Stupid Primates & Embodied Minds (or Stupid Minds and Embodied Primates?)

On a very cool episode of video blog blogginghead.tv’s “Science Saturday” called “Stupid Primates”, experimental philosopher Joshua Knobe and psychologist Laurie Santos discuss her work on the psychological shortcomings of humans and other primates. Her team’s idea is that we shouldn’t only look at the cognitive abilities we’re really proud of, like language, cooperation, and the ability to reason about other minds. Instead of trying to discover the evolutionary precursors of these abilities and looking at if and in which ways other species possess them, we should also look at the evolutionary foundations of the things we’re not so proud of, like our tendency to cheat and deceive, and especially our tendency to behave irrational and illogical.

Interestingly, monkeys also show some of the same irrational behavior as we do, such as cognitive dissonance and loss aversion. If you’re interested, you should really check out this episode.

If monkeys make some of the very same mistakes we do, this speaks for the interpretation that we make some of our mistakes because we are wired that way. For some arguments in a similar vein, you can also check out this discussion betwen science Journalist Carl Zimmer and psychologist Gary Marcus, author of Kluge. You can also check out Gary Marcus being interviewed by blogger and author Jonah Lehrer.

On a related note, there’s a really cool episode of the Brain Science Podcast, where cognitive psychologist Art Glenberg talks about embodied cognition. Glenberg’s main research focus are the bodily, “low-level” underpinnings of language comprehension. He’s done quite a lot of research on the ways language is grounded in action and embodiment, and how we use bodily states and our experience with the world to construct meaning. He is influenced by cognitive linguist George Lakoff’s work on metaphor and embodied language comprehension.

It should be noted that, the term “image schema”, i.e. a recurring stereotyped perceptual structure or pattern generated from experience with and exposure to the world and used to categorize and understand objects and events, which Glenberg attributes to Lakoff, was AFAIK coined by Lakoff’s collaborator Mark Johnson.

In 1980, Lakoff and Johnson wrote the very influential book “Metaphors We Live By”, looking at the intrinsic metaphorical structure of language as exemplified for example by the many WAR metaphors found when talking about conversation: I defended my position, He attacked my argument, etc. or in the ways we visualize Life as being a CONTAINER filled our emptied of essences: I’ve had a full life. Life is empty for him, Her life is crammed with activities, Get the most out of life, etc.

Lakoff & Johnson (1980) even go further and claim that this metaphorical structure also extends to the way our conceptual system is mapped out. Glenberg’s experiments give empircal support to this view. For example, he showed that people were better at understanding sentences like “he opened the drawer”, when they had to indicate whether the sentence makes sense by extending their arm in a manner similar to the movement described in the sentence then when they had to make a movement analogous to the movement of closing a drawer to indicate its correctness , and vice versa.

Glenberg also reports that he has submitted a paper together with Vittorio Gallese on the relation between the grammar of natural languages and the hierarchical structure of neural action systems. This sounds akin to the work of Phillip Lieberman, who claims that

“The supposed unique aspect of syntax, its “reiterative” productivity, appears to derive from subcortical structures that play a part in neural circuits regulating motor control.“ (Lieberman 2005),

especially stressing the importance of the basal ganglia in the production and evolution of language.

Interestingly, Gallese has also published a paper with George Lakoff, called “The Brain’s Concepts”, which focuses on the embodied, sensory-motor nature of conceptual structures and the role of mirror neurons in concept formation and language comprehension.

Anyways, check out the episode, I think it’s really worth it.

References:

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

Gallese Vittorio, Lakoff George (2005) The Brain’s Concepts: The Role of the Sensory-Motor System in Reason and Language. Cognitive Neuropsychology, , 22:455-479

Lakoff, George, and Mark Johnson (1980) Metaphors we live by. Chicago: University of Chicago Press

Perspectives on “Perspective” – Part I

Since in my previous posts on the phenomenon of perspective - i.e. the fact that we tend to view and (re)present thoughts and states of facts in the world in highly specifiy, perspectival ways, - I have mainly focused on the work of German linguist Wilhelm Köller and his (2004) book “Perspektivität und Sprache” (Perspectivity and Language) and how his thoughts relate to those of other linguists, developmental psychologists, cognitive scientists, etc., I wanted to represent more fully the work of some scholars whose work also focuses on the notion of perspective.

Scholars who make important contributions under the heading of perspective or perspectivity include, for example.:

- developmental and comparative psychologists Michael Tomasello and Henrike Moll from the Max Planck Institute for Evolutionary Anthropology,

- psychologist Carl F. Graumann, former Professor of Psychology at Heidelberg University, who died in 2007

- linguist Brian MacWhinney, Professor of Psychology at Carnegie Mellon University, Pittsburgh, Pennsylvania, USA

- developmental psychologist Josef Perner of the University of Salzburg, Austria

- cognitive linguist Ronald Langacker, professor emeritus at the University of California, San Diego.

- cognitive linguist Leonard Talmy, Professor Emeritus of Linguistics at the University at Buffalo, State University of New York

But in order to get a more comprehensive view of the phenomenon of perspective in general, let’s first untangle the various forms of inquiry into the whole range of phenomena that can be subsumed under the heading of perspective.

Basically, we can look at perspective from various points of views, which of course, have to be integrated for a full grasp of the notion of perspective. For example:

1. Perspective from a developmental/ontogenetic point of view

From a developmental perspective we can ask when and how children come to be able to take the viewpoint of another person, first visually (Level 1, perspective taking, e.g. Flavell 1988, Moll & Tomasello 2006), then on a mental level of “putting oneself in the cognitive shoes of someone else” (Tomasello 1999). More generally we can ask, how Children become able to grasp not only that an object looks different from a different point of view, but also how the object might look like from a certain perspective (Level 2, perspective-taking, Flavell 1988).

