Thriller-Writer Lee Child and Linguist Dieter Wunderlich on the Evolution of Language

Lee Child is one of my favorite Thriller-authors. Normally I don’t find the time to read non-studying related fiction, but I especially enjoy his audio books because of the cool American accent of the narrator. However, when I stumbled on an essay by Lee Child called “The Origin of the Thriller”, I was a bit confused. Here’s his take on the evolution of language: According to Lee Child, a couple of hundred thousand years ago, Neanderthals and humans, the only homo “contenders” left were competing for resources, and Neanderthalers had the upper hand:

“They were heavier and stronger and faster. They were superb tool makers. They were much better equipped to survive the brutal conditions of prehistory.

But they didn't survive. We did. Why?

Because Homo Sapiens developed language. Many primitive species could communicate by making sounds — and many still do: prairie dogs make distinctive noises if a predator is spotted — one noise for a ground predator, and another for an airborne predator. But Homo Sapiens went beyond two words. After a random mutation our brains grew large and the new capacity was colonized by language, with a theoretically infinite number of available words, and more importantly with syntax, such that as well as reporting we could plan and speculate. Not just: a predator is coming, but also: a predator will come, or might come. Not just reaction, but also prediction: if we do this, we'll be OK, or if we do that, we'll be in trouble. “

But here’s the gem According to Child, humans are weak and fragile and in disorganized groups we would quickly be killed by predators:

“But a coordinated crowd of two hundred humans is the most powerful animal on earth. The heaviest, the strongest, the hardest to stop, the hardest to kill. Thus, grunting Neanderthals slowly died out, despite their muscle and bone and strength and speed, and talking humans marched on toward the present, despite our slender limbs and fragile skulls”

The last Sentence is faboulus isn’t it? We better don’t tell him anything about Neanderthal-DNA, Neanderthal Vocal Anatomy, FOXP2, Introgression, etc.

But I want to present a more plausible and worked out view on the topic. Yesterday I was searching for material on the evolution of syntax, because a friend of mine asked me to comment on a section of his MA-Thesis in which he shortly discusses the topic. (For a discussion of the speculation, that certain features of language are ‘living fossils’, or vestiges of an older proto-language, see this post).

On my search I found the slides of a talk given by German linguist Dieter Wunderlich on the evolution of language, that he held in Leipzig, Germany, in December 2007. The talk and the slides are in German, but because he offers a very comprehensive and nice review on some aspects of the current state of the art in language evolution research/evolutionary linguistics, I decided to write an English summary of it.

Key Questions

When looking at the evolution of language, there are three question that guide our inquiry:

1. How exactly did language get started? What is hotly debated is whether it evolved in a gradual manner (continuist/adaptationist position: see e.g. Pinker & Bloom 1990) or in a ‘sudden leap’ (discontinuist/ exaptationist: see e.g. Hauser et al. 2002)

2. When did language evolve? Depending on our answer to question 1., the question would be when each step toward language took place, or when the big leap happened.

3. Did language evolve only once or several times?

What is language?

Basically, language can be described as a system for expression, that relates Utterances and meaning to one another, in relation to certain contexts.

Morphosyntax governs the construction of complex utterances out of smallest units of language, namely lexical entries (=”words” in your mental lexicon) as well as morphemes (-s, -ed, un-, -er, etc.). Its system is compositional, that is every construction leads to complex expressions of meaning which are determined by the single lexical entries as well the rules that govern their combination. The rules governing the compositional construction of utterances are recursive.

There are two interfaces to non-linguistic abilities:

1. an interface with the system responsible for the production and perception of sounds and gestures (In generativist terminology this would be the Sensori-Motor System (SM) or the Articulatory-Perceptual (AP) System)

2. an interface with our mental representations and our discourse intentions (in generativist terminology: the Conceptual-Intentional (CI) system. cognitive linguists would probably call it our conceptual system)

Important events which shaped the current state of language

There are 5 important events that have shaped how languages and our mental structures that enable us to use it look:

In chronological Order:

1. There was an expansion of the cortex (frontal lobe) in early hominids such as homo erectus, who lived approx. 2 million years ago. In just 1 million years, brain size rose from 600 to 1400ccm. This may be related to the begin of an ice-age about 2.5 million years ago.

2. Anatomically modern man (homo sapiens) probably evolved about 170.000 years ago in east Africa.

3. Starting from about 50.000 years ago, there is archaeological evidence of improved tool-making capacities, burials, ornaments, and figurative art in several parts of the world (the so-called Upper Palaeolithic Revolution). In Africa these features can be found even earlier, as is especially salient from about 85.000 years ago, which even led some researchers to call this period an “African Upper Palaeolithic” (see e.g. Dubreuil 2008).

4. From 12.000 years ago onwards, there was a spread in agriculture which seemed to have happened independently in several parts of the world (The Neolithic Transition)

5. Starting from 6000 years ago, writing systems were developed independently in several parts of the world.

Of these 5 events, the first three are biological of nature, whereas the last two are cultural events. A diversification of biological events brought about by mutations and selection led to one single event: genetically modern man. In principle, every human being can reproduce with every other opposite-sex human, which fulfils the criterion of biological species. Furthermore, every child, regardless of its parents, can learn every language of the world when it is put into the critical environment at the right age. Thus language is a common and uniting feature of humans, and we all share the genetic structure that enables us to learn language (but for evidence that there is still genetic variation on a small scale, see these two posts)

What are the differences between and non-human communication systems?

Influential linguist Charles F. Hockett has posed 13 ‘design features of language’, 7 of which are especially interesting regarding the evolution of language. These are:

1. For the majority of human languages, the vocal-auditory channel the basic mode of communication.

2. Parity/Interchangeability: hearer and speaker constantly switch roles during conversation, which also means that a communicator is able to both produce and receive the same signal, which isn’t the case with say, gender-specific calls in sticklefish.

3. Semanticity/Arbitrarines: specific signals can be equipped with specific meaning in a manner where there is no necessary or logical connection between form meaning (“table” has nothing to do with any actual properties of a table)

4. Displacement: humans can talk about things that are not present in their immediate environment, or even things that do not exist at all (say, for example, my comprehension of mathematics). Human reference thus extends “beyond the horizon” and the perceptual space, but extends to mental spaces and shared systemic spaces.

5. Honey bee communication about the location of nectar of course is also displaced, but it only built to convey very specific information, and is not unbounded and productive like human language.

6. Traditional Transmission/Learnability human children are able to learn the language of their environment. As W.v.O. Quine said “language is a social art”, which essentially depends on the ability to be part of and interact with a complex culture that transmits complex behavior and knowledge. This complexity and language-specificness is probably the dividing feature, because song-birds also have to learn their songs from other birds, vervet monkeys need to be reinforced in their innate tendencies to hiss at snakes and have to zoom in on the exact referent for eagle alarm callas through positive reinforcements by other group members, and chimpanzees have been shown to adhere to some forms of social transmission and conformity as well as for rational imitation (e.g. Whiten et al. 2005)

7.Discreteness/Duality of Patterning the smallest units of language combine with each other in a systematic and combinatorial manner (that is Phonemes/Sound units combine to form Morphemes) , which then also combine in a systematic fashion (Morphemes built whole words and then sentences). This method allows for “infinite expression by finite means” (Humboldt) and is responsible for the diverse displaced productivity of language.

