School of Psychology, Birkbeck College

Course PSYC044U (Psychobiology II.)
May 17 2007

gifThis is just the first 6 pages of the longer paper handout. Web versions of the other pages in the paper handout are accessible from the side index. If you need to print out the handout, then all the pages are in this 'pdf' file, but this is quite large and may be difficult to download over a telephone modem.

1st Lecture: Human Learning: Further comparisons between human, animal and machine learning


2nd Lecture: Instructions for the exam; and course review.  

Relevant essays for human learning on the March 15th list

5.    How is “conditioned fear” relevant to the understanding of the development and treatment of anxiety disorders"?

8.     'Apes cannot be taught language, but there is evidence that they have special abilities in the areas of social learning, imitation, and self-recognition.' Discuss.

9.     Thorndike called himself a connectionist — is this just a co- incidence, or can comparisons be made between modern accounts of neural networks and previous theories of animal learning?






[page 1 of wk 13 handout, with added bullet points]
  • For some time in Cognitive Psychology and Cognitive Science, the study of human learning was de-emphasized (Glaser, 1990).

  • On one hand, the influence of Chomskyean psycholinguists has been in the direction that most important aspect of human cognition are determined by innate rather than learned factors (Chomsky, 1980, Piatelli-Palmarini, 1989).

  • On the other hand the study of human information processing has focused on models of human performance in brief experiments in areas such as perception and memory, with little attention paid to the gradual acquisition of skills (Newell and Simon, 1972; see Glaser, 1990).

  • This is in stark contrast to the traditional view that the cultural transmission of knowledge is a unique and crucial feature of human societies, and also, for instance, to the widely held lay assumption that education and training hold the key to industrial and commercial competitiveness.

  • Clearly, however, interest in human learning has been retained in applied areas, such as educational psychology, and many areas of developmental psychology (Glaser, 1990; Hartley, 1998; Howe, 1998; Posner & Rothbart, 2005).

  • There are several areas of human experimental psychology where the terminology of learning is still used, such as “implicit learning” (Berry, 1994; Seger 1994; Fletcher et al, 2000; Reed & Means, 2004), perceptual learning (Goldstone, 1998; Sekiyama et al, 2000; Ashby & Maddox, 2005; Driscoll et al., 2005) and varous kinds of motor skill learning (Gordon et al, 1994; Marsolek and Field, 1999; Maxwell et al., 2001; Hikosaka et al., 2002; Tyc et al., 2005).

  • There is also a growing area of psychobiological research in to motivation and emotion, where significant parellels, as well as differences, emerge in comparisons of human and animal learning (Cox et al., 2005; O'Doherty, 2004; Panksepp, 2005; Shultz, 2006; Paton et al., 2006; Padoa-Schioppa & Assad, 2006).

  • Psychobiological parallels are also commonly appealed to in the case of theories of hippocampal functioning (Moses and Ryan, 2006; Foster and Wilson, 2006; see also week 9).
[bottom of page 1 of wk 13 handout]
1. Human Cultural Learning and Social Cognition (Tomasello et al, 1993)

A new version of the traditional theory that learning is an important feature of human cultures was put forward recently (Tomasello et al., 1993; Tomasello, 2001; Tomasello and Rakoczy, 2003; Tomasello et al., 2005; Moll & Tomasello, 2007)
  • A new version of the traditional theory that learning is an important feature of human cultures was been put forward by Tomasello et al (1993) and Tomasello (2001) and has been modified by Tomasello and Rakoczy (2003) and Tomasello et al., (2005).

  • First, they emphasize the importance of the “cultural ratchet” — knowledge is accumulated over time, and is passed on both across and within generations.

  • Their basic point is that humans learn from each other, in ways than non-human animals can not: human learning differs from animal learning because it is a more powerful and more influential process.

  • The particular focus of their theory is the idea that human learning depends on social cognition, and that developmental changes in children’s understanding of other people’s point of view underlie their ability to acquire new skills and conventions from those around them.

