Beckett Sterner, Arizona State University, and Scott Lidgard, Field Museum of Natural History, have written a new interpretation of a critical period in evolutionary biology leading to how scientists classify organisms: the “Systematics Wars” of the late 1960’s through the 1980’s.
This was a time when prominent biological systematists fought bitterly along partisan lines. They critique philosopher David Hull’s historical account in Science as a Process, which began what later became the common view that one camp, cladistics, straightforwardly “won” over another camp, phenetics.
Hull prioritized theory over practice and the conflicts of a few leading theorists over the less polarized interactions of systematists at large. He treated cultural evolution and biological evolution as forms of the same general process; cladistics and phenetics as holistically opposed theories can only interact by competition to the death.
Sterner and Lidgard instead analyze what systematists actually did in this period, the workflow that they followed, the methods they used, and the common problems that arose and were solved to the benefit of both camps.
They hope this opens a new window of different perspectives on how we classify organisms—the mathematization of systematics.
Nature human behavior has just published a research highlight written John Carson about work at the Sibilo School Road Site in Kenya done by Nick Blegen, Harvard University, that has recovered large quantities of obsidian along with Middle Stone Age (MSA) tools . The finds are thought to date back at least ∼200 kyr.
As Carson summarizes: “Geochemical analyses demonstrated that the majority of obsidian pieces had their provenance at a source site >160 km away, indicating long-distance transport of raw materials during the MSA.” Previously, East African sites evidencing long-distance resource transport have all be less than <50 kyr old.
Evidently known MSA sites of this age are rare in East Africa. If more sites can be found and excavated, the “big story” usually told about the evolution of human social behavior may need updating: far-reaching resource networks and/or intergroup trade in raw materials could have developed earlier than generally believed in the history of our species. If so, then in Carson’s words: “we may gain greater insight into the timeline of social evolution that eventually led to our modern group behaviours.”
Blegen’s report was just published (unfortunately behind a paywall) in the Journal of Human Evolution. Here is the abstract you will find available there for free:
This study presents the earliest evidence of long-distance obsidian transport at the ∼200 ka Sibilo School Road Site (SSRS), an early Middle Stone Age site in the Kapthurin Formation, Kenya. The later Middle Pleistocene of East Africa (130–400 ka) spans significant and interrelated behavioral and biological changes in human evolution including the first appearance of Homo sapiens. Despite the importance of the later Middle Pleistocene, there are relatively few archaeological sites in well-dated contexts (n < 10) that document hominin behavior from this time period. In particular, geochemically informed evidence of long-distance obsidian transport, important for investigating expansion of intergroup interactions in hominin evolution, is rare from the Middle Pleistocene record of Africa. The SSRS offers a unique contribution to this small but growing dataset. Tephrostratigraphic analysis of tuffs encasing the SSRS provides a minimum age of ∼200 ka for the site. Levallois points and methods of core preparation demonstrate characteristic Middle Stone Age lithic technologies present at the SSRS. A significant portion (43%) of the lithic assemblage is obsidian. The SSRS obsidian comes from three different sources located at distances of 25 km, 140 km and 166 km from the site. The majority of obsidian derives from the farthest source, 166 km to the south of the site. The SSRS thus provides important new evidence that long-distance raw material transport, and the expansion of hominin intergroup interactions that this entails, was a significant feature of hominin behavior ∼200 ka, the time of the first appearance of H. sapiens, and ∼150,000 years before similar behaviors were previously documented in the region.
Please note: this news story, recovered on 28-Jan-2017, was originally published in Science Dialogues on 27-August-2014.
Associate Curator Ken Angielczyk of The Field Museum was part of an international team of collaborators that conducted paleontological fieldwork in Zambia between June 22 and July 31. Ken and his collaborators focused on Middle Permian (~265 Mya) to Middle Triassic (~240 Mya) rocks in two areas of the country, the Zambezi Basin in southern Zambia and the Luangwa Basin in northeastern Zambia. The team had done preliminary work in the Zambezi Basin in 2011 and 2012, but only spent a total of about 5 days working there. This time, they spent about two weeks there and their discoveries include multiple species of archaic amphibians and dinocephalians and dicynodonts (both ancient mammal relatives) from the Middle Permian, extremely well preserved fossil wood, and evidence that two temporally-distinct faunas are preserved in the Permian rocks in the Zambezi Basin. They also collected a large amount of geological data that will help complete the picture of the environments in which the plants and animals were living.
The team had conducted more extensive fieldwork in the Luangwa Basin in 2009 and 2011, and this year their work focused on rounding out their previous collections and collecting more geological data to understand paleoenvironments. Among their discoveries is evidence of strong associations of particular dicynodonts with specific environments in the Late Permian rocks of the Luangwa Basin, and strong evidence of increased aridity and changes in the nature of river systems in the area moving from the Late Permian to the Middle Triassic. Ken and his collaborators will use these data to investigate the role environmental changes played in shaping the end-Permian mass extinction (the largest extinction in Earth history) and the recovery following the event.