Wunderlich argues that homo erectus already possessed most of these features, but maybe not 6. and 7.

So what could homo erectus do?

Although he certainly didn’t have full-fledged human language, he was able to perform complex and social tasks. From 1.5 million years ago onwards, he was able to keep a fire burning, and from 0.8 million years ago he could even make fire.

He was able to make hand-axes (1.4 million years ago) and was also able to throw them, which, according to William Calvin, is suggested by neuropaleontological evidence. He way able to hunt together with other group members. He was very mobile: signs of him can be found in Georgia (1.8 million), later on there are also signs in China, Indonesia, and Europe.

Homo erectus was divided in several species that probably lived alongside each other. The last ones co-existing with us were the Neanderthals.

Tool use

Chimpanzees and orangutans use tools (see here, for a cool post on spear fishing in orangutans)such as sticks for termite fishing, stones to crack open nuts, and leaves to soak up water, but these tools are contextually available, that is they do not have to be crafted in the same complex way as hand-axes, for example. Interestingly, there is population level handedness of 2:1 in chimpanzees. Termite fishers are mostly left-handed, whereas nut-crackers and wadge-dippers are mostly right-handed, this means that handedness seems to be heritable. In humans, the left-right ratio is 9:1. The distribution of handedness means that handedness is task-specific, and “

that the motor and cognitive demands of different tasks can have a significant influence on handedness in human and nonhuman primates” (Lanson & Hopkins 2005).

This means

“that antecedents of lateralization of function associated with hand use were present at least 5 million years ago, before the Pan-Homo split,”

and that due to tool-use the human-brain specialized, probably making possible further changes in human neurology and cognitive behaviour (for evidence that there is a neurological link between tool-making and speech, see this post). It is interesting to consider what the cognitive preconditions were that enabled tool-making. The Oldowan technique, which

can be found from 2.6 million years ago. This technique is used to make cutting tools by breaking off sharp-edged flakes from a larger stone. This is achieved by striking a core stone with a hammerstone, thereby knocking flakes from the core (see Ambrose 2001).

This technique definitely requires intentional planning that isn’t bound to the here-and-now, but directed at the future. Also, and more important for language, it requires the ability for complex propositional thought. Thus the following conscious key cognitive mechanisms found in language are also necessary for tool-making and thus already existed 2.6 million years ago:

1. Predication: the same referent (core stone), can be subject of different predications, a structure that can be called “Topic-Comment”-structure (see also this post):

George (Topic) is eating brains (Comment) / George (Topic) is a Zombie (Comment) / George (Topic) is (Comment).

2. Qualification of predications that have already been made and higher-order temporal hierarchical ordering.

To wit, what this basically means is that both in linguistics and tool-making you first have an initial structure which you change by commenting/acting on it. This new structure can then be the topic of new comments or actions, and the new structure arising from these computations/ actions can again be the topic of new predications and ad infinitum. Consider for example the sentence: The living homeless, who wanted money, had infested South Park, but then they went to California

A hierarchical behavioral sequence like toolmaking seems to have similar properties:

I don’t know about you, but for me this looks like recursion, the only difference being that for toolmaking the recursive operation are applied to a physical object, and for language they are applied to a mental object. However, if toolmaking requires intentional planning, there had to be at least some recursive mental operations that in mental action planning. This would mean that, pace Hauser et al. (2002), recursion is neither special to language nor recently evolved.

As Wunderlich writes in his (2006) paper “What forced syntax to emerge?”

"Both fast processing and mapping from hierarchical structure to temporal ordering, two other fundamental features of human language, can be attributed to progresses in the timing of actions necessary for producing and using hand axes, [as well as throwing] that is, to sensomotoric skills that could have been adapted for language.”

All this is made all the more exciting by converging evidence that combinatorial and hierarchical structure of any kind (be it linguistic, cognitive, or sensori-motor are constructed by the same part of the brain and via the same mechanisms:

“Similarities exist between the architecture for sentence structure and blackboard architectures for combinatorial structures in visual cognition, derived from the structure of the visual cortex” (van der Velde & de Kamps 2006: 1)

“Evidence is mounting that much temporally sequenced hierarchical structure is constructed by the same part of the brain – roughly Broca’s area and subcortical areas connected to it – whether the material being assembled is language, dance (Lieberman 2005: 297), hand movements (Lieberman 2005: 294; Wilkins 2005: 279), or music (Patel 2003). Nor, within language, is Broca’s area confined to syntax, as often asserted: it also appears to play a role in phonological and semantic combinatoriality, possibly in distinct though overlapping subareas (Hagoort 2005; Poeppel and Embick 2005)" (Jackendoff 2007: 388)

“On the basis of all these results, it can be hypothesized that [the recursive morphosyntax of modern language] is the computational output of a cortical premotor network originally evolved to control/represent the hierarchical structure of goalrelated action When in evolution, selective pressure led to the emergence of language, the same neural circuits doing computations to control the hierarchy of goal-related actions were ‘exploited’ to serve the newly acquired function of language syntax. A similar functional overlap between action and language acquisition is indeed evident during children’s development, i.e. children parallel their capacity to master hierarchical complexity both in the domain of language and goal-related action.“ (Gallese 2007: 666)”

That’s it for today. In my next post I will continue my summary of Wunderlich’s presentation.

References:

Ambr Ambrose, Stanley H. 2001. Paleolithic Technology and Human Evolution. Science 291, no. 5509 (March 2): 1748-1753. doi:10.1126/science.1059487.

Dubreuil, Benoît (2008): “What do modern behaviours in Homo sapiens imply for the evolution of language?”, in A. D. M. Smith, K. Smith, and R. Ferrer i Cancho (eds.), The Evolution of Language. Proceedings of the 7th International Conference (Evolang 7), World Scientific, 99-106.

Gallese, Vittorio (2007). Before and below 'theory of mind': Embodied simulation and the neural correlates of social cognition. Philosophical Transactions of the Royal Society B-Biological Sciences 362 (1480):659-669

Hagoort, Peter (2005). On Broca, brain, and binding: a new framework. Trends in Cognitive Sciences 9: 416–423

Hauser, Marc D., Noam Chomsky and W. Tecumseh Fitch (2002). “The Faculty of Language: What Is It, Who Has It, and How Did It Evolve?” In: Science 298, 1569-1579.

Jackendoff, Ray (2007): Linguistics in Cognitive Science: The State of the Art, The Linguistic Review 24, 347-401.

Lieberman, Phillip (2005): The pied piper of Cambridge. The Linguistic Review 22: 289–302.