  • They define three different kinds of cultural learning process (see Table below)


  • Imitative Learning They reserve this term for the kind of imitative learning of novel object-direct actions that is usually first seen in human infants 9-14 month old. Neonatal copying of facial movements such as head turning and tongue protrusion counts only as “social matching” and some other kinds of action emulation in younger infants also do not qualify as true imitative learning in Tomasello et al’s theory because it is not clear that they depend on the child understanding the intentions of the emulated adult.

  • Instructed Learning. This corresponds to children being able to regulate their own behaviour vial the internalization of adult instructions. It is associated with self- monitoring skills or “metacognitive strategies”.

  • Collaborative Learning. Although younger children often collaborate in play, it is only at 6 or 7 that they can understand such recursive, perspective-taking mental states such as “Mary thinks that I think that John is cute” (p. 501) and the theory is that this allows for more sophisticated forms of learning during peer interactions.

    [page 2 of wk 13 handout]
    Table 1 Major features of the three types of cultural learning.

    Cultural learning process Social-Cognitive ability Concept of person Cognitive Representation

    Imitative 9 months Perspective-taking (e.g. joint attention, social referencing. Intentional agents (0 order) Simple (other's perspective)

    Instructed (4 years) Intersubjectivity (e.g. false-belief task, intentional deception). Mental agent (1st order) Alternating/ coordinated (other's and own perspective)

    Collaborative (6 years) Recursive intersubjectivity (e.g. embedded mental-state language Reflective agent (2nd order) Integrated (dyadic intersubjectivity).

    Tomasello et al (1993 & 2003 & 2005) say that the imitative learning of chimpanzees “presents a complex and very interesting picture” but they do not believe that chimpanzees exhibit any of the above 3 kinds of cultural learning, since clearly they cannot internalize instruction and use it to regulate their own behaviour.


[bottom of page 2 of wk 13 handout]
2. The reemergence of learning theory within instructional research.

This is the title of the article by Glaser (1990), who reviewed a variety of training projects designed to inculcate skills in such specialized areas as medical diagnosis, reading comprehension or computer programming. Most of these projects made use of Computer-Aided Learning (CAL). Even with computerized training programmes there are different approaches, which correspond to different aspects of human learning, but Glaser suggests that integrating the results from a wide variety of successful methods of systematic instruction might provide an all- encompassing theory of human learning.

Certain general principles emerge from his analysis

  • Learning, as knowledge strengthening, results from error-free practice
  • But failure or conflict may trigger new learning
  • Feedback and guidance to the learner helps
  • Learning takes place in the context of work on specific problems
  • Explanation and modeling of problem-solving strategies helps

  • But there is still a difference between the two main kinds of training procedure

A. Progressive Mastery: a strict and progressive sequence of skills is laid down
B. Unstructured: the learner is given certain tools and then left alone.

Glaser believes that these different approaches may suit different kinds of task.

[top of page 3 of wk 13 handout]
3. Anderson’s Theory of Cognitive Skill Acquisition (Anderson, 1987, 2002; Anderson & Matessa, 1997)

Anderson’s theory is one of the main ones discussed by Glaser (1990)

  • It arises from work on the design of computer tutoring programmes for skills such as solving algebraic equations, computer programming in a particular language, or using a word- processor.

  • Although these are uniquely human skills, Anderson’s theory has a certain amount in common with traditional theories of animal learning, not least because he uses the terminology of learning, and says that his goal is to use his theory of learning to account for differences in behaviour by differences in experience.

  • Further, Anderson’s is a “learning by doing” theory, and the units of learning in it are “condition-action pairs” which are acquired as a function of their previous consequences, which is reminiscent of Thorndike’s “situation-response” connections.

  • Anderson calls his condition-action pairs “productions.”: “The ACT* theory offers a more abstract concept, the production, to replace the more concrete concept, the stimulus-response pair” (Anderson, 1987b, p. 198).