In this regard it’s of special interest that perspective taking is a social-cognitive skill, and thus to look at children’s perspective taking and setting in cooperative and interactive situations. On a later stage of development, it’s a major research issue how children come to construe a “Theory of Mind” which allows them to attribute mental states to others, and to include these attributions in their predictions and thus also their interactions with other people.

This ability may reflect a full understanding of the concept of perspective, allowing children to compare differing perspectives on a phenomenon and to select amongst competing perspectives (Perner et al. 2002).

It is also likely that the development of an concept of self crucially depends on our interactions with others (Mead 1934), and especially on the child’s developing ability to understand perspectives. This allows her to contrast various views of the world and to understand herself by adopting other people’s perspective on herself, thus learning to see herself through the eyes of others. She also learns to see herself from different temporal perspectives and episodes, and to integrate these different perspectives into a unified view of herself as a person (Moll 2007)

2. Perspective from an Evolutionary/Comparative point of view

From an evolutionary perspective, we can look at how the ability to take and set perspective arose in the phylogenetic history of our species, and on which evolutionary foundations this ability was built. We can thus pose the same questions we asked in regard to children for the role-taking abilities of chimpanzees and other non-human primates (for a review see Tomasello et al. 2005).

Another key issue is the question which role cooperative behaviors with shared goals and intentions, which essentially depend on the notion of perspective, played in the cultural as well as evolutionary history .

Blending this area of research with the former one, we can also assess whether the unique perspectival qualities of human cognition and human interaction lead to special forms of perspectival cognitive representation in ontogenetic development (Moll & Tomasello 2007)

This is of course deeply related to the question how our lineage came to display this diverse set of modern human behaviors, symbolic and otherwise, such as language and especially the ability to understand others as intentional mental agents, which is the foundation of “cumulative” cultural evolution, innovation and shared artifacts, symbols, and institutions (Tomasello et al. 2005, Sterelny 2003). Tomasello et al.(2005) propose that it is the evolution of “shared intentionality”, i.e. the ability to jointly attend to a situation and to

"participate with others in collaborative activities with shared goals and intentions.” (Tomasello et al. 2005: 675),

was the major stepping stone in the evolution of behaviorally modern humans.

In accordance with th Tomasello et al’s (2005) and Moll & Tomasello’s (2007) hypothesis that this ability is linked to the evolution of uniquely human forms of perspectival mental representations, Benoît Dubreuil (2008) also challenges the role of language as being the driving force behind behavioral modernity, and instead proposes that the key “

"cognitive mechanism behind modern sapiens behavior is one of the general mechanisms underlying the higher form of ToM: the ability to hold in mind a stable representation of conflicting perspectives on objects”

and that this change is especially salient in human evolution by 85,000BP. His main argument is that there is no evidence that the production of the archaeological artefacts that appear around that time, for example, engraved ochres or marine shell beads, presupposes any symbolic abilities of their producers.This is because

"from an archaeological perspective, there is no real way to tell aesthetic and symbolic functions apart.“

But what they definitely entail is that their makers knew that the object they are making looks good from various viewpoints, and especially, in the case of self-decoration, that it makes the wearer look good from someone else’s perspective.

3. Perspective from a cognitive point of view

Perspective is implicated in all forms of cognition in various ways. For starters, there is the fact of embodiment, i.e. the fact that “minds have bodies that are situated in environments” (Poirier et al. 2005: 741). This means, that all perception is essentially of a perspectival nature dependent on how our minds are ‘grounded’ in various kinds of interactions with other physical processes (e.g. Barsalou 2008). Perspective thus refers to the way we categorize and represent the world. All cognition is therefore point of view dependent, or to be more precise, dependent on the frame of reference in which we transport “the parts of an object or the elements of a complex state of affairs and their interrelations” (Graumann 2002: 25). We can thus unify diverging perspectives, construe various perspectives simultaneously, and mentally manipulate them in the domain of our frame of reference, or cognitive coordinate system (see for example Bischof-Köhler & Köhler 2007) We can thus “project” ourselves into various frames of reference. Essentially these perspectives can also be “decoupled” (Sterelny 2003) from our immediate surroundings, and we can mentally travel through time and imagine ourselves in past, future, and hypothetical situations.

Interestingly, neuroscientific evidence points toward the assumption that Thinking about the future, episodic remembering, conceiving the perspective of others (theory of mind) and navigation” engage the same cortical network, “which suggests that they share similar reliance on internal modes of cognition and on brain systems that enable perception of alternative vantage points.” (Buckner & Carrol 2007). Although the authors of this study prefer the term ‘self-projection’, we could also construe these abilities as drawing on the core principle of understanding and taking perspectives.

These observations lend support to the idea that to understand perspectives, we make use of a single representational format, namely a basic frame of reference, as systemic space or coordinate system in which we construe and into which we transport conceptual representations. This idea is further supported by the neuroscientific evidence that

“simulated actions in the first and in the third person perspectives share common representations” (Anquetil & Jeannerod 2007)

i.e. that they work on the same representation, which can be used from different perspectives via a changing Origo- or Viewpoint (Bühler 1934) within the frame of reference.

