switch in odor stimuli will occur, and the neuron will become brighter.
00:15:49.22 The brighter color, the more intense color, the larger white color in the cell body of the neuron over here,
00:15:54.21 all reflect the fact that calcium has gone up, and the neuron has become active.
00:15:59.17 So, indeed, we can see that the AWC neuron responds to odors by changing its activity.
00:16:06.23 But it responds in a way that we did not expect,
00:16:10.06 because the AWC neurons are not activated when odors are presented to the worm.
00:16:15.26 In fact, when we look at the fluorescence intensity and graph it in the presence of odor,
00:16:20.05 it is, if anything, a little less intense than it would have been in the absence of odor.
00:16:26.27 Instead, the AWC neurons become active when odor is removed.
00:16:31.21 This leads to a large increase in the fluorescence intensity,
00:16:34.21 indicating depolarization and the presence of calcium.
00:16:38.08 So these neurons seem to work in reverse.
00:16:41.13 They are inhibited by odors, their natural stimuli.
00:16:44.28 They are active when odors are removed.
00:16:47.24 And I just want to remind you that the worm has to generate a behavior when odor is removed.
00:16:53.02 When odor is removed, the worm is going to start turning.
00:16:56.00 So the activity of the neuron is correlated with the behavioral output, not with the input stimulus.
00:17:05.18 So we can now say something about this first neuron that interacts with odors.
00:17:10.25 How does it communicate with the target neurons that then convert this information into behavior?
00:17:17.10 The way that we study this is by studying the process of synaptic transmission.
00:17:21.15 Neurons connect to each other at specialized structures called synapses,
00:17:25.08 where a presynaptic neuron, the upstream neuron, in this case AWC,
00:17:29.28 will release vesicles filled with a neurotransmitter, and these neurotransmitters
00:17:33.24 will interact with receptors on the postsynaptic neuron, here shown in gray.
00:17:39.01 One kind of neurotransmitter that neurons release is glutamate, an amino acid,
00:17:45.25 and glutamate is packaged into special synaptic vesicles by a molecule called the
00:17:49.25 "vesicular glutamate transporter," or EAT-4 in C. elegans.
00:17:54.25 We can use this EAT-4 molecule to probe the action of synapses in the AWC neuron.
00:18:02.27 We can do that by using mutants in EAT-4 to inactivate the transporter
00:18:07.26 and therefore the ability of AWC to release glutamate.
00:18:11.19 And we can ask then,
00:18:13.09 what kinds of behavior can the animal generate in the absence of this glutamate transmitter?
00:18:18.15 And remember that turning is a reflection of the response to odor removal,
00:18:23.22 an important component of chemotaxis behavior, and that we can quantify this.
00:18:26.27 So a high level here of "1" is a high level of turning.
00:18:31.13 In red here is an eat-4 mutant.
00:18:33.15 The eat-4 mutant does not turn efficiently when odor is removed,
00:18:37.21 indicating to us that glutamate is required as a neurotransmitter for this turning behavior.
00:18:43.04 And when we restore EAT-4 just in the AWC neurons using a specific transgene,
00:18:48.22 we restore most of the turning behavior.
00:18:51.01 And so we can say that glutamate from AWC promotes turning.
00:18:57.25 So we now have insight into the first step of how AWC communicates with its target:
00:19:03.10 It uses EAT-4 to package glutamate into vesicles, it releases glutamate,
00:19:08.06 and this must then act on target neurons.
00:19:10.23 How does it communicate with the target neurons?
00:19:12.26 How does it communicate with these three different neurons with which it forms connections?
00:19:17.00 Well, it has to do that through glutamate receptors,
00:19:20.04 proteins that are expressed on the target neurons that enable them to detect the released glutamate.
00:19:25.11 And we found that there are two classes of glutamate receptors
00:19:28.22 that are important for this particular behavior.
00:19:31.29 There's a glutamate-gated cation channel; it's an excitatory receptor called GLR-1.
00:19:38.01 And there's also a glutamate-gated chloride channel,
00:19:41.05 an anion channel that is an inhibitory receptor called GLC-3.
00:19:45.14 These two glutamate receptors,
00:19:47.11 which can generate two different kinds of responses in target neurons,
00:19:50.20 are important for AWC's communcation with its targets.
00:19:56.26 We can demonstrate that both through quantitative behavioral assays
00:20:02.18 and through direct observation of the activity of target neurons,
00:20:06.18 which we do using genetically encoded calcium indicators.
00:20:10.15 Now, instead of expressing them in AWC, we express them in downstream neurons,
00:20:15.24 such as AIB.
00:20:17.18 AIB is one of the neurons that receives synapses from AWC,
00:20:21.16 and we see that AIB, like AWC, responds to odor removal by an increase in calcium.
00:20:29.06 This response disappears if the AWC neuron is killed,
00:20:33.21 and it also disappears in an animal that lacks the glutamate receptor GLR-1.
00:20:38.17 GLR-1 is required in AIB for AIB to sense the glutamate signal from AWC.
00:20:46.09 This excitatory glutamate receptor transmits an excitatory signal from sensory neuron to interneuron.
00:20:56.03 Next, we looked at the AIA and AIY interneurons.
00:21:01.09 These neurons also respond to odors,
00:21:04.05 but these neurons respond oppositely to AWC.
00:21:08.12 AIA and AIY respond with an increase in calcium to odor addition,
00:21:13.22 there's been a change in the sign of the signal between the sensory neuron and the interneuron.