  • However “ACT*” stands for “Adaptive Control of Thought”, and Anderson’s theory depends on the existence of “Declarative” subjectively available knowledge in long-term memory.

  • The twist is that for Anderson, the process of learning, which can be mapped on to someone’s progress from being a novice to being an expert at a particular cognitive skill, consists of the conversion of such verbally available knowledge into automatic habit-like rules — the expert has to think less about solving the problem than the novice.

  • The major learning mechanism posited by Anderson is knowledge compilation. This turns declarative knowledge ('knowing that' or 'knowing what') into proceduralized ('knowing how').

  • But this learning takes place at what Anderson calls the “mental algorithm” level, which corresponds to reportable states of working memory.

  • So although learning is limited to small pairwise units these are introspectively available as “knowing what to do next”.

  • The learning mechanism is traditional in that the pairwise units (productions) accumulate strength as a result of practice, which as Glaser (1990) says is very like the supposed strengthening of associative bonds in stimulus- response learning theory.

  • Little emphasis is placed on acquiring skills by understanding the principles behind them, and indeed Anderson (1987b) quotes experiments in which students given “how to do it” information learned to solve a computer-programming task more quickly than those given “why it works” information.

  • But Anderson shares with Tomasello et al (1993) the view that learning is a crucial and special aspect of human psychology —


[bottom of page 3 of wk 13 handout]


Our most uniquely human attribute is our ability to acquire new abilities to deal with novel problems” [Anderson, 1987a, p.475].

Most human skills and knowledge are not reinvented anew through raw induction by each generation but are passed from one generation to the next.” [Anderson, 1987a, p.474]









4. Conclusions [bottom of page 3]

There is no general agreement about the nature of human learning and the role it plays. However there is current support both from developmental psychologists (Tomasello et al, 1993 Tomasello, 2001; Tomasello & Rakoczy, 2003; Leslie et al., 2005; Matsuzawa, 2007) and those concerned with methods for the training of specific cognitive skills (Anderson, 1987, 1990; Glaser, 1990; Howe, 1998; Howe et al, 1998; Hartley, 1998; Posner & Rothbart, 2005) for the position that learning is a crucial factor in human psychology. It is reasonable to conclude that additional cognitive capacities mean that the scope of human learning is radically different from that available to other species since people can profit from instruction, both that received from others and self-instruction. But there remain similarities between aspects of traditional theories of animal learning and certain current approaches to human learning.





It is noteworthy, for instance, that two theoretical papers published in the Psychological Review in 2001 supported modern versions of conditioning theories of the causation and treatment of neurotic disorders (Bouton et al., 2001; Ohman and Mineka, 2001: see also Battaglia & Ogliari, 2005 and Hermans et al., 2005).





Not suprisingly, reference to human learning is continues to be common in educational contexts (Chi et al., 2001; Hammond and Bennett,, 2002; Parikh and Verma, 2002; Howe, 1998; Posner & Rothbat, 2005). In particular, systematic studies of Computer-Aided Instruction have suggested that learning is promoted by practice and goal achievement (Issroff and Scanlon, 2002) and may in some cases be assisted by immediate feedback and the minimization of errors (Glaser, 1990).





[top of page 4 of wk 13 handout]
In an entirely different way, in the theoretical analysis of how learning of complex skills can be achieved by simulated neural nets, connectionist modeling rests on the assumption that learning ultimately depends on the growth of low-level associations (Week 12). However, most treatments of human learning include some reference to “high-level” abilities involved in systematic thought and the self-regulation of learning strategies (Glaser, 1990; Hartley, 1998; Tomasello et al., 1993, 2005; Tomasello & Rakoczy, 2003). In so far as these “high level” abilities are important in human learning, connectionist models are not helpful, except possibly for the purpose of explaining how the high-level abilities are implemented at the neural level.
[see also bottom of page 11]

Main sources and further reading

Glaser, R. (1990) The reemergence of learning theory within instructional research. American Psychologist 45, 29-39

Hartley J. (1998) Learning and Studying: A Research Perspective. London: Routledge. [378.17 HAR:Short Loan]

Howe, M.J.A.(1998) Principles of Abilities and Human Learning. Hove:Psychology Press. [153.15 HOW: Short Loan]

Howe, M.J.A., Davidson, J.W. and Sloboda, J.A. (1998) Innate talents: Reality or myth? Behavioural and Brain Sciences, 21, 399-442.

