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Letters to the editors

Vol. 6, NO. 1 / June 2021

To the editors:

Brains are energetically expensive organs, and many organisms do very well without them. But bigger brains lead to more intelligence, as they allow a species to store and manage more information. Then why don’t more animals have big brains? One reason is the metabolic energy cost. Muscle tissue requires less than 5% of the energy of an equivalent amount of brain tissue. Because a bigger brain needs to pay its energy bills, most animals have the smallest brains that still allow them to find food, avoid predators, and outcompete rivals for mating opportunities. But some animals do have outsized brains. Among them are, notably, some types of whales and dolphins, octopuses, and, of course, humans.1 The human brain, for example, tripled in size in the last few million years and is now three times larger than a chimpanzee brain. Encephalization—the evolutionary increase in the complexity or size of brains—is a biological puzzle with a long list of hypotheses proposed to explain it. Each hypothesis has emphasized a different set of selective pressures, ranging from features of the ecology to climate change to physiology to sociality.2

One of the most popular of these hypotheses is the social brain hypothesis, which began with the observation that brain size and group size were correlated in apes and monkeys.3 The explanation proposed for this correlation was that living in larger groups required far greater behavioral complexity. Skills such as tricking rivals and tracking group members became far more demanding in larger groups, leading to the evolution of larger brains. This simple correlation between brain size and group size found in primates did not hold in other taxa.4 In birds, brain size was correlated with other social features such as parenting and pair-bonding.5 And so the social brain hypothesis evolved to account for more general forms of social cognition. In his essay, Kieran Fox discusses the application of the social brain hypothesis as it might apply to whales and dolphins (Cetacea), building on recent work by himself and collaborators Michael Muthukrishna and Susanne Shultz. As part of their research, Fox, Muthukrishna, and Shultz surveyed the published cetacean literature, compiled a large database, and analyzed it. They discovered that in cetaceans, socially tight-knit groups predicted the largest brains and the largest behavioral repertoires, i.e., sets of sophisticated behaviors such as complex vocalizations, group hunting techniques, and helping each other care for their young.6 This pattern, particularly the relationship between brains and behavioral repertoire is also consistent with another more general explanation for the evolution of large brains—the cultural brain hypothesis.7

The cultural brain hypothesis shifts the emphasis from social complexity to learning. Brains are not just for social living. In more general terms, they are for learning, storing, managing, and using information. For a social animal, that information might include the kind of tricking and tracking behaviors described by the social brain hypothesis. But for an asocial animal, it might only include what the animal discovers on its own. Because the cultural brain hypothesis predicts two main pathways for evolving bigger brains—social and asocial—it encompasses the social brain hypothesis, but might also explain the evolution of brains and intelligence in less social animals. It might, for example, explain the intelligence of cephalopods, with their soft, tentacled bodies, distributed brains, and short, solitary lives.8

The Cultural Brain Hypothesis

The cultural brain hypothesis begins with three key assumptions:

  1. Bigger brains can store and manage more information.
  2. Bigger brains are more metabolically costly than smaller brains.
  3. Storing and managing more information increases survival.

These assumptions are built into a mathematical and a computational model, which together reveal conditions that may lead to the evolution of bigger brains. The models predict testable relationships between brains and behavioral repertoire, group size, reliance on learning from others rather than individually, time spent learning, and methods of learning. These models predict two pathways to bigger brains: a pathway reliant on trial-and-error learning individually and a pathway reliant on social learning from other members of a group. In their paper on the cultural brain hypothesis, Muthukrishna et al. test these predictions using data from primates.9 The predictions fit well.

According to the cultural brain hypothesis, the correlation between brain size and group size, along with other measures of sociality, is not simply a direct result of brains adapting to social living. Instead, larger brains increase the adaptive behavioral repertoire, which in turn can increase group size as more individuals survive. For social animals, these larger groups offer more opportunities for social learning, which increases both the behavioral repertoire and brain size, strengthening these relationships. And so, we might expect a strong relationship between brain size and sociality in the most social animals, including primates and cetaceans, but a weaker to nonexistent relationship among asocial animals, including cephalopods. The cultural brain hypothesis also predicts other relationships. Among social animals, bigger brains will be accompanied by a larger behavioral repertoire, greater reliance on social learning, and more time to learn manifested as a longer juvenile period.