Another question is the nature of the concepts employed in categorizing and cognizing the world around us. There are indicators that concepts, just like linguistic symbols, are of an essentially perspectival nature, with a specific ‘highlighting-and-hiding pattern’ (Lakoff & Johnson 1980). If we take Lawrence W. Barsalou’s view of concepts as internally simulated perceptual traces, with abstract concepts “grounded in complex simulations of combined physical and introspective events. (Barsalou 1999), perspective also plays a central role in the constitution and online activation of concepts and, as we will see, also the interpretation of complex events via metaphorical mappings.

That’s it for now. In my next post I will write a bit about perspective from the viewpoint of cognitive linguistics and philosophy.

On a related note, the latest edition of the Four Stone Hearth is out. Go have a look!

References:

Barsalou, Lawrence W. (1999): Perceptual Symbol Systems. In: Behavioral and Brain Sciences 22.4, 577-609.

Barsalou, Lawrence W (2008): Grounded Cognition. In: Annual Review of Psychology 59, 617-645.

Bischof-Köhler, Doris & [My paper]Norbert Bischof (2007): Is mental time travel a frame-of-reference issue? Behavioral and Brain Sciences 30 (3):316-7

Buckner, RL & DC Carroll (2007): Self-projection and the brain. In: Trends in Cognitive Sciences, 11.2Bühler, Karl (1934): Sprachtheorie. Die Darstellungsfunktion der Sprache. Jena: Gustav Fischer.

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.

Flavell, John H. (1988): The Development of Children’s Knowledge about the Mind: From Cognitive Connections to Mental Representations. In: Janet W. Astington, Paul L. Harris und David R. Olson (eds.): Developing Theories of Mind. Cambridge: Cambridge University Press, 141-172.

Graumann, Carl F. (2002): Explicit and Implicit Perspectivity. In: Carl F. Graumann und Werner Kallmeyer (Eds): Perspective and Perspectivation in Discourse. Amsterdam, Philadelphia: John Benjamins Publishing Company, 25-40.

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

Lakoff, George, and Mark Johnson 1980. Metaphors we live by. Chicago: University of Chicago Press.

Mead, George Herbert. (1934) Mind, Self and Society. Chicago: University of Chicago Press.

Moll, Henrike (2007): Person und Perspektivität – Kooperation und soziale Kognition beim Menschen. In F. Kannetzky & H. Tegtmeyer (Eds.), Leipziger Schriften zur Philosophie. Personalität – Studien zu einem Schlüsselbegriff der Philosophie, 37-56. Leipzig: Leipziger Universitätsverlag.

Moll, Henrike und Michael Tomasello (2006): Level 1 Perspective-Taking at 24 Months of Age. In: British Journal of Developmental Psychology 24, 603-613.

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

Perner, J., Stummer, S., Sprung, M., & Doherty, M. (2002). Theory of mind finds its Piagetian perspective: Why alternative naming comes with understanding belief. Cognitive Development, 17, 1451-1472.

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale.2005. “Embodied Categorization.” In: Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier, 2005.

Sterelny, Kim (2003): Thought in a Hostile World: The Evolution of Human Cognition. Malden: Blackwell.

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

Tomasello, M., Carpenter, M., Call, J., Behne, T., & Moll, H. (2005). Understanding and sharing intentions: the origins of cultural cognition. Behavioral and Brain Sciences, 28, 675– 735.

LolAntz

In my last posts I wrote about the question how AI and Robotics can tell us something about the architecture of (simple) biological systems. In this post I’ll give an example of how the study of simple organisms, augmented by AI and robotics, can give us information about the structure of cognitive systems.
Studying ant’s navigational skills is such an example. It can tell us something about the evolution of cognitive mechanisms in general because an ant's “domain-specific processing modules” (Wehner 2003a: 585) show signs of modular adaptation, that is, it seems to have

“evolved to solve particular problems encountered by Cataglyphis during its foraging lifetime.” (Wehner 2003a: 579).

In detail, the ant’s navigational toolkit consists of:

“its skylight (polarization) compass, its path integrator, its view-dependent ways of recognizing places and following landmark routes, and its strategies of flexibly interlinking these modes of navigation to generate amazingly rich behavioural outputs.“ (Wehner 2003a: 579)

The sophistication of these synchronically orchestrated navigational modules is quite amazing given that they are found in a brain that weighs 0.1 mg. The human brain weighs about 13 million times at much, about 1,300 g (Jones 2004).
It is probable that our brains too, consist of cognitive mechanisms (and learning mechanisms) which are

"hierarchically nested adaptive specializations, each mechanism constituting a particular solution to a particular problem” (Gallistel 2000).

Another fascinating feature of the ant’s navigational toolkit is its context-dependency . Cataglyphis doesn’t create a ‘mental map’ of its environment, but has a highly egocentric perspective and employs a ‘path integrator’, a permanently updated system informing the ant “about its current position relative to its point of departure”, a little like Ariadne’s thread. (Wehner 2003a).
If the ant is picked up and placed somewhere else, it as a hard time getting home (if it even makes it at all) because the neurological ‘thread’ of the ant’s navigational system isn’t connected to the starting point anymore. When the path-integration vector (the ‘thread’) is displaced, what otherwise would leave the ant straight home is now worthless, because any information about the environment is strictly evaluated in relationship to the ant itself. Therefore the navigational toolkit of Cataglyphis is not only an example of domain-specific adaptation, but also of embodied intelligence (Wehner 2003b).