Tomasello, M. Kruger, A.C. and Ratner, H.H. (1993) Cultural learning. Behavioural and Brain Sciences, 16, 495-552.

Tomasello, M., & Rakoczy, H. (2003). What makes human cognition unique? From individual to shared to collective intentionality. Mind & Language, 18(2), 121-147.


Some Additional References Related to Human Learning (not for further reading)

Allman, J. M., Watson, K. K., Tetreault, N. A., & Hakeem, A. Y. (2005). Intuition and autism: a possible role for Von Economo neurons. Trends in Cognitive Sciences, 9(8), 367-373.

Anderson, J. R. (1987a) Methodologies for studying human knowledge. Behavioural and Brain Sciences, 10, 467-505.

Anderson, J. R. (1987b) Skill acquisition; Compilation of weak-method problem solutions. Psychological Review, 94, 192-210.

Anderson, J. R. (1990) The Adaptive Character of Thought. Hillsdale, N J: Lawrence Erlbaum.

Anderson, J. R. (2002). Spanning seven orders of magnitude: a challenge for cognitive modeling. Cognitive Science, 26(1), 85-112.

Anderson, J. R. (2005). Human symbol manipulation within an integrated cognitive architecture. Cognitive Science, 29(3), 313-341.

Anderson, J. R., Bothell, D, Lebiere, C, Matessa, M (1998) An integrated theory of list memory. Journal of Memory and Language, Vol.38, No.4, Pp.341-380 Is: 0749-596x.

Anderson, J. R., Corbett, AT, Koedinger, KR, Pelletier, R (1995) Cognitive tutors - lessons learned. Journal of the Learning Sciences, Vol.4, No.2, Pp.167-207

Anderson, J. R., Fincham, JM, Douglass, S (1997) The role of examples and rules in the acquisition of a cognitive skill. Journal of Experimental Psychology-Learning Memory and Cognition, Vol.23, No.4, Pp.932-945.

Anderson, J. R., Matessa, M (1997) A production system theory of serial memory. Psychological Review, Vol.104, No.4, Pp.728-748 Is: 0033-295x.

Anderson, J. R., Matessa, M, Lebiere, C (1997) ACT-R: a theory of higher level cognition and its relation to visual attention. Human-Computer Interaction, Vol.12, No.4, Pp.439-462.

Ashby, E. G., & Maddox, W. T. (2005). Human category learning. Annual Review of Psychology, 56, 149-178.

Bain, J. D., & McNaught, C. (2006). How academics use technology in teaching and learning: understanding the relationship between beliefs and practice. Journal of Computer Assisted Learning, 22(2), 99-113.

Battaglia, M., & Ogliari, A. (2005). Anxiety and panic: from human studies to animal research and back. Neuroscience and Biobehavioral Reviews, 29(1), 169-179.

Berry, DC (1994) Implicit learning - 25 years on - a tutorial. Attention and Performance, Vol.15, Pp.755-782.

Bons, N., Rieger, F., Prudhomme, D., Fisher, A., & Krause, K. H. (2006). Microcebus murinus: a useful primate model for human cerebral aging and Alzheimer's disease? Genes Brain and Behavior, 5(2), 120-130.

Bouton, M. E., Mineka, S., & Barlow, D. H. (2001). A modern learning theory perspective on the etiology of panic disorder. Psychological Review, 108(1), 4-32.