Lonsdorf, Elizabeth V., and William D. Hopkins. 2005. Wild chimpanzees show population-level handedness for

tool use. Proceedings of the National Academy of Sciences 102, no. 35 (August 30): 12634-12638. doi:10.1073/pnas.0505806102.

Patel, Aniruddh D. (2003). Language, music, syntax, and the brain. Nature Neuroscience 6: 674– 681.

Pinker, Steven & Paul Bloom (1990). “Natural Language and Natural Selection.” In: Behavioral and Brain Sciences 13.4: 707-726.

Poeppel, David, and David Embick (2005). Defining the relation between linguistics and neuroscience. In Twenty-first century psycholinguistics: Four cornerstones, A. Cutler (ed.), Hillsdale, NJ: Erlbaum.

Van der Velde, F. & de Kamps, M. (2006). Neural blackboard architectures of combinatorial structures in cognition. In: Behavioral and Brain Sciences, 29, 1-72.

Whiten, Andrew, Victoria Horner & Frans B. M. de Waal. 2005. “Conformity to Cultural Norms of Tool Use in Chimpanzees.” Nature 437: 737-740.

Wilkins, Wendy K. (2005). Anatomy matters. The Linguistic Review 22: 271–288.

Wunderlich, Dieter (2006): “What forced syntax to emerge?” In H.-M. Gärtner et al. (eds.) Between 40 and 60 puzzles for Krifka. ZAS Berlin

Our Imperfect Categorizing Minds

There's a cool talk over at Bloggingheads.tv featuring Carl Zimmer and linguist/cognitive psychologist Gary Marcus, who talks about his new book“ Kluge: The Haphazard Construction of The Human Mind.” The talk features some really cool insights into the short-comings of the human mind that are due to the fact that evolution is a tinkerer without foresight who always builds on the foundation of old things. One of the subsections is titled: "Noam Chomsky meets the genome" and you learn why college students respond differently if they are first asked how they see their life in general and then are asked how many dates they had in the last year than if they are asked the other way around.

Also, Larry Barsalou and three of his colleagues have an opinion piece in the latest Trends in Cognitive Sciences (Glushko et al. 2008) called "Categorization in the Wild" (you can find the draft here), in which they argue that individual and insitutional catgeorization should be a new focus of research into the cognitive phenomonon of categorization in general.

Glushko et al. argue that until now most scientists have focuse on cultural categorization, that is

"categories shared by a culture and associated with language"

Such cultural categories are the shared storage of categories that we acquire by growing up in a culture and interacting with other people. They exist for basicall all kinds and components of experience and shared imagination, such as objects, events, mental states, properties, funerals, games, zombies, "parks, serenity, blue and above".

How cool their proposal to set a new focus on two other modes of categorization actually is only becomes apparent when they reveal what they mean by these two terms:

Individual categorization: " occurs when someone creates an idiosyncratic classification system primarily for his or her own use, for example, when creating categories to organize locations where food can be gathered, objects in a garage, CDs in a music collection, websites in the favorites list of a browser, etc."

This means that the way I organize my bookmarks, label my posts, categorizes my CDs (by Genres and then in alphabetical order) books, tagging, or anytings else is about to become a research area of the cognitive sciences. How cool is that? But they even go further:

"Institutions engineer classification systems explicitly to serve institutional goals, typically requiring considerable time and resources to develop, maintain and apply."

In their view, institutional categorization consists of things like taxonomies, e.g. the Manual of Mental Disorders, the Period Table, or the Human Genome. But where it gets really interesting is where the three modes of categorization intersect. For example, Glushko et al. look a the photo-sharing website flickr.com, which as they argue shows "how individual classification systems can evolve beyond a single individual to a group," because people can join groups, tag their photos with common labels, interlink them, thus creating a new category system through the interaction of multiple agents. They even compare this process to that of pidginization and creolization, which means that lolcats are within the reach of cognitive science. Yay!

see more crazy cat pics

The Cognitive Foundations of Perspective

In my last three post I have highlighted convergences between the arguments made by German linguist Wilhelm Köller in his 2004 book “Perspektivität und Sprache” (Perspectivity and Language”) and findings in the general area of cognitive science.

In this post, I want to dig a little deeper, and ask what happens when we engage in discourse in regard to the cognitive representations that are established. Köller argues that through the use of language we create a shared ‘systemic space’ (a term he takes over from the German art historian Erwin Panofsky) a virtual, conceptual model of what we are talking about. We can then create and direct attention to certain proposition in this shared systemic space, thereby advertising a certain perspective on the world, and highlighting relevant information. Köller bases this view of language on German psychologist and linguist Karl Bühler’s (1934) notion of the “Deictic/Symbolic field” which we construct, and wherein we place and transport referential semantic messages, and which basically can be illustrated like this:

Bühler calls this the ‘coordinate system of subjective orientation’. The O represents the ‘Origopoint’, the point of origin for all referential messages, and is also called the “I-here-now-Origo”, because from this point of view/perspective the sender refers to thing in the world, and introduces new referents into the discourse. Köller adopts this view of language, but adds to it the perspectival and attention-piloting nature of discourse.

In sum, in Köller’s view Language is:

1. a means to create a shared, ‘virtual’ systemic space
   
2. a means to transfer relevant propositions in to the systemic space and
   
3. a means to focus and pilot attentions and thus to
   
4. create perspective
   

This view of mental representations as virtual, internal models of some state of affairs in the world is echoed in a variety of other proposals in cognitive science.

First, and most importantly, Michael Tomasello and his colleagues from our beloved Max Planck Institute for Evolutionary Anthropology argue for the importance of Shared Intentionality, in human cognition, that is

“the ability to participate with others in collaborative activities with shared goals and intentions” (Tomasello et al. 2005: 675).

In order to both communicate or collaborate, it is necessary that:

“each participant cognitively represent both roles of the collaboration in a single representational format – holistically, from a “bird’s-eye view,” (Tomasello et al. 2005: 681).

Thus, we need to have the knowledge of that there exists a “shared space of common psychological ground” (Tomasello & Carpenter 2007: 121).
This means that the most fundamental aspect of human cognition that enables joint attention and shared intentional actions is the ability to cognitively represent a “shared space of meaning” (Moll & Tomasello 2006: )/ a ‘systemic space’ from a central perspective (Köller 2004).

Dan Dennett (1996) also holds that one of the major feats of human cognition is the ability to build virtual models of reality, especially the ability to build rich intentional models of yourself and others. In this virtual model, you can take the physical stance, the design stance, or the intentional stance toward the systems created and basically see what happens.

In addition, Bickerton (1990) argues that the most special trait of human cognition is the ability to entertain counterfactual propositions. To give you an example in the vein of Köller (2004): If I say something like:

“There aren’t any Zombies in this room,”

not only do I introduce the concept of ‘Zombies’ into the systemic space, but negated Zombies:

Such counterfactual propositions needn’t necessarily be linguistic. In his 2006 Jean Nicod Prize lecture, Michael Tomasello gave the example of a child always wearing a belt when it goes for a walk. When the child and her mother go out of the house, and the mother then sees that the child doesn’t have his belt on, but only points to the child’s waistband, the child goes ‘Ooops’ , goes back inside and fetches the belt. Mother and child thus communicate nonverbally about a counterfactual proposition based on mutual knowledge/common ground about a conventionalized set of actions. Bickerton proposes that this ability is syntactically structured and enables us to manipulate, physical and virtual events, objects, and processes in general.