00:21:18.21 They don't respond to odor removal.
00:21:21.19 Now this response to odor addition still requires AWC,
00:21:25.19 and it requires a glutamate receptor.
00:21:28.04 It requires GLC-3, the glutamate-gated chloride channel.
00:21:32.21 This inhibitory receptor serves to transmit a signal from an excited AWC
00:21:38.18 into a signal that will inhibit the downstream neurons,
00:21:42.06 so the downstream neurons AIA and AIY respond oppositely
00:21:47.00 to odors than the upstream neuron AWC.
00:21:52.24 So putting this information together, here on the left,
00:21:56.09 we can assemble a C. elegans odor circuit.
00:21:59.26 We can say that attractive odors inhibit the AWC olfactory neurons,
00:22:04.16 that the AWC olfactory neurons now release glutamate
00:22:08.03 onto two classes of downstream neurons through two classes of receptors.
00:22:12.16 They excite one class of neurons, the AIB neurons,
00:22:15.25 through an excitatory glutamate receptor.
00:22:18.14 They inhibit other classes of neurons, AIA and AIY neurons,
00:22:22.17 through an inhibitory glutamate receptor.
00:22:25.15 By splitting the information in this way,
00:22:27.15 the AWC neurons have now transformed information into two streams:
00:22:32.00 One signals the appearance of odor, an "odor ON" response;
00:22:35.17 the second stream signals the disappearance of odor, an "odor OFF" response.
00:22:40.26 Remarkably, when we examine this circuit,
00:22:43.12 it looks similar to another sensory circuit that's been well characterized,
00:22:47.14 and that is the circuit that is used to collect light in the vertebrate retina,
00:22:51.18 in your own eye.
00:22:53.14 So in your eye, light is collected by the rod and cone photoreceptors.
00:22:58.15 Rods and cones are active in the dark;
00:23:00.29 they are inhibited by light, their natural stimulus,
00:23:04.03 just as AWC neurons are inhibited by odors.
00:23:08.12 Rods and cones release glutamate to communicate with their targets,
00:23:12.04 and they have two major classes of target neurons.
00:23:14.28 The target neurons are called bipolar cells.
00:23:17.24 One connection is through an excitatory glutamate receptor, and therefore,
00:23:22.24 these neurons have the same pattern of activity as the photoreceptors.
00:23:27.01 They're what are called "OFF" bipolar cells; they signal when lights go off.
00:23:31.26 The other class of neurons are connected through inhibitory glutamate receptors.
00:23:36.01 Therefore, these neurons are called "ON" bipolar cells; they signal when lights come on.
00:23:43.05 So comparing these different neural circuits,
00:23:45.19 we can say that in a worm olfactory system and in a vertebrate visual system,
00:23:50.23 some of the same principles are used to process sensory information.
00:23:55.02 Differential signaling of the appearance and the disappearance of a stimulus,
00:23:59.16 differential signaling through different classes of glutamate receptors,
00:24:03.01 to split information through different circuits.
00:24:05.22 This kind of insight helps convince us that there may be principles
00:24:09.10 for neural circuits that apply across different systems,
00:24:12.16 that will help us understand information processing.
00:24:16.01 What I've told you is that AWC communicates with three downstream neurons,
00:24:20.19 using glutamate to send complex information about the input stimulus
00:24:24.25 to different downstream sets.
00:24:28.23 In addition, AWC has another way of communicating with its targets,
00:24:33.04 because AWC doesn't just release glutamate,
00:24:35.23 it releases a second transmitter, a neuropeptide neurotransmitter called NLP-1.
00:24:41.15 NLP-1 is related to neuropeptides called buccalin in other animals,
00:24:46.02 and NLP-1 signals through a G protein-coupled receptor, called NPR-11.
00:24:52.04 NPR-11 is expressed on some of the downstream neurons from AWC,
00:24:57.18 but not all, including the AIA neurons.
00:25:01.09 So glutamate is released from AWC onto several neurons, and in addition,
00:25:05.29 a neuropeptide is released from AWC onto a subset of those neurons.
00:25:12.29 What is the function of NLP-1?
00:25:15.18 We can ask that by examining animals that are mutant for the NLP-1 neuropeptide
00:25:21.00 or mutant for its receptor,
00:25:22.27 and then comparing their behaviors to the behaviors of wild-type animals.
00:25:27.13 And what we find is that the function of NLP-1 is to antagonize
00:25:32.17 the glutamate signal from the same AWC neuron.
00:25:36.17 So, this is illustrated here in the quantitative turning behaviors that measure AWC output.
00:25:42.11 So a wild-type animal, shown here in white,
00:25:44.29 will turn about once a minute in response to odor removal.
00:25:48.22 These turns are absolutely dependent on the glutamate signal from AWC.
00:25:52.29 There are simply no turns when AWC glutamate is absent, as shown by this mutant.
00:26:00.06 But when we look at the nlp-1 mutant, we see that there are turns.
00:26:03.25 In fact, there are more turns than there would be in a wild-type animal.
00:26:07.21 So AWC is both sending a signal to stimulate turning (the glutamate signal),
00:26:12.20 and it's sending a second signal that inhibits turning (the NLP-1 signal).
00:26:17.23 It's limiting its own output by generating these two antagonistic signals.
00:26:24.08 We next asked how this signal interacts with the circuit
00:26:29.12 to affect the activity of different neurons.
00:26:32.20 And here there was a large surprise.
00:26:35.14 So we examined the nlp-1 mutant, and mutants in its receptor NPR-11,
00:26:40.17 to see where activity in the circuit was changed compared to the activity of wild-type animals.
