The lethality of loneliness
Emotional isolation is ranked as high a risk factor for mortality as smoking. A partial list of the physical diseases thought to be caused or exacerbated by loneliness would include Alzheimer’s, obesity, diabetes, high blood pressure, heart disease, neurodegenerative diseases, and even cancer—tumors can metastasize faster in lonely people.
Loneliness, she said—and this will surprise no one—is the want of intimacy…They insist that loneliness must be seen as an interior, subjective experience, not an external, objective condition. Loneliness “is not synonymous with being alone, nor does being with others guarantee protection from feelings of loneliness,” writes John Cacioppo, the leading psychologist on the subject. Cacioppo privileges the emotion over the social fact because—remarkably—he’s sure that it’s the feeling that wreaks havoc on the body and brain…Another school of thought insists that loneliness is a failure of social networks. The lonely get sicker than the non-lonely, because they don’t have people to take care of them; they don’t have social support.
A key part of feeling lonely is feeling rejected, and that, it turns out, is the most damaging part.
As expected, he found the students with bodily symptoms of distress (poor sleep, high cortisol) were not the ones with too few acquaintances, but the ones who were unhappy about not having made close friends. These students also had higher than normal vascular resistance, which is caused by the arteries narrowing as their tissue becomes inflamed. High vascular resistance contributes to high blood pressure; it makes the heart work harder to pump blood and wears out the blood vessels. If it goes on for a long time, it can morph into heart disease. While Cole discovered that loneliness could hasten death in sick people, Cacioppo showed that it could make well people sick—and through the same method: by putting the body in fight-or-flight mode.
The public will never tire of the nature versus nurture debate but here’s a hint: the answer in biology is always both. But if you’ve ever known any twins, you know they can have quite different personalities which, you would think, are attributable to differences in nurture of one sort or another. To understand this better, some scientists did what scientists like to do which is trap some mice in a little mouse palace and watched how they behaved. These mice were isogenic so there were no genetic differences (excepting, of course, what are probably trivial mutations and some hopefully minimal epigenetic influences).
Now the mouse palace is a wonderful place but there’s not really a lot to do there beyond roaming about, exploring their environment. But not every mouse explores their environment in the same way: some mice like to explore the whole thing, some like to stay in just a few places where they are comfortable. This alone suggests that the environment has a strong impact on behavior, over and above genetics. But they also point to two other facts that they find: first, that over time the variance across the population in this exploratory difference increases. Second, more neurons are born in the hippocampus, the area related to spatial maps and learning, in the animals that roam more than in the animals that stay put.
Now although this paper is pretty cool just for Mouse Mansion (it’s Big Brother: Mice!), there’s a lot to quibble with. They never normalize the roaming variance by the roaming mean so we don’t really know that the variability is increasing. We don’t know whether neurogenesis is increasing more in the animals that increase their roaming more. And even if they did, it’s totally unsurprising that there would be more neurogenesis in the animals that explored more: because that’s just what we think neurogenesis is for! Remembering more locations! Further, from the first moment that they are recording from – 20 days (after birth ?) – the animals that explore the least continue to explore the least, and the animals that explore the most continue to explore the most, but everyone explores more as they get older. So whatever induced most of the variability happened before the behavior was recorded.
We already know a lot about how exploratory behavior arises, and my guess is if you assayed the dopamine receptor expression level, you’d find the differences that you’re looking for to explain the behavior. My naive guess as to what explains the difference is that it is mostly social – the authors don’t really demonstrate any effects of exploratory learning. We know that mice have social structure, and social structure affects serotonin and dopamine levels which in turn affect exploratory behavior. Now I don’t know if they looked at any type of social information in the Mouse Mansion, but I’d bet that the results of social play and social behavior prior to the start of the study are what creates the difference. The fact that a few weeks of social play can change your behavior for the rest of your life? Now that would be interesting.
But then, you don’t have to take my word for it.