Don Ross (2007), reviewing Dennett’s and Bickerton’s proposals, argues that on this view language is a means to stabilize ‘referential fixed points’ in these virtual spaces. So on the one hand language can be seen as cognitive aid or artifact which enhances cognitive representations via conceptual labeling, and on the other hand it can be seen as a means of introducing fixed points into the virtual shared systemic space of joint attentional discourse.
Ross then draws our attention to the fact that we also introduced ourselves into these virtual spaces, thus ‘narrating’, and thus creating our selfhood and our identity both in private mental representation and shared intentional discourse.

Suddendorf & Corballis (2007) have similar ideas about the importance of self- and other-projection into virtual spaces as a method of ‘Mental Time Travel’, which enables us to plan and adapt to possible future stages of the world as well as future need by learning from and re-experiencing the past and projecting ourselves into future situations where we can practice various plans of action. They liken this process to a theater production, as the necessary precondition for virtual planning and decoupled thinking processes is a virtual systemic space, or, if you go with their theater-metaphor, a stage. According to Suddendorf & Corballis (2007), further necessary components of Mental Time Travel are:

• a declarative database or script from which you can infer how to act in a given situations (i.e. the playwright),
  
• the ability to represent yourself and others realistically, ergo a Theory of Mind (i.e. the actors),
  
• the ability to create an adequate physical context in which the mental representation can operate (the set),
  
• the motivation and ability to practice and rehearse future actions in the virtual space.(the director)
  
• the ability to voluntarily control and execute the ‘best plan’ to achieve the future goal, which is relatively ‘rational’, and decoupled from present stimuli and neeeds. (The executive producer)
• and additionaly, many MTTs are expressed publicly via language: "More generally, humans use language to exchange and complement their mental travels into the past and their ideas about future events, as well as to cooperatively coordinate plans and strategies" (Suddendorf & Corballis 2007: 310) (The broadcaster)
  
  

Virtual internal modeling can of course also seen as a solution to the exploration-exploitation trade-off as well as to the unstable environment homo is said to have emerged from.

Interestingly, there is additional support for this internal modeling hypothesis namely, from robotics.

As you may recall, In my first post I briefly described an experiment done by Floreano and Nolfi (1996) in which a robot evolved to internally represent the area surrounding him, thus enabling him to act in relation to the virtual internal body-related map he had created.

Even more intriguing, Bongard et al. (2006) describe a robot which adapts to an unstable environment as well as injuries (such as losing a leg) by continuous internal self-modelling.

Of course, the notions of internal systemic representation is practically all-pervasive throughout the field of cognitive science, as echoed for example in the controversy between Theory-Theory and Simulation Theory proponents in Theory of Mind research, as well as the ongoing controversies regarding the relation between mirror neurons and mental imagery, and practically every aspect of cognition, but I find the combination of internal representational spaces, shared intentionality and perspective incredibly, and I write a bit more about their cognitive and linguistic foundations in my next post. I’ll also try to stay more down to earth in my next post.

References:

Bickerton, Derek .1990. Language and Species. Chicago: University of Chicago Press,

Bongard, J. V. Zykov, & Lipson, H. 2006. “Resilient Machines Through Continuous Self-Modeling” Science 314: 1118-1121.

Bühler, Karl. 1934. Sprachtheorie. Die Darstellungsfunktion der Sprache. Jena: Gustav Fischer.

Dennett, Daniel C. 1996. Kinds of Minds. New York: Basic Books.

Floreano, Dario, and Francesco Mondada. 1996. “Evolution of homing navigation in a real mobile robot”, IEEE Transactions on Systems, Man, and Cybernetics – Part B: Cybernetics 26:396–407.

Köller, Wilhelm. 2004. Perspektivität und Sprache. Zur Struktur von Objektivierungsformen in Bildern, im Denken und in der Sprache. Berlin/ New York: de Gruyter.

Moll, Henrike, & Michael Tomasello. 2007. Co-operation and human cognition: The Vygotskian intelligence hypothesis. Philosophical Transactions of the Royal Society 362: 639-648.

Ross, Don. 2007. H. sapiens as ecologically special: what does language contribute? Language Sciences 29.5: 7 10-731.

Tomasello, Michael.1999.: The Cultural Origins of Human Cognition. Cambridge, Massachusetts; London, England: Harvard University Press

Tomasello, Michael and Malinda Carpenter. 2007. Shared Intentionality. Developmental Science 10:1:121-125.

Tomasello, Michael, Malinda Carpenter, Josep Call, Tanya Behne, and Henrike Moll. 2005. “Understanding and Sharing Intentions: The Origins of Cultural Cognition.” Behavioral and Brain Sciences 28.4: 675-735.

Suddendorf, Thomas & Michael C. Corballis. 2007. The Evolution of Foresight: What is mental time travel, and is it unique to humans? Behavioral and Brain Sciences 30.3: 219-313.

Merry Christmas! (& Memes & Mirror Neurons)

So this is my last post before I’ll be heading home over the holidays.

As I tried to show in this post, it seems that the ability to imitate is crucial for learning a language. Most importantly, it also seems to be a major foundation of all human culture.

There is whole lot of research done in this field and there are hot discussions about the relationship between mirror neurons, imitation, Theory of Mind, language acquisition, language evolution, human cultural evolution, etc.

Memetics, for example, sees our ability to adopt cultural and cognitive patterns of behavior as mediated by our imitative abilities (Blackmore 2007). In 2005 Nick Chater and Susan Hurley published and edited Perspectives on Imitation: From Neuroscience to Social Science, a two volume monstrosity with 1024 pages covering Mechanisms of Imitation, Imitation in Animals, Imitation and Human Development as well as Imitation and Culture, This underlines the renewed appreciation of the importance of imitation as a fundamental property of cognition, instead of an uninteresting low-level phenomenon. (McEwen 2007)

The notion of a link between human culture and cognition on the one hand, and imitation and learning on the other, is of course not new – as we have seen in the passage of Puttenham’s Arte of Poesie I quoted in my last post on imitation. If you look up “imitative” in the OED, you find a 1777 quote by David Hume, who wrote that

“The human mind is of a very imitative nature”

as well as the assessment that

“At present, we are become an imitative, not to say a mimic, race” (in Gifford’s 1827 introduction to the plays of John Ford).