00:26:45.25 We saw changes in the activity of the neurons not just in downstream target neurons;
00:26:51.16 we saw changes in AWC itself.
00:26:54.23 The olfactory neuron responds differently to odors
00:26:58.01 depending on the activity of this peptide system.
00:27:01.21 So we can see this here in calcium imaging experiments showing
00:27:05.08 the response of AWC neurons to odor removal.
00:27:08.23 In wild-type, they show a sharp, short response.
00:27:12.06 In animals that lack the NLP-1 peptide or its receptors,
00:27:16.27 we instead see a longer-lasting response and repeated responses,
00:27:20.21 indicating that the AWC neuron is staying active for longer after odor has been removed.
00:27:28.17 Now, AWC is releasing this signal, the receptor for this signal in on a downstream neuron...
00:27:34.23 How does that information come back to AWC?
00:27:38.15 The answer is that the downstream neuron releases another signal, a feedback signal,
00:27:44.20 that is an insulin-like peptide, that returns to the AWC neuron to modify its activity.
00:27:50.26 So, a signal from AWC talks to a target neuron,
00:27:54.07 the target neuron then sends a signal back to AWC,
00:27:57.13 and again, the use of that signal limits the activity of the AWC neuron.
00:28:02.12 The feedback keeps AWC from generating these longer
00:28:06.03 or repetitive responses to odor removal.
00:28:11.29 So, it seems curious that a neuron would be generating
00:28:14.21 both positive and negative responses.
00:28:16.29 What could be the purpose of generating a negative feedback signal?
00:28:21.13 To understand this, you should understand that,
00:28:24.02 in animals, odor preference is modified by its experience with odor.
00:28:28.10 And this can be illustrated in a variety of ways,
00:28:31.15 but one simple way is that, when animals are exposed to odor in the absence of food,
00:28:35.25 they slowly adapt to the odor, so that they are no longer attracted to it.
00:28:40.15 This causes animals to prefer new odors,
00:28:43.18 or odors that have been paired with food,
00:28:45.14 to odors that have been seen in the absence of food,
00:28:49.02 and it represents an obvious good behavioral strategy for finding odors
00:28:53.11 that might be predictive of food in the future.
00:28:56.00 This can be quantified here, where the attraction to odor, shown here in black,
00:28:59.22 drops after 60 minutes of seeing an odor without food,
00:29:03.04 and drops even further after two hours of seeing the odor without food.
00:29:09.03 This change in the odor-dependent activity requires the neuropeptide feedback loop
00:29:16.10 that limits AWC activity.
00:29:19.06 If you remove either NLP-1 or its receptor NPR-11
00:29:24.13 or the feedback signal INS-1 that converts that information back to AWC,
00:29:29.19 then animals that have been exposed to odor, adapted animals, as shown here,
00:29:34.05 continue to respond to odor even after a long time of pairing of odor at the absence of food,
00:29:40.07 where wild-type animals would lose their response.
00:29:44.09 Adaptation requires the function of NLP-1 in the AWC neurons
00:29:49.22 and the function of NPR-11 and of INS-1 (the feedback signal) in the AIA neurons.
00:29:56.04 And so we can map this particular negative feedback signal to a particular
00:30:01.09 negative feedback that must occur to drive a useful olfactory behavior:
00:30:06.10 olfactory adaptation.
00:30:09.14 The activity of this feedback loop is observed not only at the behavioral level,
00:30:13.23 but also at the level of neuronal responses,
00:30:17.01 because when we examine the activity of AWC neurons after a long time of exposure to high odor,
00:30:23.06 as shown here in black, they simply stop responding to the odor
00:30:27.17 if the odor was present in the absence of food.
00:30:30.26 And this suppression of their response is defective in animals
00:30:36.05 that lack the neuropeptide feedback signal, as shown here in red,
00:30:39.29 which continue to respond to the odor even when it no longer predicts the presence of food.
00:30:50.07 So the conclusion of this part of the talk is that neuropeptide feedback,
00:30:55.04 superimposed on the basic function of the circuit, shapes sensory dynamics:
00:31:01.06 That sensory neurons like AWC respond to odors not in one way,
00:31:05.17 but in different ways depending on the activity of a feedback circuit;
00:31:09.20 that if that feedback circuit is lost, the sensory neurons respond for longer and with multiple stimuli;
00:31:16.14 that if the feedback circuit is present, they respond with a short stimulus;
00:31:20.07 and that if the feedback circuit is strongly activated through olfactory adaptation,
00:31:24.25 the sensory neurons stop responding,
00:31:26.23 allowing the animals to suppress the response to that odor, and to respond to new odors.
00:31:34.08 And the conclusion of this talk is that circuits change over time, that circuits are not fixed,
00:31:41.09 that they actively shape and transform sensory information.
00:31:45.05 They don't just passively receive that information.
00:31:48.03 And furthermore, circuits change their own properties
00:31:51.05 based on sensory information in real time.
00:31:55.12 This process, this dynamic and active interpretation of information,
00:32:00.18 allows circuits to perform complex computations and calculations.
00:32:05.14 If you take just what I told you about this small circuit of just a few C. elegans neurons,
00:32:11.06 you can realize that, if you multiply that by the billions of neurons in a human brain,
00:32:15.21 it can start to explain why a human brain can generate an
00:32:19.17 infinite number of perceptions, memories, and behaviors.
00:32:23.18 Thank you.