And one important result of fieldwork like that: scientific publications. Ken and colleagues have a paper in the July issue of Journal of Vertebrate Paleontology describing fossils of tapinocephalids from Southern Zambia. Tapinocephalids are hippo-sized, herbivorous mammal relatives that lived about 265 million years ago; the fossils were discovered by Ken and his collaborators during short exploratory trips to the Zambezi Basin in southern Zambia in 2011 and 2012. They are the oldest known tetrapod remains from Zambia, and demonstrated the potential of the area for further paleontological exploration (as in previous item). This is also the second time that Ken and his teammates have discovered tapinocephalids in an area from which they were previously unknown (the first time was in 2008 in Tanzania).
Please note: this news story, recovered on 28-Jan-2017, was originally published in Science Dialogues on 5-Sept-2014.
A team from the University of Chicago, The Field Museum, and the University of Minnesota has been working for three years on a topic that has long confounded avian biogeographers: the origins and evolution of bird migration. In the August 19 issue of Proceedings of the National Academy of Sciences the team—U of C Ph.D. student Ben Winger, FMNH Associate Curator Rick Ree, and Minnesota prof Keith Barker—published a paper aimed at resolving that question for one of the largest groups of migratory birds.
Traditionally, there have been two schools of thought on where migration began and how it evolved: one theory proposed that ancestors of migratory birds spent the whole year in temperate regions, and that migration patterns evolved over time as these birds’ winter ranges gradually moved to the tropics. The other theory held that these ancestors were originally found in the tropics, with breeding grounds shifting to more temperate locales like North America.
To solve this riddle of migration the team used an innovative phylogenetic model designed to infer the historical biogeography of migratory birds. Ben and Rick developed this new model based on an existing biogeographic method that Rick developed called the “dispersal-extinction-cladogenesis” model, which has been widely used by biogeographers. They applied the model to New World “emberizoid” songbirds, a large group of migratory birds that include warblers, cardinals, sparrows, tanagers, and orioles, using a comprehensive phylogenetic tree developed by Keith and a group of colleagues. “We named it the ‘domino model’ because the breeding and winter ranges of species were coded in 3×2 grids of binary values, like dots on domino pieces,” Rick explains. “The computational challenge was to reconstruct the most probable evolutionary shifts from one domino to another.” Examining common ancestors of migratory and non-migratory species over time using the phylogenetic data, the team concluded that there was more evidence supporting the idea that birds lived year-round in North America and began migrating further and further south, resulting in today’s birds migrating thousands of miles every year.
Another result of the study suggests that many tropical species of birds are descendants of migratory ancestors that lost migration and stayed in the tropics year-round. “This is an interesting result because species diversity in this group is much higher in the tropics,” notes Ben. “Previously, more species in the tropics led to the assumption that temperate, migratory species are derived from tropical, non-migratory ancestors; however, the results of our phylogenetic study suggest that the opposite pattern happened often in this group.”
This study received nice coverage by National Geographic, among other outlets, and will soon be featured on the Field’s Science Newsflash web feature.
So what’s that about botanist and birders joining forces? Well, Ben and Keith are ornithologists, and Rick is a botanist, but with deep experience in biogeography and genomics, which he has applied beyond plants (e.g., butterflies, Amazonian amphibians, lichens). Natural history museums are places where scientists in nominally different fields, but with congruent interests—like biogeography and genomics—can cross paths, and disciplines. Which is one of the things that makes them particularly fascinating places to work.
Here’s the full citation for the article: Benjamin M. Winger, F. Keith Barker, and Richard H. Ree. Temperate origins of long-distance seasonal migration in New World songbirds. PNAS, August 4, 2014 DOI: 10.1073/pnas.1405000111
While using network theory and visualization techniques to map the genetic structure of species in space and time is in its infancy, reconfiguring how science grapples with the inherent complexity of evolution as an ever unfolding process using network approaches has the promise of making it easier to explore how comparable or dissimilar species are in their strategies for survival and reproduction. Looking long and hard at what other species do to survive and reproduce may also make it easier for all of us to see just how toxic our own social strategies—and the assumptions supporting them—can be.
Please note: this commentary, recovered on 9-Jan-2017, was originally published in Science Dialogues on 16-May-2015.
Mathematics, they say, is the language of science. When it comes to what is happening—or has happened—down here on earth, it is beginning to look like the right dialect of mathematics to learn is what is now being called (somewhat confusingly) network science.
When the goal is integrating research discoveries across disciplines as diverse as archaeology, primatology, neurobiology, and geochemistry, the mathematics of networks is the Esperanto of choice.
Field Museum in Chicago is one of the world’s largest natural history and anthropology museums. Scientists working there study the world and its human inhabitants from scores of different research directions, both pure and applied. Integrating these often seemingly disparate specialities so that the results of so much scholarship can be communicated to the public through exhibits and publications has always been a problem.
Under the leadership of Thorsten Lumbsch, Ph.D., the Director of Integrative Research at the Museum, “The Field” as it is affectionately known in Chicago is pushing back against research specialization using network science. Here is one example.
A social network is a set of actors defined by their ties, links, or relationships with one another (e.g., friendship networks, ecological networks, global trade networks, and protein interaction networks) rather than by their individual characteristics (attributes) as actors. Since the research focus is on relationships rather than on characteristics, statistical methods in network science are being developed that do not need to assume—unlike in traditional statistical analyses—that the observations being studied are independent of one another.