Interestingly, an experiment by Floreano and Nolfi (1996) in which robots had to explore an area (which I described in my first post) led to the development of very similar mapping-strategies in the robot’s self-organizing neurons. (Wehner and his colleagues also suceeded in building a mobile robot modeling the navigational skills of Cataglypghis, with comparable results.)
This means that both in Cataglyphis and simple artificial systems,

“There is no categorization of the environment that is independent of it” (Poirier et al. 2005: 751)

These “lessons from Cataglyphis” (Wehner 2003b), crucial as they are for understanding human cognition, surely aren't the whole story, especially as there is evidence for a dual-system account of human cognition, consisting of a ‘primitive’, fast , automatic and strongly modular system, and a more-fluid, conscious, cross-domain system. (Evans in press) Additionally,

“One should never underestimate the functional economy of nervous systems: once they have been adapted, over evolutionary time, to the principal physical properties of a predictable environment, they can employ comparatively simple neural strategies to solve quite sophisticated computational tasks.” (Wehner 2003a: 582)

A higher-cognitive task like reading, for example, can probably be explained best by the functional economy and plasticity of human brains. For reading, the “capacity to accommodate a broad range of new functions through learning” (Dehaene 2004) and the ability to employ (or ‘recycle’ as Dehaene calls it) neuronal circuits which serve a similar or related function seems to be essential.
Of course there is still a long way from systems showing properties of embodiment to systems that have internal perspective, but the research discussed in this as well as other posts makes it pretty clear that embodiment is without doubt a crucial component not only of all sensori-motor systems, but also of cognitive systems (Cruse 2003),

P.S.: please note that the ant in the picture isn't a desert ant but a leafcutter ant. I just couldn't find a useful picture of cataglyphis to toy around with ;-)

References:

Cruse, Holk. 2003: “The Evolution of Cognition – A Hypothesis.” Cognitive Science 27: 135–155

Dehaene, Stanislas. 2004. “Evolution of human cortical circuits for reading and arithmetic: The “neuronal recycling” hypothesis." From monkey brain to human brain. Eds. S. Dehaene, J. R. Duhamel, M. Hauser & G. Rizzolatti Cambridge, MA: MIT Press.

Evans, Jonathan St. B.T. in press. “Dual-Processing Accounts of Reasoning, Judgment, and Social Cognition.” Annual Review of Psychology 59

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.

Gallistel, C.R. 2000. „The Replacement of General-Purpose Learning Models with Adaptively Specialized Learning Modules.” The Cognitive Neurosciences. 2d ed. Ed. M.S. Gazzaniga. Cambridge, MA: MIT Press: 1179-1191.

Jones, Owen D. 2004. “Law, Evolution, and the Brain: Applications and Open Questions.” Proclamations of The Royal Society of London B: Biological Sciences 359: 1697-1707.

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale.2005. “Embodied Categorization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier, 2005.

Wehner, Rüdiger. 2003a. “Desert ant navigation: how miniature brains solve complex tasks.” Journal of Comparative Physiology A: Neuroethology, Sensory, Neural, and Behavioral Physiology 189: 579–588

Wehner, Rüdiger. 2003b. “Blick ins Cockpit von Cataglyphis” Naturwissenschaftliche Rundschau 56.3: 134-140.

Does Artificial Intelligence Worm its Way into the Study of Cognition? (Pun Intended)

Citing evidence from AI/AL/Robotics to gain insight into cognitive mechanisms, Poirier et al. (2005) clearly share the sentiment that

„a measure of understanding will be gained by studying simple and superficial models of complete agents.” (p. 762)

Although they state that to fully understand the principles governing cognition, complete models of situated embodied agents engaged in brain-body-world-interaction (or their AI-counterparts) will prove essential, they hold that

“simple models like these can help us understand some general principles governing categorization” (p. 762).

There is, of course, a bigger question looming behind this assertion:

"Can robots make good models of biological behaviour?“ (Webb 2001a)

Barbara Webb (who you can hear talk about her work on robotic crickets here) proposes that models can indeed tell us a lot about biological systems, if only the dimensions of the simulation are made explicit. She proposes the following variables:

“1. Relevance: whether the model tests and generates hypotheses applicable to biology.
2. Level: the elemental units of the model in the hierarchy from atoms to societies.
3. Generality: the range of biological systems the model can represent.
4. Abstraction: the complexity, relative to the target, or amount of detail included in the model.
5. Structural accuracy: how well the model represents the actual mechanisms underlying the behaviour.
6. Performance match: to what extent the model behaviour matches the target behaviour.
7. Medium: the physical basis by which the model is implemented.“ (p. 1033)

Another problem is the confusion over the term model, which is defined in so many different ways that it is sometimes hard to find out whether two people mean the same thing when talking about models.
According to Webb (2001a)

“modelling aims to make the process of producing predictions from hypotheses more effective by enlisting the aid of an analogical mechanism” by symbolically simulating the properties assumed to perform certain functions. (p. 1035)

Biological systems and biorobotics share the property that they are

“physically instantiated and have unmediated contact with the external environment” (p. 1037).

Poirier et al. (2005) show that we can already draw much insight from this correlation, given that even simple models show how

"categorization capacities that are quite sophisticated can emerge from very simple embodied and situated systems” (p. 762).

These observations clearly speak for the importance of embodied properties when studying cognitive mechanisms. On the other hand, they give a practical example of how robotics can support specific hypotheses regarding cognition. They too show that robots that are models if animal behavior can be seen as “as a simulation technology to test hypotheses in biology” (Webb 2001a: 1049).
Many of the peer commentaries on Webb’s Behavioral and Brain Sciences Article are not that optimistic. One general criticism is that of underdetermination,

"that is, having a robot behave like an animal is no guarantee that the animal works the same way“ (Webb 2001b: 1083).