We can trace this notion as far back as to Aristotle, who in his Poetics, claimed that mimesis, the representation or imitation of a state in the world in the form of action, art, or speech, is a fundamental property of human cognition. Interestingly, he describes imitation as an “instinct of our nature” and writes that:

“the instinct of imitation is implanted in man from childhood, one difference between him and other animals being that he is the most imitative of living creatures, and through imitation learns his earliest lessons;”

As it seems, Aristotle’s assessment is indeed backed up by behavioral evidence. 30 years ago, Meltzoff and Moore (1977) found that 12 to 21-day old infants were able to imitate the experimenter’s facial gestures of mouth opening, lip protrusion and, tongue protrusion, as well as manual gestures such as the opening of the hand. In a follow-up study, they showed that even newborns who are less than 72 hours old are able to imitate these gestures (Meltzoff & Moore 1989). Interestingly, this tendency seems to disappear between two and three months of age. This is probably explained by the fact that autonomously controlled, spontaneus face-to-face social interaction (as a baby smiling at her mother, for example) kicks in around this time and infants start to communicate intentionally. (Myowa-Yamakoshi et al. 2004: 441)

Now is this a uniquely human trait?

Quite astonishingly, Myowa-Yamakoshi et al. (2004) found that chimpanzees who are less than 7 days old are also able to imitate the gestures of tongue protrusion, mouth opening, and lip protrusion.

As in humans, this tendency disappeared at two months of age. The authors conclude that
“like human neonates, chimpanzee neonates are born with the ability to match visually perceived oral gestures with a proprioceptive motor schemes .“ (Myowa-Yamakoshi et al. 2004: 440).

So what about other primates? Previously it was thought that only humans and apes posses these neonatal skills, but it seems that at 3 days of age, rhesus macaques are able to imitate lip smacking and tongue protrusion (Ferrari et al. 2006), facial gestures which later become important in social interaction (Gross 2006)

However, the macaques showed this behavior only a few days after birth and after that it vanished. This may be due the fact that motor as well as cognitive development in macaques is much more rapid in macaques than in the higher apes. It thus seems that the more advanced human imitation capacities built on these imitative foundations that must have been present at the time our lineage split from that of macaques, namely 25 million years ago.
Interestingly, macaques were the first species in which mirror neurons – neurons that fire both during the performance as well as during the observation of an action – were found, and hopefully there will be more studies on the neural basis of imitation in macaques.

Quite Remarkably, adult macaques are also able to notice when someone else is imitating their actions (e.g. a human experimenter), but it is unclear whether they are able to grasp the fact that the experimenter is intentionally imitating them, or if they just recognize it implicitly (Paukner et al. 2005). In the second case, the macaques would just exhibit this knowledge via metacognition, i.e. the awareness of some inner state, something which macaques seem to be able to do.
Evidence for metacognition in macaques comes from research done by H.S. Terrace and his team, who taught their macaques a matching game, and then offered them the options to either play the game and get some food if they won and nothing if they lost, or the option to not play the game and get less food. Interestingly, sometimes the macaques chose the latter, option, and sometimes they chose the former, but if they chose the first option, they performed pretty well, indicating that the macaques had a means of assessing how accurate they were at getting the game right. In another experimental setting, macaques also learned to ask for hints if they otherwise had to solve the problem by trial and error, again indicating that they had some metacognitive means of assessing what they knew and what they didn’t (Kornell et al. 2007).
It is much more questionable if macaques exhibit metarepresentation, i.e. the awareness of mental states of others (Hurford 2007: 35)

This of course taps into the discussion of which primates exhibit a Theory of Mind, or an awareness of the mental states of others, and whether the transition from nonhuman to human minds should be seen as continuous or discontinuous. The two main camps in this debate are that of Povinelli and his colleagues on the one side, who argue that nonhuman primates do not exhibit abstract inferences of others mental states, and that there is a qualitative gap between human and nonhuman cognition (Povinelli & Vonk 2003), and Tomasello and his team on the other side, who argue that chimpanzees are able to understand some psychological states to a certain degree, and that human cognition should be seen as much more continuous (Tomasello et al. 2003). It seems as if Povinelli and his colleagues are just about to launch their next major attack (to be publish in the journal Behavioral and Brain Sciences in 2008) awe-inspiringly called “Darwin’s mistake: Explaining the discontinuity between human and nonhuman minds” . As BBS consists of the target article along with 25 or so commentaries other researchers, I’m really interested in how this will turn out.

For now it is quite interesting enough (and also somewhat amusing) how both parties assess the importance of the debate:

Whereas Tomasello et al. (2003) claim that:

“At issue is no less than the nature of human cognitive uniqueness” (Tomasello et al. 2003: 156)

Povinelli et al. take a much more relaxed stance:

"the idea that theory of mind is the ‘holy grail’ of comparative cognition needs to be abandoned. Neither chimpanzees nor evolutionary theory will be insulted if the very idea of ‘mental states’ turns out to be an oddity of our species’ way of understanding the social world.“ (Povinelli et al. 160)

Dang, I still haven’t posted about either the Lyons et al. (2007) paper or the genetic differences between humans and chimpanzees. But I will do so next year. Promise. Cross my Heart and Hope to Die. As an apology, here’s a link to a great song by Jonathan Coulton, performed live in front of an audience of (judging by the chorus) zombies. Gotta love that.

So merry Christmas & Happy New Year, and see you in 2008.

References:

Blackmore, Susan. 2007. “Those dreaded memes: The advantage of memetics over “symbolic inheritance.” Behavioral and Brain Sciences 30.4: 365-366.

Ferrari PF, Visalberghi E, Paukner A, Fogassi L, Ruggiero A, et al. (2006) Neonatal imitation in rhesus macaques. PLoS Biol 4(9): e302. DOI: 10.1371/journal.pbio.0040302

Gross L (2006) Evolution of Neonatal Imitation. PLoS Biol 4(9): e311 doi:10.1371/journal.pbio.0040311

Hurford, James M. 2007. The Origins of Meaning: Language in the Light of Evolution. Oxford: OUP.

Kornell, Nate, Son, Lisa K. and Herbert S. Terrace. 2007. “Transfer of Metacognitive Skills and Hint Seeking in Monkeys. Psychological Science” 18.1: 64-71.

McEwen, Fiona. 2007. “Review: Perspectives on Imitation: From Neuroscience to Social Science.” Mind & Language, 22.2 April : 207–213

Meltzoff AN, Moore MK .1977. Imitation of facial and manual gestures by human neonates. Science 198: 75–78.

Meltzoff AN, Moore MK (1989) Imitation in newborn infants: Exploring the range of gestures imitated and the underlying mechanisms. Developmental Psychology 25: 954–962

Myowa-Yamakoshi M, Tomonaga M, Tanaka M, Matsuzawa T .2004. “Imitation in neonatal chimpanzees (Pan troglodytes).” Developmental Science 7: 437–442

Paukner A, Borelli E, Visalberghi E, Anderson JR, Ferrari PF (2005) Macaques (Macaca nemestrina) recognize when they are being imitated. Biology Letters 1: 219–222.

Povinelli, D.J. and Vonk. J. (2003) Chimpanzee minds: Suspiciously human? Trends in Cognitive Sciences, 7.4, 157–160.