Dr. Termeh Shafie, who is currently a Visiting Bass Scholar at the Field, arrived in mid April from the Algorithimics Department at the University of Konstanz in Germany to help the Field’s scientists apply the statistical methods and models of network science to their research datasets which are as seemingly dissimilar as gorilla social interactions, sharks swimming in the ocean, the genetics of lichens, and the decorations on prehistoric American potshards.
When asked about her work at the Field Museum in Chicago, Termeh Shafie explains:
"The first step will be to learn more about the empirical data at hand, the hypotheses about these data being considered, and how to embed a network approach to them. The second step will be to develop network models based on these hypotheses. This requires the mathematical formulation of models, programming these models using statistical software, and then running simulations. Goodness-of-fit tests can be used to test the fit of the models to the data. Once suitable models are identified, statistics can be used to measure different properties of the networks under study and unlock information in them using the models as predictive tools. Within a level of certainty, we can then predict trends and behavior patterns even for parts of the networks we don’t yet have data for."
On Wednesday, May 13th, Dr. John P. Hart (Director, Research & Collections Division, New York State Museum), Dr. Mark Golitko (Regenstein Research Scientist), and James Zimmer-Dauphinee (2015 Regenstein Intern) participated with Shafie in a small-group Network Science Workshop at the Museum exploring ways to apply network analysis to a large database of information about pottery designs on ancient vessels from 102 archaeological sites to help unravel how communities across southern Ontario coalesced between ca. A.D. 1350 and 1650 into the larger regional populations that ultimately became the historically documented Huron confederacy.
Shafie will be at the Field until August 15th, but even after she returns to Germany, she will continue to be the “networks link” between scientists at the Museum and the Algorithmics Unit under the direction of Professor Ulrik Brandes in the Department of Computer & Information Science at the University of Konstanz.
Please note: this commentary, recovered on 9-Jan-2017, was originally published in Science Dialogues on 16-April-2015.
“The first thing in a visit is to say ‘How d’ye do?’ and shake hands!” And here the two brothers gave each other a hug, and then they held out the two hands that were free, to shake hands with her.
Alice did not like shaking hands with either of them first, for fear of hurting the other one’s feelings; so, as the best way out of the difficulty, she took hold of both hands at once . . .
Through the Looking-Glass by Lewis Carroll, 1871
AT THE HANDS OF SOMEONE like William Shakespeare or Virginia Woolf, humans may come off sounding complex, cantankerous, and downright mean at times, but often and also kind, noble, loving, and at least momentarily wise and intelligent. On the other hand, portrayals of our species in the reckonings of science are often far more one-sided and two-dimensional. Thus according to the zoologist Edward O. Wilson (2012) we are a tribal eusocial species committed to killing outsiders for the good of our home group. The evolutionary psychologist Steven Pinker (2011a) maintains that we all have in effect if not in fact violent demons lurking within us that must be tamed by reason, compassion, and good governance. The social scientists Samuel Bowles and Herbert Gintis (2011) have expressed a more favorable view of human nature, but again like Wilson and Pinker, they have described our willingness to cooperate with one another as an evolutionary mystery in need of resolution given that humans are selfish at heart and can be self-serving in their motivations.
The most parsimonious proximal explanation of cooperation, one that is supported by extensive experimental and other evidence, is that people gain pleasure from or feel morally obligated to cooperate with like-minded people. People also enjoy punishing those who exploit the cooperation of others, or feel morally obligated to do so. (Bowles and Gintis 2011: 3)
There are two major assumptions at the ground level of most current scientific analyses of human nature. The first is that selfishness is one of the prime movers of biological evolution. The second is the claim that human cooperation is based on reason, shame, and good gamesmanship. “The most important psychological contributor to the decline of violence over the long term may instead be reason: the cognitive faculties, honed by the exchange of ideas through language, that allow us to understand the world and negotiate social arrangements” (Pinker 2011b: 310). Both of these assumptions are questionable.
The fundamentals of evolutionary thinking as a way of explaining what we are seeing in the world of today and in the past have changed over time since Darwin’s day (Amundson 2014). Tom Clark has shown in his series of commentaries at SCIENCE DIALOGUES on Darwin’s use of “use and disuse” that during the latter half of the 20th century, the neo-Darwinian assumption that genes and environments were sufficient causes of observed behavior “turned natural selection from an animate doing into a physical happening. Attributing behavior to stable causes both inside (molecules) and outside (environment) turned animals into spectators, along for the ride.”
Clark underscores that how we tell our story of what it means to be human and how we have evolved to be the sort of animal we are directly leverages or constrains how well we handle our individual and collective impacts on the earth and our fellow human beings.
As Michael Ruse (2014) has observed, today natural selection is the mechanism seen by most experts on evolution as the chief reason for organic change. It is perplexing, however, that when it comes to our species, attempts to explain our general willingness to cooperate with one another often take it as self-evident that selfishness, infra-specific competition, and gamesmanship (Potter 1947; Rand et al. 2013) rule the day even when we seem to be acting in kind, considerate, and evidently caring ways towards others (Terrell 2015: 111–117).