But, as Poirer et al. (2005) argue, artificial systems give us major clues about what kind of and which quantities of structure are able to perform certain functions.
Another criticism aimed at biorobotics is that, although they are inspired by biological systems, as of yet the haven’t done much to inform biology. But as Webb’s (2001a) impressive sample of biorobotics research – 78 articles from 1992-2001 ranging from bat sonar and frog snapping to simulations of insect wings, paper wasp nest construction and ant/bee landmark homing – as well as Poirier et al.’s (2005) review show, this complaint is clearly mistaken.
Another interesting test case for the ability of artificial systems to simulate biological behavior are neural networks employed to simulate properties of Caenorhabditis elegans, a roundworm that is about 1mm in length. I will discuss some of these attempts in my next post.


Reference:

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale. 2005. “Embodied Categorization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier.

Webb, Barbara. 2001a. “Can robots make good models of biological behaviour?” Behavioral and Brain Sciences 24.6: 1033–1050.

Webb, Barbara. 2001b. “Robots can be (good) models.“ Behavioral and Brain Sciences 24.6:1081-1087

Shared Symbolic Storages

The last kind of category discussed in Pierre Poirier, Benoit Hardy-Vallée, and Jean-Frédéric Despasquale’s (2005) article about “Embodied Categorization” are ‘linguistic categorizers.’

Concepts
Poirier et al. call linguistic categories ‘concepts’, that is, first and foremost public objects whose usage is controlled by the linguistic community. Seen this way, the generally established system of concepts is the shared symbolic storage of a community. Jerry Fodor (1998) has a similar notion of concepts, stating that one requirement (Nr. 5 of 5, to be precise) for concepts is that they be

“public; they’re the sorts of things that lots of people can, and do, share” (p. 28).

Fodor’s other requirements for concepts are that they:

1. are states of the mind/brain that function as mental effects or causes.
   
2. that they are categories, that is that they function as mental operations “by which the brain classifies objects and events” (Cohen/Lefebvre 2005: 2).
   
3. that they are compositional, that is that they, one the one hand, consist of constituents (of other, hierarchically intertwined, ‘lower’ concepts), and, on the other hand, that they are the constituents of what Fodor calls ‘thoughts’(i.e. his “cover term for the mental representations which […] express the propositions that are the objects of propositional attitudes.” (p. 25) As if that would make anything clearer, since ‘proposition’ and ‘propositional attitude’ are terms that are just as controversial)
   
4. that a lot of them are learned. (Jesse Prinz (2005) even argues that all concepts are learned, a hypothesis Fodor definitely wouldn’t like. And of course, Prinz’s definition of concepts is different, too.)
   

Hurford (2007) further differentiates between ‘proto-concepts’, ‘pre-linguistic concepts’ and ‘linguistic concepts’ in order to account for neuropsychological (Barsalou 2005a) and ethological evidence (Cheney & Seyfarth 2007) for mental and conceptual representations in other animals (= ‘proto-concepts’ and in higher mammals probably (and definitely so in our ancestors) even ‘pre-linguistic concepts’). Thus, the shared/public-requirement of Fodor (1998) only holds for linguistic concepts.

Concepts and Categories
Regarding the difference between concepts and categories: concepts can be said to represent categories, e.g. when we encounter a member of the category DOG, the DOG concept is activated (Prinz 2005), or, in Barsalou’s (2005) terms, a category corresponds to a component of experience, whereas the conceptual system consists of the collected representations of these categories.
Thus, on seeing a dog, the human conceptual system construes this perception as a category instance of DOG by binding the specific perceived token (i.e. the individual dog) “to knowledge for general types of things in memory (i.e., concepts)” (p. 581).
Poirer et al. argue that linguistic categorizers are "farthest removed from their basic sensorimotor counterparts” (p. 761),although, as argued by Lakoff and Johnson (1980,1999), they still seem to be heavily influenced by embodied experience.

Linguistic Categories and Language Acquisition

Poirier et al. make an interesting analogy between the embodiment perspective they adopt throughout their paper and language acquisition. A child can be seen as simulating the arbitrary word-category/siginfiant-signifié contingencies she is presented with through her linguistic environment, forming “internal models of her community’s lexicalized categories”(p. 761) which enables her to communicate with others. Evidence for the importance of linguistic/lexicalized categorization comes from the fact that words help us to acquire new categories, “that category labels play a role in the formation and shaping of concepts” (Lupyan 2006) and that they

“play an especially important role in shaping representations of entities whose perceptual features alone are insufficient for reliable classification.” (Luypan 2005).

To conclude, it seems that all forms of categorizations may in some way be present in human cognition, and that many of the feats that make us ‘uniquely human’ are augmented by sophisticated forms of categorization which can best be described from the perspective of embodied evolutionary-developmental computational cognitive neuroscience.

Next week I will try to discuss the implications of computational/AI/robotics research, as presented by Poirier et al, for the study of human cognition and behavior.

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

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

Cohen, Henri and Claire Lefebvre. 2005 “Bridging the Category Divide.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier. 1-15.

Fodor, Jerry A. 1998. Concepts. Where Cognitive Science Went Wrong. Oxford Congitive Science Series. Oxford: Clarendon.

Hurford, James R. The Origins of Meaning: Language in the Light of Evolution 1. Oxford OUP.

Lakoff, George, and Mark Johnson 1980. Metaphors we live by. Chicago: University of Chicago Press.