Tomasello, Michael, Josep Call and Brian Hare. 2003. Chimpanzees understand psychological states – the question is which ones and to what extent. Trends in Cognitive Sciences, 7- 153-156.

A Zombie’s Inquiry Into the Evolution of his Most Favorite Meal III: What are Humans Good at?

Except running away from poor, starving zombies, that is (– the Selfish Bastards!)

A while back Juan Uarigerika wrote an article in Seed magazine about language evolution. In it he proposed that maybe language is responsible for most of our especially human intelligence, as well as precursor for our more advanced sensorimotor capacities, and that in the end it could turn out that research into our cognitive architecture would come up with the formula ‘Finch + Chimp = Human.’ Uarigerika’s article is written, for a magazine, so it’s clear that he doesn’t really do much in order of presenting evidence and arguments in a really ‘scientific’ way but rather presents his ideas in a in a popular style, but still I think his proposal is quite problematic (Mark Liberman has written a nice rebuttal of Uarigerika’s reductionsit view over at Language Log)


moar funny pictures

A better way to study the differences between human and animal cognition effectively is to compare differences and similarities of certain cognitive traits and analyze how these may come about and how the cognitive function in question is enabled in the given organism.
In a massive comparative study, Hermann et al. (2007) had Chimpanzees, Orangutans and 2.5 year-old children perform various task and then evaluated and compared the species’ qualitatively differing performances. The tasks were divided into two “domains”, physical and social, each consisting of three “scales” (physical: space, quantitiy, causality; social: social learning, communication, theory of mind). Among the 20 tasks there were such things as “using a stick in order to retrieve a reward which is out of reach.” (causality), “Locating a reward.“ (space), “Solving a simple but not obvious problem by observing a demonstrated solution” (social learning), “Following an actor’s gaze direction to a target” or “Understanding what an actor intended to do (unsuccessfully” (both Theory of Mind).

On average, the results of humans and chimpanzees were very similar in the physical domain, and scored much higher than the orangutans. In the social domain, however, humans outperformed chimpanzees and orangutans by far. The non-human apes were right only half as often as the human children. This means that chimpanzees outcompete orangutans when it comes to things as causal reasoning and quantities, but are equally bad at imitating others or assessing their intentions. Whereas in the physical tasks chimps sometimes performed better than humans (e.g. Tracking of a reward after location changes or Using a stick in order to retrieve a reward which is out of reach, something where human children performed much worse than both chimps and orangutans), interestingly

“Children were better than both ape species at the three causality tasks in which a judgment must be made before manipulation or choice, whereas chimpanzees were better than children and orangutans at the one causality task involving active tool use.” (Hermann et al. 2007:1362)

as well as in regard to inhibitory control, which could partly be due to the prominence and dominance of prefrontal circuitry in the human brain and its importance in cognitive control— “the ability of the brain to coordinate processing mong its millions of neurons in order to direct them toward future goals.” (Miller et al. 2002: 1131) — which I alluded to in my earlier posts.

Chimps and orangutans both performed a little better than human children when it came to “Producing communicative gestures in order to retrieve a hidden reward.”, which was the only social domain task in which the difference between the human and non-human primates wasn’t significant. The authors conclude that

“the current results provide strong support for the cultural intelligence hypothesis that human beings have evolved some specialized social-cognitive skills (beyond those of primates in general) for living and exchanging knowledge in cultural groups: communicating with others, learning from others, and “reading the mind” of others in especially complex ways“ (Hermann et al. 2007: 1365).

But they caution against the conclusion that social intelligence as a whole, or a “Theory of Mind-module” is the distinctive property separating humans, chimps and orangutans. Instead, taking into account that human children were better than chimps in causality tasks that didn’t include the active manipulation of tools, they speculate that

“what may be distinctive is the ability to understand unobserved causal forces in general, including (as a special case) the mental states of others as causes of behavior. Even in this case, however, it is a plausible hypothesis that understanding hidden causal forces evolved first to enable humans to understand the mental states of other persons, and this generalized only later to the physical domain.”

Which fits well with the evidence that humans are especially good at displaced mental and conceptual simulation (Miller et al. 2002, Barsalou 2005) and such things as mental time travel (Gilbert & Wilson 2007).
In my next post I will expand a bit on complementary approaches to comparing human and other non-human primate cognition and differences in general.

References:

Barsalou, Lawrence W. 2005. “Continuity of the conceptual system across species.” Trends. Cog. Sc. 9.7: 309-311.


Gilbert, Daniel T. and Timothy D. Wilson. 2007. “Prospection: Experiencing the Future.” Science 317: 1351-1354.

Hermann, Esther Josep Call, María Victoria Hernández-Lloreda, Brian Hare, and Michael Tomasello. 2007. “Humans Have Evolved Specialized Skills of Social Cognition: The Cultural Intelligence Hypothesis” Science 317: 1360-1366.


Miller, Earl K., David J. Freedman and Jonathan D. Wallis 2002. “The Prefrontal Cortex: Categories, Concepts and Cognition.” In: Phil. Trans. R. Soc. Lond. B 357: 1123–1136

A Zombie’s Inquiry Into the Evolution of his Most Favorite Meal II

In my last post I listed some important factors in the evolution of the human brain, or better imagined what a zombie evolutionary biologist, named George, might dig up when investigating the evolutionary path of his Dinner Nr. 1. As Terrence Deacon (1997) puts it, there is no escaping the fact that human brains are unusually large. There are several factors why humans could develop large brains, but what is still at stake is the question why they actually did, and how they came into a position that allowed them to devote so much energy to a walnut-shaped pink lump of tissue with the consistency of a half-baked egg.
This question is critical, because organisms do not normally develop new traits just because they can. This of course also happens, in combination with random genetic drift and populations bottlenecks. But because evolution is a ‘miserable and greedy tinkerer’, or put more nicely, an economical process, it is highly unlikely that it produces needless and incredibly complex capacities that are extremely costly to maintain. As a consequence,

“some proportionately beneficial advantage must have driven brain evolution against the steep selection gradient created by the high costs of brain tissue.” (Dunbar & Shultz 2007)

Why, Dunbar and Shultz ask further, do primates have so much bigger brains than squirrel, with both facing about the same foraging decisions? (Dunbar & Shultz argue that ecological explanations fail to account for this differences, but their Chimpanzee-Squirrel dichotomy nevertheless is a bit hyperbolical, given that, among primates, those whose diet includes insects and fruits show higher encephalization rates than leaf-eaters, and strategic hunting and gathering of food and prey places additional demands on navigational, representational and other cognitive skills. However, their general argument is still valid. (Park et al. 2007))

To shed light on this issue, we can divide the big picture into several smaller ones. Useful questions include: What are we good at? Split into What are we (primates) good at? And What are we (humans) even better at than other primates? What could the ecological niche favoring big brains in humans have looked like? How exactly does our brain differ from that of other primates?
These questions essentially depend on comparative ethology (how do our minds work compared to how the minds of other animals work?), comparative (neuro)anatomy (On which evolutionary foundations are our modern cognitive abilities, and other phenotypic traits built upon?), and the kind of scenario we envision or infer from these observations togther with the fossil record and other lines of evidence. Of course it is also crucial what we think what the most salient and essentially aspects of our ancestors were. Do we see our ancestor as “Man the Tool Maker”, “Man the Hunter” or “Man the Social Animal”, or just as “Man with the extraordinarily big & expensive (and extremely delicious, George might add) brain”.