Call, J. & Tomasello, M (1999) A nonverbal false belief task: the performance of children and great apes. Child Development, Vol.70, No.2, Pp.381-395.

Carpenter, M, Akhtar, N, Tomasello, M (1998) Fourteen through 18-month-old infants differentially imitate intentional and accidental actions. Infant Behavior & Development, Vol.21, No.2, Pp.315-330 Is: 0163-6383.

Carpenter, M, Tomasello, M, Savage-Rumbaugh, S (1995) Joint attention and imitative learning in children, chimpanzees, and enculturated chimpanzees. Social Development, Vol.4, No.3, Pp.217-237

Carpenter, M., Nagell, K., & Tomasello, M. (1998). Social cognition, joint attention, and communicative competence from 9 to 15 months of age. Monographs of the Society for Research in Child Development, 63(4), 176--

Chi, M. T. H., Siler, S. A., Jeong, H., Yamauchi, T., & Hausmann, R. G. (2001). Learning from human tutoring. Cognitive Science, 25(4), 471-533.

Chiappe, D., & MacDonald, K. (2005). The evolution of domain-general mechanisms in intelligence and learning. Journal of General Psychology, 132(1), 5-40.

Christiansen, M. H., Chater, N., & Seidenberg, M. S. (1999). Special issue - Connectionist models of human language processing: Progress and prospects. Cognitive Science, 23(4), 415-415.

Cox, S. M. L., Andrade, A., & Johnsrude, I. S. (2005). Learning to like: A role for human orbitofrontal cortex in conditioned reward. Journal of Neuroscience, 25(10), 2733-2740.

Driscoll, I., Hamilton, D. A., Yeo, R. A., Brooks, W. M., & Sutherland, R. J. (2005). Virtual navigation in humans: the impact of age, sex, and hormones on place learning. Hormones and Behavior, 47(3), 326-335.

Elman, J. L. (2005). Connectionist models of cognitive development: where next? Trends in Cognitive Sciences, 9(3), 111-117.

Elston, G. N., Benavides-Piccione, R., Elston, A., Zietsch, B., Defelipe, J., Manger, P., et al. (2006). Specializations of the granular prefrontal cortex of primates: Implications for cognitive processing. Anatomical Record Part a-Discoveries in Molecular Cellular and Evolutionary Biology, 288A(1), 26-35.

Ericsson, KA, Charness, N (1994) Expert performance - its structure and acquisition. American Psychologist, Vol.49, No.8, Pp.725-747.

Ericsson, KA, Lehmann, AC (1996) Expert and exceptional performance - evidence of maximal adaptation to task constraints. Annual Review of Psychology, Vol.47, Pp.273-305

Evans, P. D., Gilbert, S. L., Mekel-Bobrov, N., Vallender, E. J., Anderson, J. R., Vaez-Azizi, L. M., et al. (2005). Microcephalin, a gene regulating brain size, continues to evolve adaptively in humans. Science, 309(5741), 1717-1720.

Fletcher, J., Maybery, M. T., & Bennett, S. (2000). Implicit learning differences: A question of developmental level? Journal of Experimental Psychology-Learning Memory and Cognition, 26(1), 246-252.

Foster, D. J., & Wilson, M. A. (2006). Reverse replay of behavioural sequences in hippocampal place cells during the awake state. Nature, 440(7084), 680-683.

Glaser, R. and Bassok, M. (1989) Learning theory and the study of instruction. Annual Review of Psychology, 40, 631-666. Palo Alto CA: Annual Reviews Inc.

Goldstone, RL (1998) Perceptual learning. Annual Review of Psychology, Vol.49, Pp.585-612.

Hammond, N., & Bennett, C. (2002). Discipline differences in role and use of ICT to support group- based learning. Journal of Computer Assisted Learning, 18(1), 55-63.