Such scientific cynicism may make perfect sense given the ruling assumptions of neo-Darwinian theory today, but the picture looks quite different if it isn’t accepted from the get-go that selfishness has to be a part of every permissible Darwinian explanation for life’s diversity and history on earth.
Social baseline theory
The psychologists Lane Beckes and his colleague James Coan are studying empathy and cooperation based on a radically different view of what it means to be human, a research tactic they call social baseline theory (Beckes and Coan 2011). Their working assumption is one that many would accept with little disagreement: being a social animal gives any species a genuine and practical advantage in the Darwinian struggle for survival and reproduction. And for humans at least, having the capacity to live and work closely with others also gives us a social baseline of emotional support and security. So much so, they say, that our social ties with other people are in effect an extension of the way the human brain interacts with the world. As a consequence, when we are around others we know and trust, we can let down our guard and relax.
From this perspective, the experienced payoffs are more than emotional. When we thus feel safe and secure, we are literally able to devote less energy—and we would add, less time—to staying alert for possible threats and uncertainties. Indeed, they have argued that the human brain has evolved to assume the presence of other people. In their words: “In our view, the human brain is designed to assume that it is embedded within a relatively predictable social network characterized by familiarity, joint attention, shared goals, and interdependence.”
On the other side of the mirror
Beckes and Coan have said a major saving grace of human sociality is the energetic cost benefit of not having to be the only one looking out for number one (Beckes and Coan 2011; Coan and Maresh 2014; Coan and Sbarra 2015). While we would grant that there may be be such a cost benefit, we are uncertain how decisive this savings has been in shaping human evolution. After all, the probability of survival is determined not only by how much effort you have to put into the struggle. It can be argued that we are such strongly social animals for other reasons, too. First, we critically depend on social learning to know how to survive in the first place. Second, many of us—but admittedly not all—are predisposed socially and emotionally to be caregivers because our offspring wouldn’t survive the first years of their lives if we weren’t (Terrell 2015: 190–191).
To survive and reproduce, organisms must take in more energy than they expend, a principle of behavioral ecology called economy of action. Social baseline theory (SBT), a framework based on this principle, organizes decades of observed links between social relationships, health, and well-being, in order to understand how humans utilize each other as resources to optimize individual energy expenditures. (Coan and Maresh 2014: 221).
Furthermore, there is the matter of time. It may be true that time is money, but we humans are pretty good at wasting time for apparently no good reason, energetic or otherwise. And certainly there is no denying that when we feel safe and secure, many of us are willing to invest both time and energy in seemingly unproductive ways.
Consider, for example, the metabolic cost of the continuing mental activity in what has been dubbed the brain’s default mode network (DMN) when we are not task-engaged. The reward of not having to attend closely to the practicalities of the world around us when we feel safely embedded in nurturing social networks may be the excitement Alice must have felt in Lewis Carroll’s story after she had slipped through the looking-glass to explore the hidden wonders to be found therein (although judging by his singular account, Alice evidently did not find doing so as addictive as some today find the similar cognitive experience of playing online computer games). Just as those incarcerated in our penal system may be given time off for good behavior, so too, sharing the demands and burdens of life with others gives us time off to play with whatever takes our fancy on that landscape between our ears.
Amundson, Ron (2014). Charles Darwin’s reputation: How it changed during the twentieth-century and how it may change again. Endeavour 38: 257–267.
Beckes, Lane and James A. Coan (2011). Social baseline theory: The role of social proximity in emotion and economy of action. Social and Personality Psychology Compass 5: 976–988.
Bowles, Samuel and Herbert Gintis (2011). A Cooperative Species: Human Reciprocity and Its Evolution. Princeton: Princeton University Press.
Coan, James A. and Erin L. Maresh (2014). Social baseline theory and the social regulation of emotion, pages 221–236. In J. Gross, ed., The Handbook of Emotion Regulation, 2nd. ed., pp. 221–236. New York: Guilford Press.
Coan, James A. and David A. Sbarra (2015). Social baseline theory: The social regulation of risk and effort. Current Opinion in Psychology 1: 87–91.
Pinker, Steven (2011a). The Better Angels of Our Nature: The Decline of Violence in History and its Causes. New York: Viking.
Pinker, Steven (2011b). Taming the devil within us. Nature 478: 309–311,
Potter, Stephen (1947). Theory and Practice of Gamesmanship. New York: Henry Holt & Company.
Rand, David G., Corina E. Tarnita, Hisashi Ohtsuki, and Martin A. Nowak (2013). Evolution of fairness in the one-shot anonymous Ultimatum Game. Proceedings of the National Academy of Sciences U.S.A. 110: 2581–2586.
Ruse, Michael (2014). Was there a Darwinian revolution? Yes, no, and maybe! Endeavour 38: 159–168.
Terrell, John Edward (2015). A Talent for Friendship: Rediscovery of a Remarkable Trait. Oxford and New York: Oxford University Press.
Wilson, Edward O. (2012). The Social Conquest of the Earth. New York: Liveright (a division of W. W. Norton).
Please note: this commentary, recovered on 9-Jan-2017, was originally published in Science Dialogues on 24-March-2015.