The cultural brain hypothesis generalizes other explanations, including the social brain hypothesis, and hypotheses based on physiology and ecology.10 Brains are not just adapting to a changing ecology, they adapt to how much energy is available or potentially available with the right behavioral innovation. The size of a species’ brain matches the amount of knowledge that the animal can acquire and how many calories that knowledge can unlock in a particular ecology.

In comparison to other species, humans represent an extreme example. The complexity seen in the human brain is the result of a runaway positive feedback loop: the cumulative cultural brain hypothesis. Within the cultural brain hypothesis, a narrow set of conditions can lead to an autocatalytic takeoff that increases brain size and group size. Reliance on social learning and social information is also increased, as is the species’ broader cultural and behavioral repertoire.11 This uniquely human pathway has led to

  • sophisticated learning biases to select the right moments and models to learn from;12
  • complex socio-cognitive abilities such as theory of mind and gaze-following for improved accuracy and efficiency in transmitting information;
  • cumulative cultural learning, whereby innovations of the previous generation can be built upon by the next generation;
  • and adolescence, an unusual cultural juvenile period between when an individual can reproduce and when it actually does, thus delaying reproduction to allow for more time to learn.13

The cultural brain hypothesis and cumulative brain hypothesis seat humans within the animal world but also account for our peculiarities and unusual evolutionary trajectory. The cultural brain hypothesis also reveals a second, as yet untested, pathway to bigger brains, a pathway that may help explain the curious case of the cephalopods—a pathway through asocial learning.

The Asocial Path

In asocial animals, the cultural brain hypothesis predicts that the relationship between brain size and sociality is weak or nonexistent. The model also predicts that for asocial animals, maturity is hastened and the juvenile period quickly completed to move from exploring to exploiting knowledge. Learning by oneself is less efficient than learning from others and so the return on time spent learning is lower for asocial animals.14 These relationships have not yet been tested but may help resolve otherwise puzzling findings.

African mole rats (Bathyergidae) are an ideal subject for investigating the relationship between social organization and brain size. These species all live in similar ecologies, but range from strictly solitary examples to agglomerations living in practically eusocial groups that are tightly knit by genetic kinship. In African mole rats, the larger brains are found among the solitary species.15 These larger brains may be an adaptation to the asocial learning pathway, which can drive up brain size as a result of the pressure to immediately exploit information acquired through trial-and-error learning.16 Current analyses of African mole rats do not, to our knowledge, include life-history data. The crucial prediction that larger-brained asocial mole rats have relatively shorter juvenile periods than the social species therefore remains untested.

Research on the evolution of brains and intelligence has tended to focus on social species. This may be explained by the fact that sociality is so crucial for our own species. The social cetaceans are an example of this emphasis. Compared to primates, cetaceans offer a stronger test in that they live in a strange and alien underwater world and are evolutionarily distant; our last common ancestor lived around 85 to 100 million years ago. But cetaceans are still mammals with centralized nervous systems and a common mammalian body morphology. In comparison to cephalopods, for example, cetaceans are practically our cousins. Our last common ancestor with cephalopods lived over 500 million years ago, making them truly aliens in our midst. The next step toward a unifying theory of brain evolution is a test with such an asocial, evolutionarily distant taxa.

Cephalopods: An Evolutionary Enigma

Many cephalopod species live solitary lives, except when aggregating for feeding and mating. A general view holds that octopuses are the least social cephalopod and that squids are the most social, with cuttlefish being somewhere in between. Cannibalism is widespread in many cephalopod species, providing yet another obstacle for the emergence of stable social interactions.17 Many cephalopods live short lives, spanning perhaps a couple of years, and are semelparous—they die more or less immediately after reproduction. Eggs of some species are left drifting on ocean currents to hatch in the open ocean or settle on the seafloor, but even in brooding species, the brooding parent often perishes right after the eggs have hatched. These features of cephalopod life-history leave little opportunity, if any, for intergenerational social learning and the transmission of information from parent to offspring.18