Hermans, D., Dirikx, T., Vansteenwegenin, D., Baeyens, F., Van den Bergh, O., & Eelen, P. (2005). Reinstatement of fear responses in human aversive conditioning. Behaviour Research and Therapy, 43(4), 533-551.

Hikosaka, O., Nakamura, K., Sakai, K., & Nakahara, H. (2002). Central mechanisms of motor skill learning. Current Opinion in Neurobiology, 12(2), 217-222.

Hof, P. R., & Van Der Gucht, E. (2007). Structure of the cerebral cortex of the humpback whale, Megaptera novaeangliae (Cetacea, Mysticeti, Balaenopteridae). Anatomical Record-Advances in Integrative Anatomy and Evolutionary Biology, 290(1), 1-31.

Issroff, K., & Scanlon, E. (2002). Using technology in higher education: an Activity Theory perspective. Journal of Computer Assisted Learning, 18(1), 77-83.

Johnson, M. H., & Munakata, Y. (2005). Processes of change in brain and cognitive development. Trends in Cognitive Sciences, 9(3), 152-158.

Leslie, A. M., German, T. P., & Polizzi, P. (2005). Belief-desire reasoning as a process of selection. Cognitive Psychology, 50(1), 45-85.

Leslie, AM (1994) Pretending and believing - issues in the theory of ToMM. Cognition, Vol.50, No.1-3, Pp.211-238

Marino, L., Connor, R. C., Fordyce, R. E., Herman, L. M., Hof, P. R., Lefebvre, L., et al. (2007). Cetaceans have complex brains for complex cognition. Public Library of Science Biology, 5(5), 966-972.

Marsolek, C. J., & Field, J. E. (1999). Perceptual-motor sequence learning of general regularities and specific sequences. Journal of Experimental Psychology-Human Perception and Performance, 25(3), 815-836.

Matsuzawa, T. (2007). Comparative cognitive development. Developmental Science, 10(1), 97-103.

Maxwell, J. P., Masters, R. S. W., Kerr, E., & Weedon, E. (2001). The implicit benefit of learning without errors. Quarterly Journal of Experimental Psychology Section a-Human Experimental Psychology, 54(4), 1049-1068.

Moll, H., & Tomasello, M. (2007). Cooperation and human cognition: the Vygotskian intelligence hypothesis. Philosophical Transactions of the Royal Society B: Biological Sciences, 362(1480), 639-648.

Moses, S. N., & Ryan, J. D. (2006). A comparison and evaluation of the predictions of relational and conjunctive accounts of hippocampal function. Hippocampus, 16(1), 43-65.

Newell, A. and Simon, H.A. (1972) Human Problem Solving. Englewood Cliffs, NJ: Prentice-Hall.

O'Doherty, J. P. (2004). Reward representations and reward-related learning in the human brain: insights from neuroimaging. Current Opinion in Neurobiology, 14(6), 769-776.

Ohman, A., & Mineka, S. (2001). Fears, phobias, and preparedness: Toward an evolved module of fear and fear learning. Psychological Review, 108(3), 483-522.

Padoa-Schioppa, C., & Assad, J. A. (2006). Neurons in the orbitofrontal cortex encode economic value. Nature, 441(7090), 223-226.

Panksepp, J. (2005). Affective consciousness: Core emotional feelings in animals and humans. Consciousness and Cognition, 14(1), 30-80.

Paton, J. J., Belova, M. A., Morrison, S. E., & Salzman, C. D. (2006). The primate amygdala represents the positive and negative value of visual stimuli during learning. Nature, 439(7078), 865-870.

Perner, J, Ruffman, T, Leekam, SR (1994) Theory of mind is contagious - you catch it from your sibs. Child Development, Vol.65, No.4, Pp.1228-1238

Piatelli-Palmarini, M. (1989) Evolution & cognition: From "learning" to parameter setting in biology and the study of language. Cognition, 31, 1-44.