THE BEHAVIORIST B. F. SKINNER was famously opposed to “mentalistic explanations” for human behavior. By this he meant attributing to the world of the mind an active “top-down” role (Baumeister and Miller 2014) in determining what we think, say, and do. In his eyes, trying to explain our overt behavior by appealing to inner states of mind, feelings, and other elements of an “autonomous man” inside our skulls was utterly foolish, unscientific, and a waste of time. “The ease with which mentalistic explanations can be invented on the spot is perhaps the best gauge of how little attention we should pay to them” (Skinner 1971: 160).
Instead, according to Skinner, the “task of a scientific analysis is to explain how the behavior of a person as a physical system is related to the conditions under which the human species evolved and the conditions under which the individual lives” (1971: 14). As distasteful as some might find such a realization, “the fact remains that it is the environment which acts upon the perceiving person, not the perceiving person who acts upon the environment” (1971: 188).
Even Skinner was willing to concede the “indisputable fact of privacy.” Nonetheless he stuck to his staunch environmentalism. “It is always the environment which builds the behavior with which problems are solved, even when the problems are to be found in the private world inside the skin” (1971: 194).
In a scathing review of Skinner’s 1971 book Beyond Freedom and Dignity, the linguist Noam Chomsky thoroughly rejected Skinner’s scientific claims. “His speculations are devoid of scientific content and do not even hint at general outlines of a possible science of human behavior. Furthermore, Skinner imposes certain arbitrary limitations on scientific research which virtually guarantee continued failure” (Chomsky 1971).
Unfortunately Chomsky’s spirited defense of human freedom and dignity against Skinner’s denial of both offered few concrete hints on why we are not the automatons Skinner said we are. But how are we not controlled by the world around us and by all that life deals us, both painful and pleasurable? How and how much does Skinner’s nemesis “autonomous man” have any real say in what we think, feel, and do? Chomsky left these critical issues unexplored and undocumented.
The mind-body problem
The philosopher Jerry Fodor noted in 1980 that traditional philosophies of mind can be divided into two sorts: dualist theories and materialist theories. “In the dualist approach the mind is a nonphysical substance. In materialist theories the mental is not distinct from the physical; indeed, all mental states, properties, processes and operations are in principle identical with physical states, properties, processes and operations” (Fodor 1980: 114). Since then cognitive psychologists and experts in neuroscience imaging have come down more or less firmly on the side of materialist theories, although exactly how the neurological hardware and software called the brain processes information and arrives at conclusions remains more an educated guess than a demonstrated reality.
Awkwardly what has traditionally been called the “mind-body problem” has often been seen in both science and philosophy as a conundrum about the consciousness of our thoughts and decisions. Yet as Max Velmans (2008) has observed, “it is now clear that ‘mind’ is not quite the same thing as ‘consciousness,’ and that the aspect of body most closely involved with consciousness is the brain. It is also clear that there is not one consciousness–brain problem, but many.” In other words, reading “mind and body” to mean “consciousness and brain tissue” is far too restrictive, too limiting.
Recently Ralph Adolphs (2015) at the California Institute of Technology surveyed what we do and don’t know about consciousness as a mental phenomenon and finds that there is little agreement about what it is and how it works. He helpfully divides the unsolved problems in neuroscience into four basic categories ranging from those that are now solved or will soon be to those that may never be decided. Discouragingly, he puts three key issues in the latter category. (1) How does the human brain compute? (2) How can cognition be so flexible and generative? (3) How and why does conscious experience arise?
His final conclusion is equally sobering. “In a nutshell, then, the biggest unsolved problem is how the brain generates the mind, conceived of in a way that does not simultaneously require answering the problem of consciousness.” However, on a more promising note, he adopts the framework proposed by David Marr (1982) to suggest that memory at least can be understood as the “ability to predict the future by learning.”
This comment is worth emphasizing. Unlike old Father William in Lewis Carroll’s famous poem who elected to stand on his head again and again after learning he had no brain, we see the design and decision-making that are both so fundamental to human niche construction as tangible proof that the human brain is capable of stimulus-independent, self-directed thought (Bonn 2013)—a roundabout way of saying that like Father William, the cognitive manipulations and innovations happening in our minds can lead to top-down, not just bottom-up causation (Foulkes and Domhoff 2014).
Evidence favoring this admittedly far from surprising conclusion can be seen readily enough in what happens on the landscape between our ears during that mysterious cognitive activity called dreaming.
Dreams and dreaming
It is an enduring folk belief that we live our lives on-again off-again in dichotomous ways. We are either happy or sad, awake or asleep, conscious or unconscious, rational or emotional, and so on.
Cognitive psychology today, however, is discovering that a great deal that is happening in the brain instrumental to our survival, success, and emotional well-being is (1) largely disengaged from our conscious awareness of what’s going on both inside and outside us (e.g., Mudrik et al. 2014; Soto and Silvanto 2014), and is (2) more dependent on our feelings and emotions than conventionally seen (e.g., Inzlicht et al. 2015).
Dreaming, like consciousness, is one of those arenas of mental life about which much has been written and yet much remains to be understood (Domhoff and Fox 2015). Here we offer two observations. First, dreaming is more a top-down brain activity than generally envisioned (Foulkes and Domhoff 2014). Second, nobody who has ever recalled a dream needs to be told by anyone else that our brains are capable of creating often credible but truly off-the-wall situations, scenarios, and storied experiences that may not only have lingering emotional impact long after awakening, but can also be a source of great inspiration and creative insight. In short, cognitive niche construction does not need to be either conscious or wakeful.