Despite these constraints, cephalopods are equipped with complex nervous systems and show signs of intelligence, comparable to those of large-brained vertebrates. Cephalopods not only have flexible bodies, but also flexible brains and behavior. Many species exhibit a variety of foraging and predator-avoidance strategies, such as camouflage, mimicry, tool use, strategic hunting, and evasion. These strategies are considered flexible in many species. Cephalopods appear to adjust their behavior in response to the presence of a nearby prey or predator species, as well as other relevant contextual cues. Many cephalopods are also able to communicate using intricate body patterning and postures. This is notably evident in mating contexts, where aggressive signaling and tactical deception have been observed in a range of species. When competing for a female during mating aggregations, a male cuttlefish (Sepia apama) may signal either aggressive or defensive displays toward a rival male depending on the relative size of the rival. A smaller male cuttlefish may also mimic a female in order to avoid aggression from a larger rival. In another variety of cuttlefish (Sepia plangon), males have been observed performing split-body displays, simultaneously signaling courtship to a nearby female on one side while mimicking female appearance toward a rival male on the other side. Under some circumstances, female squids (Doryteuthis opalescens) may deter mating attempts by mimicking the appearance of a male squid. More generally, many cephalopod species appear to employ a range of complex learning and memory types.19 Playful behavior, an otherwise very rare occurrence in the animal kingdom, has also been observed in some octopuses.20 In a broader sense, cephalopods represent an independent evolutionary origin of intelligence from that of animals that we usually consider intelligent, such as mammals and birds.21

As a group, cephalopods may be an extreme example of the asocial pathway in the cultural brain hypothesis. For this reason, cephalopods are an important test for the hypothesis. What we have learned so far is suggestive. First, although there is very little uncontroversial evidence of social learning in cephalopods, robust evidence has been found for a wide variety of asocial learning and problem-solving abilities in a variety of species.22 Many cephalopod species are short-lived. The longest-living cephalopods, with life spans reaching perhaps five or six years, are the deep-sea species. Low temperatures and limited food availability may lead to decreased metabolic activity among the deep-sea dwellers, resulting in longer life spans. Further, many cephalopod species have a dramatically reduced juvenile period; some hatch as miniature adults.23 Even group-living species either live in semi-stable or ephemeral groups that break off and come together at various times each day, or school in huge numbers, but with seemingly limited social interactions.24 The latter scenario is perhaps comparable to large whale pods, which correlated with smaller brain size among individuals.25

According to the cultural brain hypothesis, all of these traits are general characteristics of species following the asocial learning pathway. As a result, many cephalopods may have evolved to specialize for lifestyles in an almost exclusively asocial world. They appear to have taken an opposite evolutionary trajectory to humans, who rely fundamentally on cultural learning.

How can these assertions be tested? At the time of writing, the authors, along with a small team of talented research assistants,26 are creating the largest quantitative dataset of extant coleoid cephalopod species ever assembled, covering their ecology, physiology, neuroanatomy, life-history traits, behavioral repertoires, and sociality. With this dataset, we will be able to test predictions from a range of hypotheses for the evolution of cephalopods,27 as well as pool datasets from across diverse species and taxa. Although the project is still developing, our expectation is that the analyses will eventually both support and challenge current evolutionary accounts of intelligence, including the cultural brain hypothesis, as well as fuel novel theoretical insights.

A Third Pathway

As noted, the cultural brain hypothesis incorporates the social brain hypothesis as a special case and predicts two main pathways to intelligence and large brains in the animal kingdom: a social learning path, with humans at the extreme, and an asocial learning path, with many cephalopods perhaps at the extreme. Although the animal kingdom is expansive, relatively large brains and flexible behavioral repertories are rare. Most animals cannot afford their huge energy costs. How then have most animals managed to survive, reproduce, and evolve without oversized heads?

The answer is genes. Behavioral routines are effectively stored in the genome of individuals and species. Residing in the cells of every organism is an unbroken line of ancestral information reaching back to the origin of life. If an organism’s immediate environment does not change much from generation to generation, or if generations are short,28 then adapting genetically to the world may be more efficient than evolving large brains for learning.