Well, of course Man should probably rather be seen as “Man the cooperative, competitive, tool-making, hunting, {…}, articulate social animal.” And all of these property probably contributed (co-evolutionary, we might say, without adding much in terms of explanatory adequacy) to our cognitive abilities and brain size, but in which order? And which driving forces were a little more pushy than others?
As Cheney & Seyfarth (2007) have show in baboons, interactions in primate groups are cognitively highly demanding and require sophisticated representational and predictive abilities, because of the intricate and complex networks and ‘friendships’ they inherit. Thus rising complexity in social life could be seen as a key selection pressure in the evolution of cognitive abilities in primates in general, and especially in humans. (Lewin 2005: 220f.)
Depending on which aspect one wants to stress, this correlations can be described in different terms. Scholars who wanted to stress the competitive aspect of social life dubbed it the “Machiavellian Intelligence Hypothesis.” (Byrne & Whiten 1988: who themselves, interestingly, didn’t want to stress the competitive aspect by giving the hypothesis the title). Now it is most widely called the “Social Brain Hypothesis” to emphasize the general complexity of primate groups including all arising affordances (Dunbar 1998, Dunbar & Shultz 2007).
Unfortunately, this is still rather vague. To get a clearer picture, it is important to make explicit the advantages and disadvantages of large social groups and the specific problems which need to be solved. However, group size indeed seem to contribute advantageously to genetic fitness by minimizing predation risk, but paired with greater ecological and reproductive competition and suppression, affording higher behavioral flexibility (Dunbar & Shultz 2007). Brain expansion theories stressing the importance of ’technological intelligence’ as a driving force. (without neglecting the importance of social factors, but seeing the latter as less crucial). According to these views, the ‘behavioral drive’ for cultural transmission and innovation is more frequent in species with large brains. As a consequence these species are led to exploit the environment in new way, opening up new possibilities regarding new selective pressures. ´(Reader and Laland 2002). Certainly, these tendencies were important, but where do they come from? Big-brains seem to be a prerequisite for ‘technological intelligence’, but how did these evolve in the first place? Rather it seems probable that

“Although innovation, tool use, and technological invention may have played a crucial role in the evolution of ape and human brains, these skills were probably built upon mental computations that had their origins and foundations in social interactions.” (Cheney & Seyfarth 2007: 283).

Supporting Reader and Laland’s emphasis on the importance of technological aspects on human cognitive evolution, Tomasello and his colleagues propose that human’s advanced Theory of Mind-skills were amplified not in the context of intention-reading present in great apes, but rather during learning and imitation of hierarchical planned and structured tool-making and tool-using. (Tomasello et al. 2005: 687). I’m not sure whether George would like this speculation. Probably, he would argue this to be a ‘just-so story’ and propose that all scientist coming up with these should be eaten. So thank God scientists are not really zombies, I wouldn’t miss the Max Planck Institute for Evolutionary Anthropology in Leipzig, Germany (and especially its co-director) for anything in the world (OK, except for the really important things such as love, life, family, donuts.

I haven’t addressed much of the questions stated in the beginning, especially What we as humans are especially better at than other primates. I will come to this issue in my next post (relying again on research done by scientists from the Max Planck Institute for Evolutionary Anthropology, so again, glad they haven’t been eaten.)

References:

Cheney, Dorothy L. and Robert M. Seyfarth. 2007. Baboon Metaphysics: The Evolution of a Social Mind. Chicago: University of Chicago Press.

Deacon, Terrence William 1998. The Symbolic Species. The Co-evolution ofLanguage and the Brain. New York / London: W.W. Norton

Dunbar, Robin I.M.1998.“The Social Brain Hypothesis” Evolutionary Anthropology 6: 178-190.

Dunbar, R. I. M. and Susanne Shultz. 2007.“Evolution in the Social Brain” Science 317: 1344-1347

Park, Min S., Andrew D. Nguyen, Henry E. Aryan, Hoi Sang U, Michael L. Levy, Katerina Semendeferi. 2007. “Evolution of the Human Brain: Changing Brain Size and the Fossil Record.” Neurosurgery 60:555–562.

Reader, S.M. and K.N. Laland. 2002. “Social Intelligence, innovation, and enhanced brain size in primates” PNAS 99: 4436-4441

Tomasello, Michael, Malinda Carpenter, Josep Call, Tanya Behne, and Henrike Moll. 2004. “Understanding and Sharing Intentions: The Origins of Cultural Cognition.” Behavioral and Brain Sciences 28

Zombies have Taste

In my last post I wrote about the fact that human brains are selfish energy-hungry little bastards, which makes the stuff they’re made of extremely ‘expensive tissue’ (Aiello & Wheeler 1995). This means that zombies have a quite extraordinary taste, equivalent to a caviar-gourmet (either that, or they are ‘informavores’ just like we are (Miller 1991)).
Now imagine (instead of the oft-cited martian scientist) a zombie-evolutionary biologist (Insert joke about the parasitic tendencies of the ‘mindless new atheism’ and/or Intelligent Design, the Idea of theistic evolution, greedy reductionism, Evolutionary Psychology or whatever floats you boat here) puzzling over the evolutionary emergence of his most favorite meal. Let’s take it for granted that our zombie-scientist is not easily satisfied by zombie-centric evolutionary concepts, just as Steven Pinker warns us that, if Elephants were the most culturally advanced species (well, and maybe they are, who knows), their evolutionary biologist (albeit only the bad ones) would probably search for the evolutionary path that inevitably climaxed in the highest form, the evolutionary optimum of trunkitude. Let’s also assume our zombie-scientist isn’t a friend of ‘just-so’ stories like ‘humans evolved bigger brains to run away from zombies more effectively’. Assuming, too, that human scientist like Aiello, Wheeler, Dunbar and others weren’t eaten before publishing their caveats about the expensiveness of brain evolution and maintenance, or that some other zombie-scientists could hold back their hunger long enough to test human subjects before eating them, coming to similar conclusions as Aiello and others did – or, rather would have come if they hadn’t been eaten beforehand. Assuming this, we could be sure that our zombie-scientist would not regard the evolution of a ‘general being-eaten-avoidance intelligence’ as unlikely.