Saying you know for sure what free will is or isn’t has long been a reliable way of provoking debate (Monroe et al. 2014). Nonetheless, here are three claims based on what we have been discussing thus far in this SCIENCE DIALOGUES series. First, human beings can think about things and actions—past, present, or future—without being aware that they are doing so (Bonn 2013). Second, human beings can act in accord with the worlds they construct for themselves in their Leslie minds. Third, free will does not have to be rational if by rational we mean “makes sense” in terms of the external world and the laws of physics, etc. Cognitive niche construction may begin with our own experiences of the world, but it does not have to end there. And as we shall discuss in later commentaries in this series, therein lies a problem.
Adolphs, Ralph (2015). The unsolved problems of neuroscience. Trends in Cognitive Science, in press.
Buschman, Timothy J. and Earl K. Miller (2014). Goal-direction and top-down control. Philosophical Transactions of the Royal Society B: Biological Sciences 369: 20130471 http://dx.doi.org/10.1098/rstb.2013.0471.
Bonn, Gregory B. (2013). Re-conceptualizing free will for the 21st century: Acting independently with a limited role for consciousness. Frontiers in Psychology 4: 920. doi: 10.3389/fpsyg.2013.00920
Chomsky, N. (1971). The case against B. F. Skinner. The New York Review of Books 17: 18-24.
Domhoff, G. William and Kieran C. R. Fox (2015). Dreaming and the default network: A review, synthesis, and counterintuitive research proposal. Consciousness and Cognition 33: 342–353.
Fodor, Jerry (1880). The mind-body problem. Scientific American244/1: 114–123.
Foulkes, David and G. William Domhoff (2014). Bottom-up or top-down in dream neuroscience? A top-down critique of two bottom-up studies. Consciousness and Cognition 27: 168–171.
Inzlicht, Michael, Bruce D. Bartholow, and Jacob B. Hirsh (2015). Emotional foundations of cognitive control. Trends in CognitiveScience 19: 126–132.
Marr, David (1982). 9 Marr, D. (1982) Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. San Francisco: W. H. Freeman.
Monroe, A. E., Dillon, K. D., and Malle, B. F. (2104). Bringing free will down to earth: People’s psychological concept of free will and its role in moral judgment. Consciousness and Cognition 27: 100–108.
Mudrik, Liad, Nathan Faivre, and Christof Koch (2014). Information integration without awareness. Trends in Cognitive Sciences 18: 488–496.
Skinner, B. F. (1971). Beyond Freedom and Dignity. New York: Alfred A. Knopf, 1972.
Soto, David and Juha Silvanto (2014). Reappraising the relationship between working memory and conscious awareness. Trends in Cognitive Sciences 18: 520–525.
Velmans, Max (2008). How to separate conceptual issues from empirical ones in the study of consciousness. In R. Banerjee and B. K. Chakrabarti (eds.), Models of Brain and Mind: Physical, Computational and Psychological Approaches 168: 1–9.
We thank Tom Clark and Kevin Kelly for their comments and suggestions for improvement.
Please note: this commentary, recovered on 9-Jan-2017, was originally published in Science Dialogues on 5-March-2015.
“Oh, Kitty! how nice it would be if we could only get through into Looking-glass House! I’m sure it’s got, oh! such beautiful things in it! Let’s pretend there’s a way of getting through into it, somehow, Kitty. Let’s pretend the glass has got all soft like gauze, so that we can get through. Why, it’s turning into a sort of mist now, I declare! It’ll be easy enough to get through—” She was up on the chimney-piece while she said this, though she hardly knew how she had got there. And certainly the glass was beginning to melt away, just like a bright silvery mist.
Through the Looking-Glass by Lewis Carroll, 1871
ALICE’S ADVENTURES IN WONDERLAND (first published in 1865) is Lewis Carroll’s most beloved book thanks in part to Walt Disney Studios and its 1951 cartoon version that beautifully captured the logical nonsense of Carroll’s rich fantasy world of talking rabbits, smiling cats, and unlikely occurrences. The Disney cartoon, however, also incorporated a few of the characters and events from Carroll’s sequel Through the Looking-Glass and What Alice Found there (1871).
While both books exhibit his brilliance at cognitive niche construction, Carroll’s framing his second story around the otherworldly semblance of reality seen in a looking-glass may have been inspired by his own reflections on the elusiveness of human thought. He was a mathematician first and foremost. He knew well that however much our thoughts may mirror the world around us and what we experience from the cradle to the grave, each of us lives in a cognitive world populated by our own private thoughts on the “other side of the looking-glass”—a world that, unlike Alice, others cannot enter and explore.