Lakoff, George and Mark Johnson. 1999. Philosophy in the Flesh: The Embodied Mind and its Challenge to Western Thought. New York: Basic Book

Lupyan, Gary. 2005. “Carving Nature at its Joints and Carving Joints into Nature: How Labels Augment Category Representations.” Modelling Language, Cognition and Action: Proceedings of the 9th Neural Computation and Psychology Workshop. Eds. A. Cangelosi, G. Bugmann & R. Borisyuk Singapore: World Scientific. 87-96

Lupyan, Gary. 2006. “Labels Facilitate Learning of Novel Categories.” The Evolution of Language: Proceedings of the 6th International Conference. Eds. A. Cangelosi, A.D.M. Smith & K.R. Smith Singapore: World Scientific,190-197

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale. 2005. “Embodied Categorization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier.

Prinz, Jesse. 2005. "The Return of Concept Empirism." Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier.

Life is a Journey

Analogy

In my last posts I wrote about embodiment and how many of our categories stem from sensorimotor experience, embodiment, simulation and emulation. But what about abstract concepts? Lakoff and Johnson (1980, 1999) argue that our conceptual system, which enables us to categorize and draw analogies, is also built on the basis of embodied experience. As Poirier et al. put it

"An analogical inference is a “cut and paste” process: from a cognitive domain (the source), copy the structure of an object in the domain and paste it into another (the target), while replacing every variable from the source domain by a variable from the target domain" (Poirier et al. 2005: 759f.).

Lakoff and Johnson see embodied experience as the source domain for such processes, many of which can be found in everyday language. One example is the conceptual network of CONTAINER-metaphors. As physical organisms which are separated from the outside world by our skin, we project our own experience of being a container with a demarcating surface with an inside-outside-orientation to other physical objects which are partitioned by surfaces (Lakoff/Johnson 1980). This results in many container-metaphors in everyday language, such as “I’ve had a full life.” “Life is empty for him.” “Her life is crammed with activities.” “Get the most out of life.” etc. Other examples are metaphors of movements or spatial dimension, like to get idea’s across, words reaching someone etc. These cross-domain mapping-ability, or ‘conceptual integration’ may be an essential evolutionary step in what makes us human (Turner 2006, Mithen 1996).

Dual Systems Theory

These observations can also be integrated in dual-system accounts of reasoning, which proposes that human cognition basically consists of the interactions of:

1. an evolutionary older system (System 1) shared by humans and other animals consisting of parallel and automatic modules mediated by domain-general learning mechanisms
   
2. and a uniquely human, central system 2, whch enables hypothetical thinking, abstract reasoning, and therefore is able to access and blend multiple domains, on the other (Evans 2003).

I’m not really sure what to think about the general-purpose-claims that come with this idea, but surely cross-domain access is crucial for modern cognition. On the neuropsychological level, higher frontal control over other cognitive systems could offer some insights on how to think of a system 2, or generally into the mechanisms enabling mental time-travel and displaced reasoning (Barsalou 2005, Deacon 1997), regardless of calling it general purpose or not.

When making 'analogizing categorization' a key feature of human evolution, we have to keep in mind that analogy of a simple kind, the abstraction and mapping of common global structures, can be found in other animals as well: Even fish have distinct areas for interpreting perceptual/sensory input and motor-coordination. The cerebral cortex of mammals, however, seems to have a much higher level of brain organization, i.e. the cerebral cortex with distinct ‘projection areas’ for various sensory and motor systems, enabling a cat, for example, to play with a ball of yarn as a mouse analog (Sowa 2005). If so, System 1 and System 2 should probably not be seen as discontinuous dichotomies but rather as different stages on a continuum, or extended specializations of previous abilities (Sowa 2005, Turner 2006).

Still, positing a System 2 seems to be justified considering the importance of cross-modal, “large-scale neural integration” (Donald 2006) for human cognition. Accepting this dual account, it is still important to make out the subsumed cognitive architecture, but as a heuristic tool it seems to be as fruitful for cognitive research as Dan Dennett’s (1987) tripartite account of ‘physical stance’, ‘design stance’, and ‘intentional stance’ and Hauser et al.’s (2002) division of the faculty of language in the broad sense (FLB), and the Faculty of Language in the narrow sense (FLN). Our understanding about the levels of cognition could also be enriched by complementary approaches, for example from Artifical Life and Artifical Intelligence (Sowa 2005), or cognitive ethology.
In my next post on Poirier et al.’s paper I will describe their account of “linguistic categorizers.”

References:

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

Deacon, Terrence William 1997. The Symbolic Species. The Co-evolution of Language and the Brain. New York / London: W.W. Norton.

Donald, Merlin. 2006. “Art and Cognitive Evolution.” The Artful Mind: Cognitive Science and the Riddle of Human Creativity. Ed. Mark Turner. Oxford: OUP

Evans, Jonathan St. B.T. 2003. “In two minds: dual-process accounts of reasoning” Trends in Cognitive Sciences 7.10: 454-459.

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?” Science 298, 1569-1579.

Lakoff, George, and Mark Johnson 1980. Metaphors we live by. Chicago: University of Chicago Press.

Lakoff, George and Mark Johnson. 1999. Philosophy in the Flesh: The Embodied Mind and its Challenge to Western Thought. New York: Basic Book

Mithen, Steven J. The Prehistory of the Mind. London: Thames & Hudson.

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale.2005. “Embodied Categorization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier.

Sowa, John F. 2005. “Categorization in Cognitive Computer Science.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier.

Turner, Mark. 2006. “The Art of Compression.” The Artful Mind: Cognitive Science and the Riddle of Human Creativity. Ed. Mark Turner. Oxford: OUP.