This insight is encapsulated in a series of models by Robert Boyd and Peter Richerson, from which the cultural brain hypothesis descends. Boyd and Richerson demonstrated how differences in environmental stability should predict different adaptation strategies.29 Genetically programmed routines are favored in highly stable environments in which the lives of offspring look a lot like those of their parents. In a highly unstable environment, information needs to be constantly updated, and an organism is better off relying on asocial trial-and-error learning.30 Social learning arises when environments are stable to the degree that the behavior of parents is still relevant but sufficiently variable that adaptation through social learning outcompetes the slower process of genetic evolution.31

The evolutionary success of life on this planet is a complex combination of three intertwined pathways: the efficient and reliable but less flexible genetic pathway, the inefficient but highly flexible asocial pathway, and the middle ground represented by the social pathway.32 Understanding these pathways and the strategic specialization of different species may lead to an expansion of the cultural brain hypothesis into a unifying theory of brain evolution. Such a theory would offer a richer and deeper appreciation of the explosion of biological wonders observed both in the fossil record and unfolding before us today on our precious Pale Blue Dot.33

  1. In the octopus and other cephalopods, the majority of nerve cells reside outside the brain and are distributed in a complex peripheral nervous system, with large concentrations of cells residing in the arms. The concept of “brain size” therefore has a radically different meaning in the study of these animals. See, e.g., Binyamin Hochner, “An Embodied View of Octopus Neurobiology,” Current Biology 22, no. 20 (2012): R887–92, doi:10.1016/j.cub.2012.09.001 
  2. For instance, Susan Healy and Candy Rowe reviewed more than fifty comparative studies on brain evolution and found it “bewildering […] that there seem to be almost as many hypotheses as there are studies, with little or no attempt to integrate the diverse results into a coherent scientific framework” (“A Critique of Comparative Studies of Brain Size,” Proceedings of the Royal Society B: Biological Sciences 274, no. 1,609 [2007]: 456, doi:10.1098/rspb.2006.3748). 
  3. Robin I. M. Dunbar, “The Social Brain Hypothesis,” Evolutionary Anthropology: Issues, News, and Reviews 6, no. 5 (1998): 178–90, doi:10.1002/(sici)1520-6505(1998)6:5%3C178::aid-evan5%3E3.0.co;2-8. Another popular and related hypothesis is the Machiavellian intelligence hypothesis: Richard Byrne and Andrew Whiten, “Machiavellian Intelligence: Social Expertise and the Evolution of Intellect in Monkeys, Apes, and Humans,” Behavior and Philosophy 18, no. 1 (1990): 73–75. 
  4. For a review, see Robin I. M. Dunbar and Susanne Shultz, “Why Are There So Many Explanations for Primate Brain Evolution?Philosophical Transactions of the Royal Society of London B: Biological Sciences 372, no. 1,727 (2017), doi:10.1098/rstb.2016.0244. 
  5. See, e.g., Nathan Emery et al., “Cognitive Adaptations of Social Bonding in Birds,” Philosophical Transactions of the Royal Society B: Biological Sciences 362, no. 1,480 (2007): 489–505, doi:10.1098/rstb.2006.1991; Natalie Uomini et al., “Extended Parenting and the Evolution of Cognition,” Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1,803 (2020): 20190495, doi:10.1098/rstb.2019.0495. 
  6. Kieran Fox, Michael Muthukrishna, and Susanne Shultz, “The Social and Cultural Roots of Whale and Dolphin Brains,” Nature Ecology & Evolution 1 (2017): 1,699–1,705, doi:10.1038/s41559-017-0336-y.  
  7. Michael Muthukrishna et al., “The Cultural Brain Hypothesis: How Culture Drives Brain Expansion, Sociality, and Life History,” PLOS Computational Biology 14, no. 11 (2018), doi:10.1371/journal.pcbi.1006504. 
  8. Cephalopods are octopuses, cuttlefish, and squids (Coleoidea). For an entertaining cinematic introduction to this evolutionary enigma, see the 2020 documentary My Octopus Teacher directed by Pippa Ehrlich and James Reed. 