The human conundrum
There is nothing surprising about saying we can draw a line between our public lives and our private thoughts. Look into the eyes of any dog. There is also nothing remarkable about saying we are evidently not the only species capable of entertaining private thoughts and passions. As one of us has explored more fully elsewhere (Terrell 2015), our evolved human capacity to engage in cognitive niche construction—however remarkable or shared with at least some other species—brings with it costs as well as benefits. Socially we have evolved as a species to both want and need human contact and engagement. Yet during the evolution of our huge human brain we achieved a level of private cognition that enables us to disengage from the world around us. Hence as a species we are confronted with a conundrum. We are social creatures with private thoughts “on the other side of the mirror” that can isolate us from others.
THE DYNAMIC INTERPLAY OF HUMAN EVOLUTION
Over the course of human evolution there has been a dynamic interplay between our mental & physical abilities, our brains, our social behavior, and our cleverness at niche construction that has also nurtured our skillfulness as a species at cognitive niche construction.
Lou, Laurence, and Leslie
Modeling how our minds work has taken many twists and turns over the course of human history. Some of the more extreme recent interpretations have insisted either that the brain is massively modular in its aptitudes (Steven Pinker and other evolutionary psychologists), or alternatively is passively shaped, or sculpted, by our interactions with the world around us (classical 20th century stimulus-response psychology).
At this stage in our investigations, we prefer to remain agnostic about how the brain’s circuitry gives us the capacity for thinking as seen in all its many dimensions, public and private (Adolphs 2015; Lamme 2006). In keeping with Daniel Kahneman’s (2011) wisdom to use such things as tools for thought rather than as literal descriptions of our cerebral hardware, we find it useful to characterize how we think about things and events in three different ways using the labels Lou, Laurence, and Leslie (for discussion, see: Terrell 2015: chapter 4):
Lou (also known as System 1 or Type 1)—thinking that is unconscious, automatic, quick, perhaps emotional, and easy to do; in short, information processing in the brain done mostly without conscious awareness; a type of thinking that may be evolutionarily old and is probably also within the mental capabilities of other animal species; the realm of our habitual selves.
Laurence (called System 2 or Type 2)—thinking that is conscious, slow, takes effort, and is purposeful; usually said to be involved in “higher-order” cognitive processes such as logical reasoning and decision-making; may or may not be unique to our species; the realm of intentional environmental niche construction.
Leslie—thinking that is contemplative, abstract, may be counterfactual, and is largely detached from an individual’s immediate realities; may or may not be unique to our species; the realm of cognitive niche construction
As Jessica Andrews-Hanna and her colleagues observed recently, understanding the mechanisms underlying self-generated thought and its adaptive and maladaptive functional outcomes has been a key aim of cognitive science in recent years (Andrews-Hanna et al. 2014: 29). In their estimation, far from being a passive brain phenomenon, for example, the default mode network (DMN) within our skulls contributes to several active forms of internally driven cognition. As she and her colleagues have written:
Tasks that activate the network often require participants to retrieve episodic, autobiographical, or semantic information, think about or plan aspects of their personal future, imagine novel scenes, infer the mental states of other people, reason about moral dilemmas or other scenarios, comprehend narratives, self-reflect, reference information to one’s self, appraise or reappraise emotional information, and so on. (Andrews-Hanna et al. 2014: 32)
Although much remains to be learned about the costs and benefits of self-generated thought—which has also been dubbed stimulus-independent thought, spontaneous thought, internally-directed thought, and mind-wandering—it is becoming increasingly clear that the default and executive networks in the brain are not inherently working in opposition.
Kalina Christoff and her colleagues, as a case in point, have argued that both networks can work in parallel in ways that are reminiscent of the neural recruitment observed during creative thinking before solving problems with insight. Furthermore, “similar parallel recruitment of executive and default regions has also been observed during naturalistic film viewing, which is related to immersive simulative mental experience” (Christoff et al. 2009: 8723).
What we find both intriguing and frustrating is that many researchers studying self-generated thought, with notable exceptions (Killingsworth and Gilbert 2010), seem committed to the view that internally-directed thought lies within the reach of human cognition because even when it appears to be getting us away from what we really ought to be doing to survive and make a living, mind-wandering may nonetheless “enable the parallel operation of diverse brain areas in the service of distal goals that extend beyond the current task” (Christoff et al. 2009: 8723).
Perhaps, but not necessarily so, as we shall discuss in the next commentary in this series.
Andrews‐Hanna, Jessica R., Jonathan Smallwood, and R. Nathan Spreng (2014). The default network and self‐generated thought: Component processes, dynamic control, and clinical relevance. Annals of the New York Academy of Sciences 1316: 29–52.
Christoff, Kalina, Alan M. Gordon, Jonathan Smallwood, Rachelle Smith, and Jonathan W. Schooler (2009). Experience sampling during fMRI reveals default network and executive system contributions to mind wandering. Proc. Natl. Acad. Sci. U.S.A. 106: 8719–8724.
Kahneman, Daniel (2011). Thinking: Fast and Slow. New York: Farrar, Straus and Giroux.
Killingsworth, Matthew A., and Daniel T. Gilbert (2010). A wandering mind Is an unhappy mind. Science 330: 932.
Lamme, Victor A. F. (2006). Towards a true neural stance on
consciousness. Trends in Cognitive Sciences 10: 494–501.
Terrell, John Edward (2015). A Talent for Friendship: Rediscovery of a Remarkable Trait. Oxford and New York: Oxford University Press.