What then, our zombie-scientist, call him George, would ask, was the reason humans developed such large, specialized brains. Looking for homologues or convergent evolution in other (hopefully not entirely eat… I mean extinct) species, and considering what makes the human mind special. George could come up with a lot of possible hypotheses as driving forces and triggers of brain evolution, and other facts he would have a hard time to make sense of such as:

• positively selected genes involved in regulating (Microcephalin: Evans et al. 2005) and determining brain size (ASPM: Mekel-Brobov et al. 2005), development of the human neocortex (HAR1F: Pollard et al. 2006), and playing a part in progressive changes in cognitive abilities (Neuropsin: Li et al. 2004)
  
• 
  
• cooking, paired with gastrointestinal shrinkage (our intestinal tract is only 60% the size expected of a primate with similar size) may have saved energy from digestion which in turn could be used to help fuel the brain. Together with the possible role of meat and more efficient upright walking and running, this could have expanded the human energy budget significantly (Gibbons 2007)
  
• 
  
• supporting this hypothesis, AMY1, a gene improving the digestion of food containing starch, is found in much greater numbers in humans than in chimpanzees (Perry et al. 2007)
  
• 
  
• Correlations between group size and neocortex size (Dunbar 1993, Dunbar & Shultz 2007) on the one hand, and significant positive correlation between innovation, social learning, tool use and brain size on the other, (Reader and Laland 2002, Reader 2003), making it likely that social and technological innovative intelligence (mediated by social learning) both played a crucial and inseparable role in human brain evolution (Cheney & Seyfarth 2007)
  
• 
  
• The possibility that the ability to evolve fat babies was the precursor for the evolution of the big and metabolically expensive brain (The article proposing this hypothesis is called ‘survival of the fattest’, What a great pun! Er… or maybe not) . In a resting newborn baby, the brain consumes 74% of the baby’s energy intake. In a 4-6 months old baby the rate is 64%, further dropping during ontogenetic development until reaching a rate of about 23% in adults. And whereas in chimpanzee infants, there is virtually no body fat, in human infants body fat contributes about 11-14% of the baby’s weight (as does the baby’s brain) (Cunnane & Crawford 2003)
  

So one thing is clear: a stable high-energy food supply was essentially necessary for human brain development, as were the possibility for longer ontogenetic development (as often observed, human (and generally primate) newborns are pretty much helpless compared to newborns of other species, with some even able to walk following almost immediately after birth).
Another important aspect is the general tendency in mammals to develop bigger brains compared to other species (they are about 10 times ‘brainier’ than amphibians or reptiles). Then, humans are part of the order of primates, which (along with toothed whales) have bigger brains than other mammals. And among primates, monkeys and apes have the biggest brains. But, as I said, our brains are even three times bigger than that expected of an ape of similar size. Another factor is the fact that the pre-natal rapid brain growth observed in other species whose infants are relatively helpless continues post-natally in human babies for about twelve months instead of changing into a slower pace.
As a consequence, human infants are even more helpless than that of other primates. This requires a much greater devotion of time, energy and other resources from the parent’s side. (Lewin 2005: 217f., John L. Locke and Barry Bogin (2005) make a similar argument concerning the unique human life history and ontogenetic development, but extending it not only to brain growth in general, but also to the evolution of language).
Making such a list, George would probably have a lot of trouble to distinguish preconditions, epiphenomena, co-evolutionary processes and driving forces of brain expansion. In my next post I will try to shed some light on this issue (Of course I will fail even more grotesquely than someone who is not a complete layman, but I hope that I will at least clarify some points)

References:

References:

Aiello L.C. and P. Wheeler 1995. ”The expensive tissue hypothesis: the brain and the digestive system in human and primate evolution.” Current Anthropology 36:199–221

Cheney, Dorothy L. and Robert M. Seyfarth. 2007. Baboon Metaphysics: The Evolution of a Social Mind. Chicago: University of Chicago Press.

Cunnane Stephen C. and Michael A. Crawford. 2003. “Survival of the fattest: fat babies were the key to evolution.” Comparative Biochemistry and Physiology Part A: 136.1: 17-26

Dunbar, R.I.M. 1993. “Co-evolution of Neocortex size, group size and language in humans.” Behavioral and Brain Sciences 16.4: 681-735

Dunbar, R. I. M. and Susanne Shultz. 2007.“Evolution in the Social Brain” Science 317: 1344-1347

Evans, Patrick D., Sandra L. Gilbert, Nitzan Mekel-Bobrov, Eric J. Vallender, Jeffrey R. Anderson, Leila M. Vaez-Azizi, Sarah A. Tishkoff, Richard R. Hudson, Bruce T. Lahn “Microcephalin, a Gene Regulating Brain Size, Continues to Evolve Adaptively in Humans” Science 309: 1717-1720.

Gibbons, Ann. 2007. “Food for Thought.” Science 316. 1558-1560.

Lewin, Roger. 2005. Human Evolution: An Illustrated Introduction. Fifth Edition. Suffolk: Blackwell.

Locke, John L. and Barry Bogin. 2005. “Language and life history: A new perspective on the development and evolution of human language” Behavioral and Brain Sciences

Mekel-Bobrov, Nitzan, Sandra L. Gilbert, Patrick D. Evans, Eric J. Vallender, Jeffrey R. Anderson, Richard R. Hudson, Sarah A. Tishkoff, Bruce T. Lahn. “Ongoing Adaptive Evolution of ASPM, a Brain Size Determinant in Homo sapiens.” Science 309: 1720-1722

Li, Yi, Ya-ping Qian, Xiao-jing Yu,* Yin-qiu Wang, Ding-gui Dong’ Wei Sun, Run-mei Ma and Bing Su. 2004. “Recent Origin of a Hominoid-Specific Splice Form of Neuropsin, a Gene Involved in Learning and Memory.“ Molecular Biology and Evolution 21.11: 2111-2115.

Miller, G.A. 1991. The Science of Words. New York: W.H. Freeman

Reader, S.M. 2003. “Relative brain size and the distribution of innovation and social learning across the nonhuman primates.” The Biology of Traditions: Models and Evidence. Eds. D.M. Fragaszy and S. Perry, 56-93.

Reader, S.M. and K.N. Laland. 2002. “Social Intelligence, innovation, and enhanced brain size in primates” PNAS 99: 4436-4441.

Pollard, Katherine S., Sofie R. Salama, Nelle Lambert, Marie-Alexandra Lambot4, Sandra Coppens, Jakob S. Pedersen, Sol Katzman, Bryan King, Courtney Onodera, Adam Siepel, Andrew D. Kern, Colette Dehay, Haller Igel, Manuel Ares Jr, Pierre Vanderhaeghen & David Haussler. 2006 “An RNA gene expressed during cortical development evolved rapidly in humans.” Nature 443: 167-172.

Perry, George H, Nathaniel J Dominy, Katrina G Claw, Arthur S Lee, Heike Fiegler, Richard Redon, John Werner, Fernando A Villanea, Joanna L Mountain, Rajeev Misra, Nigel P Carter, Charles Lee, & Anne C Stone. 2007 “Diet and the evolution of human amylase gene copy number variation“ Nature Genetics Advanced Online Publication doi :10.1038/ng2123