  9. Muthukrishna et al., “The Cultural Brain Hypothesis.” 
  10. For instance, the technical intelligence hypothesis suggests that appendages that afford opportunities for manipulating objects and using tools for foraging, defense, etc., drive brain size. See, e.g., Richard Byrne, “The Technical Intelligence Hypothesis: An Additional Evolutionary Stimulus to Intelligence?” in Machiavellian Intelligence II: Extensions and Evaluations, ed. Andrew Whiten and Richard W. Byrne (Cambridge: Cambridge University Press, 1997), 289–311, doi:10.1017/CBO9780511525636.012. 
  11. The cultural and cumulative brain hypothesis has recently received independent theoretical backing in the form of the cultural drive hypothesis, a separate set of models arriving at comparable theoretical conclusions to the cultural brain hypothesis: Alexander Markov and Mikhail Markov, “Runaway Brain-Culture Coevolution as a Reason for Larger Brains: Exploring the ‘Cultural Drive’ Hypothesis by Computer Modeling,” Ecology and Evolution 10, no. 12 (2020): 6,059–77, doi:10.1002/ece3.6350. 
  12. Joseph Henrich, The Secret of Our Success: How Culture Is Driving Human Evolution, Domesticating Our Species, and Making Us Smarter (Princeton: Princeton University Press, 2016). 
  13. In humans, cultural adolescence has been increasing to make room for high school, university, postgraduate degrees, and internships, creating a new selection pressure for giving birth at an older age. 
  14. Asocial to social learning should be thought of as a spectrum. The model predicts that brain size may shrink if a species transitions from asocial to social learning, as smaller social brains can more efficiently acquire an equivalent amount of information compared to equivalent asocial brains. 
  15. Kristina Kverková et al., “Sociality Does Not Drive the Evolution of Large Brains in Eusocial African Mole-Rats,” Scientific Reports 8, no. 1 (2018): 9,203, doi:10.1038/s41598-018-26062-8. 
  16. This argument is consistent with the “explore–exploit tradeoff” in evolutionary biology. For a recent review, see Alison Gopnik, “Childhood as a Solution to Explore–Exploit Tensions,” Philosophical Transactions of the Royal Society B: Biological Sciences 375, no. 1,803 (2020): 20190502, doi:10.1098/rstb.2019.0502. 
  17. Christian Ibáñez and Friedemann Keyl, “Cannibalism in Cephalopods,” Reviews in Fish Biology and Fisheries 20, no. 1 (2010): 123–36, doi:10.1007/s11160-009-9129-y. 
  18. For reviews of the life-history of cephalopod species, see Peter R. Boyle, ed., Cephalopod Life Cycles, vols. 1 and 2 (New York: Academic Press, 1983 & 1987); Marion Nixon and Young, The Brains and Lives of Cephalopods (Oxford & New York: Oxford University Press, 2003). 
  19. Such and similar complex behaviors have recently been reviewed in Piero Amodio et al., “Grow Smart and Die Young: Why Did Cephalopods Evolve Intelligence?Trends in Ecology & Evolution 34, no. 1 (2019): 45–56, doi:10.1016/j.tree.2018.10.010; Piero Amodio, Shuichi Shigeno, and Ljerka Ostojić, “Evolution of Intelligence in Cephalopods,” eLS (2020): 77–84, doi:10.1002/9780470015902.a0029004; Roger Hanlon and John B. Messenger, Cephalopod Behavior (Cambridge: Cambridge University Press, 2018); Jennifer Mather and Michael Kuba, “The Cephalopod Specialties: Complex Nervous System, Learning, and Cognition,” Canadian Journal of Zoology 91, no. 6 (2013): 431–49, doi:10.1139/cjz-2013-0009; Alexandra Schnell et al., “How Intelligent Is a Cephalopod? Lessons from Comparative Cognition,” Biological Reviews 96, no. 1 (2021): 162–78, doi:10.1111/brv.12651; Alexandra Schnell and Nicola Clayton, “Cephalopod Cognition,” Current Biology 29, no. 15 (2019): R726–32, doi:10.1016/j.cub.2019.06.049. 
  20. Michael Kuba et al., “When Do Octopuses Play? Effects of Repeated Testing, Object Type, Age, and Food Deprivation on Object Play in Octopus vulgaris,” Journal of Comparative Psychology 120, no. 3 (2006): 184–90, doi:10.1037/0735-7036.120.3.184. 
  21. Jennifer Mather and Ludovic Dickel, “Cephalopod Complex Cognition,” Current Opinion in Behavioral Sciences 16 (2017): 131–37, doi:10.1016/j.cobeha.2017.06.008. 