Please note: this commentary, recovered on 9-Jan-2017, was originally published in Science Dialogues on 22-Jan-2015.
“Can we state more distinctly still the manner in which the mental life seems to intervene between impressions made from without upon the body, and reactions of the body upon the outer world again?”
William James, The Principles of Psychology, 1890: 6
THE NEUROLOGIST MARCUS RAICHLE HAS remarked that studies of brain function have traditionally focused on task-evoked responses (Raichle 2010, 2015). As Daniel Kahneman has explained, such research has contributed the useful convention that there are two modes of thinking—two systems in the mind, System 1 (or Type 1) and System 2 (or Type 2). In Kahneman’s words (2011: 20–21):
System 1 operates automatically and quickly, with little or no effort and no sense of voluntary control.
System 2 allocates attention in the effortful mental activities that demand it, including complex computations. The operations of System 2 are often associated with the subjective experience of agency, choice, and concentration.
Although such conventions are useful, Raichle argues that focusing on task-evoked responses “ignores the alternative possibility that brain functions are mainly intrinsic, involving information processing for interpreting, responding to and predicting environmental demands” (2010: 180).
As he says, it is not difficult to see why so much attention has been given to monitoring neural responses to carefully designed tasks that can be rigorously controlled: “evaluating the behavioral relevance of intrinsic activity (i.e. ongoing neural and metabolic activity which is not directly associated with subjects’ performance of a task) can be an elusive enterprise” (2010: 180).
While it could be argued that intrinsic brain tasks are part and parcel of System 2 thinking, I believe it may be more constructive to infer instead that there is a third mode of thinking—one that I have suggested may be called cognitive niche construction (Terrell 2015: 29–32, 168–172)—a way of thinking that may strongly engage the brain’s default-mode network.
As Raichle (2015) and Robert Spunt and his colleagues (in press) have underscored, there is considerable metabolic cost to running the human brain when it is engaged in ongoing internal activity. As the latter researchers observe: “most of the brain’s energy budget is consumed not by activity evoked by specific cognitive tasks (e.g., mental arithmetic) but by spontaneous ongoing activity that is most notable when the brain is at rest.”
Given the metabolic cost of this ongoing internal activity in what has been dubbed the brain’s default mode network (DMN) when we are not task-engaged, an obvious question arises. How can we afford such stimulus-independent activity?
Raiche, Spunt et al., and others stress the likelihood that such inner-directed brain activity must be somehow adaptive in a realistic Darwinian sense, i.e., this inner activity must be “functionally consequential for the execution of stimulus-dependent mental state inferences” (Spunt et al. in press). This inference is plausible, but arguably not sufficient.
How we are able to remake the world around us when we put our minds and backs to the effort has been called niche construction (Odling-Smee et al. 2003). In the biological sciences, the word “niche” means “way of life,” and every species is said to have its particular place, or niche, in the economy of life. We are just one of a number of species that excel at making and remaking their way of life, their place in the grand scheme of things, their ecological niche. Similarly, I have argued that even when it may look as if we are day-dreaming, our minds actually may be hard at work engaged in cognitive niche construction—a way of using our brains that is possibly but not necessarily unique to our species (Terrell 2015).
Others recently have also written about cognitive niche construction, but what they evidently have in mind may be more clearly activity under the heading of System 2 thinking. Steven Pinker, for instance, has defined cognitive niche construction as “a mode of survival characterized by manipulating the environment through causal reasoning and social cooperation” (Pinker 2010: 8993).
Such a description glosses over how difficult it can be to apply what we envision in our mind’s eye to the realities of life. More to the point, such a definition does not confront the obvious weakness of cognitive niche construction at least as I have described it. What goes on between our ears when we are engaged in such mental activity does not have to be rational at all, at least not if by “rational” we mean thinking that makes practical sense in the real world outside our bodies.
By detaching from the realities of the moment and turning our mind to our inner thoughts, we are able to ponder what I like to call the “coulds & shoulds” of life. We can devote our mind to a kind of imaginary niche construction that does not even have to be “of this world” at all. We can see seemingly impossible things in our mind’s eye. We can engage in “what if” fantasies of remarkable, perhaps sexually charged, and even quite unrealistic complexity. We can invent imaginary worlds, invent new things, rewrite the story of our life to our heart’s content. All in the mind rather than in the real world.
In short, it seems likely we engage in cognitive niche construction not just for interpreting, responding to, and predicting environmental demands—to paraphrase what Raichle has previously said. As Spunt et al. observe: “Given that the DMN activity is metabolically costly, widely distributed in the cortex, and highly sensitive to both the presence and type of task demand, it should be no surprise that this network would have functional consequences in multiple domains” (Spunt et al., in press).
They themselves hypothesize that natural selection has favored the evolution of such a costly DMN in humans (and possibly also in chimpanzees and monkeys) so that we can more skillfully “see the world in terms of other minds” and live together socially—thereby gaining far more socially than would be likely by living separately.
While this is a plausible hypothesis, it is not the only one possible, as Gabriel Terrell and I will discuss in the forthcoming commentaries.
Editor’s note: This is the first in a series of eight commentaries at SCIENCE DIALOGUES on cognitive niche construction and its implications for psychology, philosophy, and the social sciences generally.