References
Freund, J., Brandmaier, A., Lewejohann, L., Kirste, I., Kritzler, M., Kruger, A., Sachser, N., Lindenberger, U., & Kempermann, G. (2013). Emergence of Individuality in Genetically Identical Mice Science, 340 (6133), 756-759 DOI: 10.1126/science.1235294
The cosmopolitan ape
Peony had arthritis and was very old, so she could barely move. She would try to climb into a climbing frame where a bunch of chimps were sitting and grooming each other. She wanted to join them, but she could barely get in there. The younger females would walk up to her, put their hands on her behind, and start pushing until she was up there with the rest. We’ve also seen cases where she started walking towards a water faucet, but, since it’s a very large enclosure and she walked with so much difficulty, a younger female would run ahead of her, take water in her own mouth, walk back to Peony, and then spit the water into her mouth so she wouldn’t need to walk all the way to the faucet. The acts of kindness made us interested in testing for altruistic behavior more systematically because the literature has claimed only humans care about others, that ifprimates are altruistic, it’s only to get favors in return.
…I don’t think primates have religions, but they may have certain superstitions. For example, if a thunderstorm comes through with an enormous amount of noise and rain, male chimpanzees will put their hands up and start walking around bipedally, in a dancing sort of fashion. It’s called a rain dance and it has been observed with chimpanzees approaching a waterfall. We really don’t know why they do it. Are they impressed by what happens? Do they think they can stop it? Of course, that would be superstition. Are they somehow in awe of nature? They also react to death. We see that primates are very strongly affected by the death of others. They will not eat for days after one of their group members has died.
Go read about the cosmopolitan ape.
The young and the restless
It struck me recently that one of the key differences between economists and neuroscientists studying decision-making is their interest in dynamics. Economists seem more interested in explaining how behavior operates (or should operate) on average whereas neuroscientists would like to explain trial-to-trial variability. Decisions are rarely made just once in a lifetime, but are instead made repeatedly. Any behaviorist would instantly tell you that this means that there will be a learning component, something that I hardly see in the economic decision-making literature (feel free to correct me if this is wrong).
In many of these repeated decisions, people are not simply making a decision in a vacuum but are responding to the actions of others. The decision must then be balanced by their prior beliefs, the results of recent decisions, and their predictions of how other people will act. All of this can be incorporated into a reinforcement learning (RL) paradigm, where the expected value of any action is a combination of classical RL – where every payoff suggests future payoffs, and every loss suggests future losses – as well as a ‘mentalizing’ component that predicts how the opponent is likely to act, and how the opponent will react. By fitting the responses of different brain regions to this type of model, one can get a sense of what each region is (kind of) doing. One region that instantly pops out is the medial prefrontal cortex (mPFC): this region is highly correlated with the prediction of other people’s behavior.
I once took a behavioral economics class in which the professor pointed out that deviations from rational behavior are only important if they translate to something in aggregate. In other words, who cares if just a few people have abnormal mPFC function. In a large population you won’t notice them. But in fact there is a very large group of people with degraded mPFC: the elderly. 13 percent of the US is over the age of 65, and this group is known to have significant loss of volume in mPFC. The prediction, then, would be that older individuals would be less inclined to take into account the behavior of other individuals when making decisions.
To test how they will act, we can take the experimental game the “Patent Race”. In this game, two players are selected from a pool to compete for a prize. They are each given either a large five credit or a small four credit endowment, and are asked to “invest” some portion of that. They then get to keep whatever is left over, and the person who “invested” the most wins ten extra credits.
Cumulative distribution plots of how influential other individual’s behavior is in determining one’s own behavior. Blue represents young adults and purple-dashed represents the elderly.
There does exist a Nash equilibria to this game, and young adults will play the Nash equilibria exactly. Old adults, on the other hand, play a significantly different strategy. What is more interesting, though, is half of elderly adults behave as if they did not care at all about the strategy of the other player. In other words, they are making decisions using a pure reinforcement learning strategy where they only cared about payoffs, not about how the other player was going to act. In contrast, no young adults played like this: they all took into account the strategy that the other player would use.
References
Hampton, A., Bossaerts, P., & O’Doherty, J. (2008). Neural correlates of mentalizing-related computations during strategic interactions in humans Proceedings of the National Academy of Sciences, 105 (18), 6741-6746 DOI: 10.1073/pnas.0711099105
Zhu, L., Walsh, D., & Hsu, M. (2012). Neuroeconomic Measures of Social Decision-Making Across the Lifespan Frontiers in Neuroscience, 6 DOI: 10.3389/fnins.2012.00128
Economics of Social Status
In economic terms, for a good to function as money it must serve three related purposes:
- A medium of exchange,
- A store of value, and
- A unit of account.