  22. For recent reviews, see Amodio et al., “Grow Smart and Die Young”; Amodio et al., “Evolution of Intelligence in Cephalopods”; Mather and Kuba, “The Cephalopod Specialties”; Schnell and Clayton, “Cephalopod Cognition”; Schnell et al., “How Intelligent Is a Cephalopod?” 
  23. Nixon and Young, The Brains and Lives of Cephalopods
  24. Jennifer Mather, “Mating Games Squid Play: Reproductive Behaviour and Sexual Skin Displays in Caribbean Reef Squid Sepioteuthis sepioidea,” Marine and Freshwater Behaviour and Physiology 49, no. 6 (2016): 359–73, doi:10.1080/10236244.2016.1253261. 
  25. Recently, a species of octopus (O. tetricus) previously thought of as solitary was found in surprisingly high densities at two Australian sites, indicating that perhaps octopuses are more social than often thought. However, since observed social behaviors between individuals appear relatively basic, these exceptional aggregations might also, according to the discoverers of the sites themselves, more parsimoniously be explained as “an inadvertent outcome of the availability of food and the risk of predation in the habitat.” See David Scheel et al., “Octopus Engineering, Intentional and Inadvertent,” Communicative & Integrative Biology 11, no. 1 (2018): e1395994, doi:10.1080/19420889.2017.1395994. 
  26. Alexander Sørensen, Joshua Omotosho, Kiran Basava, and Nicole George. The assistants are funded by the Templeton World Charity Foundation. 
  27. For a recent review of intelligence hypotheses in cephalopods, see Amodio et al., “Grow Smart and Die Young.” 
  28. As they are for bacteria. 
  29. Robert Boyd and Peter Richerson, Culture and the Evolutionary Process (Chicago: University of Chicago Press, 1985). 
  30. This theory implies that the ancestors of modern cephalopods might have lived under very variable ecological conditions, perhaps coinciding with the loss of their protective—and behaviorally restrictive—shells, favoring in turn the flexibility in both body and mind of contemporary species. This is an intriguing speculation that might just be empirically tractable with the right kind of data. 
  31. These patterns predicted in the 1980s are consistent with data on past climates that began to emerge a decade later. See Henrich, The Secret of Our Success; Peter Richerson and Robert Boyd, “Climate, Culture and the Evolution of Cognition,” in The Evolution of Cognition, ed. Cecilia Heyes and Ludwig Huber (Cambridge, MA: MIT Press, 2000), 329­–46; Peter Richerson, Robert Bettinger, and Robert Boyd, “Evolution on a Restless Planet: Were Environmental Variability and Environmental Change Major Drivers of Human Evolution?” in Handbook of Evolution, Vol. 2: The Evolution of Living Systems (Including Hominids), ed. Franz Wuketits and Francisco Ayala (Weinheim: Wiley-VCH, 2005), 223–42, doi:10.1002/9783527619719.ch7. 
  32. Cephalopods have recently been found to undergo so-called RNA editing, which often, unlike in mammals and other animals, appears to be adaptive and evolutionarily conserved. Perhaps such editing constitutes a fourth pathway to evolutionary success in the animal kingdom. See Noa Liscovitch-Brauer et al., “Trade-off between Transcriptome Plasticity and Genome Evolution in Cephalopods,” Cell 169, no. 2 (2017): 191–202.e11, doi:10.1016/j.cell.2017.03.025. 
  33. Carl Sagan, Pale Blue Dot: A Vision of the Human Future in Space (New York: Random House, 1994). We thank the Templeton World Charity Foundation for supporting the Diverse Intelligences project “A Theory for Cephalopod Intelligence: The Alien Intelligence in Our Midst” (TWCF No. 0464). Theiss Bendixen thanks Aarhus University Research Foundation for financial support. 

Theiss Bendixen is a PhD fellow at the Religion, Cognition and Culture research unit at Aarhus University.

Jennifer Mather is Professor in the Department of Psychology at the University of Lethbridge.

Michael Muthukrishna is an Associate Professor of Economic Psychology at the London School of Economics.


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