Pinker, S (1998) How the Mind Works. Allen Lane, London

Ponting, C., & Jackson, A. P. (2005). Evolution of primary microcephaly genes and the enlargement of primate brains. Current Opinion in Genetics & Development, 15(3), 241-248.

Posner, M. I., & Rothbart, M. K. (2005). Influencing brain networks: implications for education. Trends in Cognitive Sciences, 9(3), 99-103.

Pruetz, J. D., & Bertolani, P. (2007). Savanna chimpanzees, Pan troglodytes verus, hunt with tools. Current Biology, 17(5), 412-417.

Ramberg, R. and Karlgren, K. (1998) Fostering superficial learning. Journal of Computer Assisted Learning, 14, 120-129.

Reed, J. M., & Means, L. W. (2004). Human implicit memory for irrelevant dimension values is similar to rats' incidental memory in simultaneous discrimination tasks. Behavioural Processes, 67(3), 383-393.

Roth, G., & Dicke, U. (2005). Evolution of the brain and intelligence. Trends in Cognitive Sciences, 9(5), 250-257.

Saxe, R. (2006). Uniquely human social cognition. Current Opinion in Neurobiology, 16(2), 235-239.

Schultz, W. (2006). Behavioral theories and the neurophysiology of reward. Annual Review of Psychology, 57(1), 87-115.

Seger, CA (1994) Implicit learning. Psychological Bulletin, Vol.115, No.2, Pp.163-196.

Sekiyama, K., Miyauchi, S., Imaruoka, T., Egusa, H., & Tashiro, T. (2000). Body image as a visuomotor transformation device revealed in adaptation to reversed vision. Nature, 407(6802), 374-377.

Sim, G., MacFarlane, S., & Read, J. (2006). All work and no play: Measuring fun, usability, and learning in software for children. Computers & Education, 46(3), 235-248.

Skowronski, M. D., & Harris, J. G. (2006). Acoustic detection and classification of microchiroptera using machine learning: Lessons learned from automatic speech recognition. Journal of the Acoustical Society of America, 119(3), 1817-1833.

Stout, D., & Chaminade, T. (2007). The evolutionary neuroscience of tool making. Neuropsychologia, 45(5), 1091-1100.

Sun, T., & Walsh, C. A. (2006). Molecular approaches to brain asymmetry and handedness. Nature Reviews Neuroscience, 7(8), 655-662

Thorndike, E.L (1903) Educational Psychology. New York. Lemke and Buechner.

Tomasello, M. (1999). The human adaptation for culture. Annual Review of Anthropology, 28, 509-529.

Tomasello, M. (2001). Cultural transmission - A view from chimpanzees and human infants. Journal of Cross-Cultural Psychology, 32(2), 135-146.

Tomasello, M., & Rakoczy, H. (2003). What makes human cognition unique? From individual to shared to collective intentionality. Mind & Language, 18(2), 121-147.

Tomasello, M., Carpenter, M., Call, J., Behne, T., & Moll, H. (2005). In search of the uniquely human - Response. Behavioral and Brain Sciences, 28(5), 721-735.

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(5), 675-+.

Tyc, F., Boyadjian, A., & Devanne, H. (2005). Motor cortex plasticity induced by extensive training revealed by transcranial magnetic stimulation in human. European Journal of Neuroscience, 21(1), 259-266.

Vaes, J., Paladino, M. P., & Leyens, J. P. (2002). The lost e-mail: Prosocial reactions induced by uniquely human emotions. British Journal of Social Psychology, 41, 521-534.

Vincent, J. L., Patel, G. H., Fox, M. D., Snyder, A. Z., Baker, J. T., Van Essen, D. C., et al. (2007). Intrinsic functional architecture in the anaesthetized monkey brain. Nature, 447(7140), 83-U84.

Wijekumar, K. J., Meyer, B. J. F., Wagoner, D., & Ferguson, L. (2006). Technology affordances: the 'real story' in research with K-12 and undergraduate learners. British Journal of Educational Technology, 37(2), 191-209.