We’ve already discussed how status functions as a medium of exchange. Because it’s so fluid, it can be used to price favors and other goods at relatively fine resolutions, and it facilitates transactions that wouldn’t otherwise be able to occur. Negotiating with status beats the hell out of bartering — i.e., trading one specific good for another — thereby allowing smoother, more efficient economies to develop.
Certain goods – money, nice cars – are only useful insofar as they contribute to first-order goods: food, water, reproduction. Does social status count as a first- or second- order good? While it doesn’t keep us alive, we are social creatures that crave and need social attention. Consider what happens to socially isolated individuals, especially those in prison. Go read about the economics of social status.
Jumping off of bridges
No man is an island, entire of itself. Although we like to think of our decisions occurring in a vacuum, in reality we’re bombarded with information on how other people are deciding all the time. It would be shocking if our decisions weren’t influenced by the behavior of other people – and, obviously, a wide range of studies indicate that we are (sociology).
In nature, too, the behavior of animals is dependent on what they see other animals doing. Think of fish swimming through schools and schools of other fish. To the right it sees a flash of a fin: is it a predatory fish? Or a friendly fish? If it’s a predator and you misidentify it you’ve made a big mistake; but misidentify a friendly fish as a predator and you’ve just wasted a bunch of energy – and you maybe you’ve lost a friend.
You can improve your identification of a predator – or of anything really – just by listening to the crowd. If your friends are looking out for the same things that you are, you should make your decision based on what the majority of your friends think (quorum sensing). Not only will you make more true positive decisions, you’ll also make fewer false positive decisions: you become more perceptive as a whole.
Humans do this, too. Just sit a bunch of people together in a room and force them to identify 
whether a short movie clip has a predator in it or not. When they are told what percent of other people think they’ve seen a predator, they will do much better than if they just decide on their own information alone. Even having just one other person help to you out will have a dramatic impact. People don’t go with a simple majority opinion, rather, they base their decision on how reliable the group has been. When the group has been more reliable in the past – when it has had more true positives – then more of the group needs to agree in order for someone to be swayed in their decision (see figure).
What is most interesting about this to me is how trivial it would to implement in a spiking neural network model. Divisive normalization (or gain control) is a common feature of neural networks: neural activity isn’t really the sum of its inputs, but is divided by a factor relating to the total stimulation. In other words, if there were a very strong input stimulus (say, a lot of social input) then the neural response would relate to the fraction or variation in that input. Basically, quorum sensing. And using group reliability to determine your quorum threshold? It just reeks of reinforcement learning.
As I’ve been reading papers over the last year, attempting to become a ‘neuroecologist’, I’ve been trying to keep in mind how social decisions might be built into the brain. This paper is a great example of how ideas in ecology might provide straightforward input that can advance neuroscience.
References
Wolf, M., Kurvers, R., Ward, A., Krause, S., & Krause, J. (2013). Accurate decisions in an uncertain world: collective cognition increases true positives while decreasing false positives Proceedings of the Royal Society B: Biological Sciences, 280 (1756), 20122777-20122777 DOI: 10.1098/rspb.2012.2777
Humans are not the only copycats…
Both sets of newcomers seemed to follow social cues when selecting their snacks. Baby monkeys ate the same colour maize as their mothers. Seven of the ten males that migrated from one colour culture to another adopted the local colour preference the first time that they ate any maize. The trend was even stronger when they first fed with no higher-ranking monkey around, with nine of the ten males choosing the locally preferred variety. The only immigrant to buck this trend was a monkey who assumed the top rank in his new group as soon as he got there — and he may not have given a fig what anyone else ate.
“The take-home message is that social learning — learning from others rather than through individual trial and error — is a more potent force in shaping wild animals’ behaviour than has been recognized so far,” says Andrew Whiten, an evolutionary and developmental psychologist at St Andrews and co-author of the paper.
Humans are not the only copycats. (More from Ed Yong). With the key question being: what are the neural mechanisms that distinguish between social learning and ___ learning?