Simulation and Stances II: The Intentional Stance

How can we assess intentions? How does ‘folk psychology’, Theory of Mind, or ‘the intentional stance’ work?
Basically, there are two competing theories, the Theory Theory (TT) Simulation Theories (ST) of mind reading.
The simulation theory proposes that, instead of developing a full-fledged real theory about how to explain our own as well as other peoples' behavior and experience, we mentally try to simulate and imagine the internal states of others (Gopnik 1999).
An embodied perspective on this phenomenon suggests that at least some features of mind-reading are accounted for by ST (Poirier et al. 2005: 758f.). According to neuropsychological evidence, for example, the recognition of face-based emotions (FaBER), is better supported by simulationist accounts than by TT’s of mind-reading (Goldmann & Sripada 2005). As Poirier et al. (2005: 759) argue, it may be that in some situations, simulation may be a more direct means to gain insight into someone else’s, especially emotional, mental states.

Mirror Neurons

Another case for ST comes from the fact of ‘mirror neurons’, which discharge during the observation of goal-directed movement, and thus may be critical to understand others intentional states (Rizzolatti & Craighero 2004). It seems possible that we simulate the behavior of others via our ‘mirror system’ and ascribe to them the resulting intentional states. (Poirier et al. 2005: 759, Gallese et al. 2004). To interpret and integrate this intentional state, though, mirror neurons alone seem to be insufficient and in need of other social cognitive mechanisms, (Wheatley et al. 2007, Uddin et al. 2007, Gallagher 2007). On the other hand, mirror neurons play a greater role in the coding of intentions than is sometimes acknowledged, albeit depending on what we call an ‘intention’ (Iacoboni et al. 2005).

The Intentional Stance

Poirier et al. conclude that:

“the intentional stance is clearly a predictive strategy, which could (but does not always) make use of categories to which we have access not by deriving them from a theory, but by simulating the internal doxastic and volitional states of others on the basis of their behavior, context, and facial expression. Language can give access to higher order intentionality: an agent represents its own mental states as they mentally represent another agent’s mental states, and so on“ (p. 759)

In my next post on “Embodied Categorization”, I will write about Poirier et al.’s account of analogical categorizers.

References:

Gallagher, Shaun. 2007 “Simulation Trouble”. Social Neuroscience 2.3/4: 353-365.

Gallese, Vittorio, Christian Keysers and Giacomo Rizzolatti. “A Unifying View of the
Basis of Social Cognition.” Trends in Cognitive Sciences 8 (2004): 396–403.

Goldman Alvin I. and Chandra Sekhar Sripada. 2005. “Simulationist models of face-based emotion recognition” Cognition 94: 193-213.

Gopnik, Alison. 1999. “Theory of Mind.” The MIT Encyclopedia of the Cognitive Sciences. Eds.Robert A. Wilson and Frank C. Keil. Cambridge, MA: MIT Press 838-841.

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale. 2005. “Embodied Categorization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier.

Iacoboni M, Molnar-Szakacs I, Gallese V, Buccino G, Mazziotta JC, et al. (2005) "Grasping the intentions of others with one’s own mirror neuron system." PLoS Biol 3(3): e79.

Rizzolatti, Giacomo and Laila Craighero. “The Mirror-Neuron System.” Annual Review of Neuroscience 27 (2004): 169–192.

Uddin, Lucina Q., Marco Iacoboni, Claudia Lange and Julian Paul Keenan. 2007. “The Self and Social Cognition: The Role of Cortical Midline Structures and Mirror Neurons.” Trends in Cognitive Sciences 11.4 (2007): 153-157.

Wheatley, Thalia, Shawn C. Milleville and Alex Martin. 2007. “Understanding Animate Agents: Distinct Roles for the Social Network and Mirror System.” Psychological Science 18.6 : 469-474.

Simulation and Stances I: The Physical Stance and The Design Stance

What can the theory of embodied categorization tell us about how the intentional stance works? Dan Dennett (1987) speculates that the combinatorial, generative properties of language/the language of thought play a crucial role in our attempts to predict the behaviors of physical, designed, and intentional systems.
Combining data from various areas of research, Poirier et al. (2005), on the other hand, try to account for some aspects of these stances as internal simulations of possible external states.

The Physical Stance

Systems that are able to categorize physical systems, that is, those able to adopt the ‘physical stance’ or use ‘folk physics’, seem to do so by simulating geometrical relationships. (Poirier et al. 2005). MetaToto, for example, is a robot able to build a map of its environment from sensory input, and whose behavior is guided by simulations of movement in his internal map. Thus, the robot is able to categorize physical features, e.g. a wall, not by hitting it but by simulating it (Poirier et al. 2005 757f.; Stein 1994).
People also seem to make physical inferences either by acting on objects (similar to the “we off-load cognitive work into the environment”-view I described briefly here), or by simulating actions and visuomotor experience internally (opposed to simply engaging in mental imagery, where crucial aspects of action-oriented simulation, and dynamics like gravity and other physical, ‘abstract’ forces seem to be missing) (Schwartz and Black 1999).

The Design Stance

Systems able to categorize functional categories, i.e. those able to adopt the ‘design stance’, ‘folk biology’, or mechanics, simulate features of animals or artifacts. (Poirier et al. 2005: 758). According to Hegarty (2004), design inferences work via the ad hoc simulation of ‘abstract’ functional features in a spatial dimension, which can, but not necessarily has to, be complemented by visual simulation.
Of course, as complexity rises, Dan Dennett might be right in assuming a role for language here.
An interesting question concerns how behavior-reading works in other primates. Do they adopt the ‘design stance’, that is, do they simulate functional features in order to predict behavior, e.g. associate certain behavioral/gestural/facial/phonetic patterns as ‘do not come near me’, and others as ‘safe to approach’, etc. -or “Does the chimpanzee have a theory of mind?” (Premack & Woodruff 1978).
Poirier et al. support the idea that other primates do not have a Theory of Mind, that they are not able to model the “’action level’, a rather detailed and linear specification of sequential acts”, but only the “’program level’, a broader description of subroutine structure and the hierarchical layout of a behavioural ‘program’” (Byrne and Russon 1998).
Whereas the action level invokes mental, unobservable, ‘intentional’ concepts, behavior-reading only invokes functional categories such as movement. The reason for this inability to adopt the ‘intentional stance’ may be that primates generally lack the concept of unobservable causes and thus are not able to

“posit hidden mental representations, assessable from the intentional stance.” (Poirier et al. 2005: 758, Povinelli 2000).