Videos in this Talk

Part 1: Genes, the Brain and Behavior
Audience:
- Student
- Researcher
- Educators of H. School / Intro Undergrad
- Educators of Adv. Undergrad / Grad
Part 2: Cracking the Circuits for Olfaction: Odors, Neurons, Genes and Behavior
Audience:
- Student
- Researcher
- Educators of H. School / Intro Undergrad
- Educators of Adv. Undergrad / Grad

Speaker: Cori Bargmann

Total Duration: 1:10:20

Recorded: November 2011

Educator Resources for this Talk

All Talks in Neuroscience

Talk Overview

In her first talk, Cori Bargmann explains how individual genes can affect the brain and behavior. Humans are complex creatures, but as many as 99% of our genes are shared with simpler organisms. By focusing on the genes for a family of proteins found in many organisms, the G protein-coupled receptors, Bargmann illustrates that mutations in a single gene can cause significant behavioral changes in organisms as diverse as nematodes, dogs and humans. In Part 2, Bargmann presents work from her own lab in which the olfactory system in C. elegans was used to dissect the role of genes on behavior. She shows us how it was possible to map the neuronal circuits that modulate worm behavior in response to different odors.

Speaker Bio

Cori Bargmann

Cori Bargmann received her B.S. in biochemistry from the University of Georgia and her Ph.D. from the Massachusetts Institute of Technology. Bargmann began her studies on C. elegans during her post-doc with Bob Horvitz, also at MIT. She joined the University of California, San Francisco as an assistant professor in 1991, and moved to the… Continue Reading