The evolution of such a concept may have enabled humans to have a ‘real’ Theory of Mind, and subsequently may have influenced our engagements of the physical stance and the design stance (Herrmann et al. 2007).

Next week I will write about how the intentional stance might work, given what we know about embodiment and simulation.

References:

Byrne, Richard W and Anne E. Russon. 1998. “Learning by Imitation: a Hierarchical Approach.” Behavioral and Brain Sciences 21: 667-684

Dennett, Daniel C. 1987. The Intentional Stance. Cambridge, MA: Bradford Books.

Herrmann, 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: 1360-1365.

Hegarty, Mary.2004.“Mechanical Reasoning by Mental Simulation.” Trends in Cognitive Sciences 8: 280-285.

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale. 2005. “Embodied Categorization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier.

Premack, David Guy and G. Woodruff. (1978). "Does the chimpanzee have a theory of mind?" Behavioral and Brain Sciences 1: 515-526.

Povinellim Daniel J. 2000. Folk Physics for Apes: The Chimpanzee's Theory of How the World Works. Oxford: OUP.

Schwartz, Daniel L. and Tamara Black. 1999. “Inferences through imagined actions: Knowing by simulated doing.” Journal of Experimental Psychology. Learning, Memory, and Cognition. 25.1: 116-136.

Stein, Lynn Andrea. 1994. “Imagination and situated cognition.” Journal of Experimental and Theoretical Intelligence 5: 393-407.

Embodied Cognition

In my last post I wrote about Poirier et al.’s (2005) paper on ‘embodied categorization’ in which they coined the “cumbersome” phrase ‘embodied evolutionary-developmental computational cognitive neuroscience’.
As Wilson (2002) notes, there are actually several claims included in the term of ‘embodied cognition’ which do not come as an inseparable package but each have their own validity (or lack of it). Wilson untangles the following viewpoints that go with the idea of embodiment:

1. “Cognition is situated.” We categorize and predict the real world in order to perform and perceive events.
2. “Cognition is time pressured,” because it takes place in a real-time environment and must adapt and react adequately to real environmental challenges.
3. “We off-load cognitive work onto the environment” by storing information in the outside world. Language and culture, in this view, could be seen as ‘shared symbolic storages’ of symbols, memes, cultural and cognitive artifacts, or however you want to name your desired unit of information. By this process we supplement our cognitive capacities, for example by letting some calculations be done by computers, or change our environment as to act more efficiently within it, or form a dynamic system with it.
   
4. "The environment is part of the cognitive system.” This claim is actually quite controversial, but philosophers like Andy Clark (Clark 1997, Clark and Chalmers 1998), argue that, since out-of-body cognitive supplements function interactively as ‘external minds’, cognition should not be defined as something the mind does, but as a unified system emerging through the situated interaction of mind/brain, body, and environment.
5. “Cognition is for action.” Action-guidance is the mind/brain’s main function, and perception, memory and perception are crucially involved in the selection and anticipation of desired events.
6. “Off-line cognition is body based.” Embodiment plays a crucial part in how we see and conceptualize the world. The way we structure our knowledge, is often deeply influenced by sensorimotor categories and embodied experience. (Lakoff and Johnson 1980, 1999).

Poirier et al. mainly focus on the aspects 1. and 5., without ever claiming that this is all there is to cognition. Rather, they propose that embodiment accounts for certain critical properties of cognition.
In their account of cognitive simulations, the “reenactment of perceptual, motor, and introspective states acquired during experience with the world, body, and mind” which are reactivated and integrated to form categories is the process by which we model and predict external and internal states (Barsalou in press a).
They blend this view with Dan Dennett’s (1987) differentiation of three predictive strategies: the physical stance (folk physics), the design stance (folk biology and mechanics) and the intentional stance (theory of mind), which I will write about in my next post.

References:

Barsalou, Lawrence W. In press. “Grounded Cognition.” In: Annual Review of Psychology 59

Clark, Andy. 1997. Being There: Putting, Brain, Body and World Together again. Cambridge, MA: MIT Press.

Clark, Andy and David Chalmers. 1998. “The Extended Mind.” Analysis 58.1: 7-19.

Dennett, Daniel C. 1987. The Intentional Stance. Cambridge, M.A.: Bradford Books

Lakoff, George, and Mark Johnson 1980. Metaphors we live by. Chicago: University of Chicago Press.

Lakoff, George and Mark Johnson. 1999. Philosophy in the Flesh: The Embodied Mind and its Challenge to Western Thought. New York: Basic Book

Poirier, Pierre, Benoit Hardy-Vallée and Jean-Frédéric Depasquale. 2005. “Embodied
Categorization.” Handbook of Categorization in Cognitive Science. Eds. Henri Cohen and Claire Lefebvre. Amsterdam: Elsevier, 2005.

Wilson, Margaret. 2002. "Six views of embodied cognition." Psychonomic Bulletin & Review 9.4: 625-636