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One of my research interests is in simulating evolution of body and brain/mind modularity in complex organisms by means of artificial neural networks and genetic algorithms (Calabretta & Neirotti, 2015; Calabretta & Parisi, 2005; Wagner, Mezey & Calabretta, 2005; Calabretta et al., 2000). In 1997 I spent one sabbatical year as post-doctoral fellow at Yale University Department of Biology and in 2000 and 2002 came back to Yale as visiting fellow at the Department of Ecology and Evolutionary Biology and of Psychology. I collaborate with Gunter Wagner (founding chair of the Department of Ecology and Evolutionary Biology) and Frank Keil (Faculty of Psychology, editor of The MIT Encyclopedia of Cognitive Sciences, MIT Press, 1999). 

 "The existence of modules is recognized at all levels of the biological hierarchy. In order to understand what modules are, why and how they emerge and how they change, it would be necessary to start a joint effort by researchers in different disciplines (evolutionary and developmental biology, comparative anatomy, physiology, neuro- and cognitive science). This is made difficult by disciplinary specialization. [...] we claim that, because of the strong similarities in the intellectual agenda of artificial life and evolutionary biology and of their common grounding in Darwinian evolutionary theory, a close interaction between the two fields could easily take place. Moreover, by considering that artificial neural networks draw an inspiration from neuro- and cognitive science, an artificial life approach to the problem could theoretically enlarge the field of investigation." (Calabretta et al., 1998)

A general definition of modularity and nonmodularity in neural networks can be the following: "modular systems can be defined as systems made up of structurally and/or functionally distinct parts. While non-modular systems are internally homogeneous, modular systems are segmented into modules, i.e., portions of a system having a structure and/or function different from the structure or function of other portions of the system. [...] In a nonmodular architecture one and the same connection weight may be involved in two or more tasks. In a modular architecture each weight is always involved in a single task: Modules are sets of 'proprietary' connections that are only used to accomplish a single task." (Calabretta & Parisi, 2005, Fig. 14.4; see also Calabretta et al., 2003).

Recently Jose' B. Pereira-Leal and Sarah A. Teichmann of the 'Laboratory of Molecular Biology, Structural Studies Division' at Cambridge University (the so called laboratory of Nobel laureates), provided strong support for Calabretta et al.'s (2000) hypothesis on the evolution of modularity:

"Duplication of modules has been shown to be an efficient mechanism for the generation of functional innovation in the field of artificial intelligence, but has not been studied in biological networks. Therefore, we ask whether module duplication occurs in cellular networks. We developed a generic framework for the analysis of module duplication, and use it in a large-scale analysis of Saccharomyces cerevisiae protein complexes. [...] The mechanisms that underlie the evolution of functional modules are largely unknown. Theoretical simulations in neural networks have shown that duplication and specialization of en-tire modules is an effective mode of network growth (Calabretta et al. 1998, 2000). [...] These results strongly support the view that complex duplication is a mechanism by which evolution generates functional specialization. This extends what has been found previously for duplication of individual genes (Prince and Pickett 2002), and is in agreement with the behavior of artificial systems such as neural networks (Calabretta et al. 2000)" (Pereira-Leal & Teichnmann, 2006, pp. 552 and 557).

Other simulation results, for the first time, revealed the existence of genetic interference, a new population genetic mechanism that is independent from the network architecture. Our simulations clearly show that genetic interference reduces the evolvability of visual neural networks and that sexual reproduction can at least partially solve the problem of genetic interference. It was shown that entrusting the task of finding the neural network architecture to evolution and that of finding the network connection weights to learning is a way to completely avoid the problem of genetic interference. On the basis of this evidence, it is possible to formulate a new hypothesis on the origin of structural modularity, and thus to overcome the traditional dichotomy between innatist and empiricist theories of mind (see Calabretta, 2007). 


[Here you will find my full short biography;
here and below you will find the list of my scientific publications (most of all are available on line)
here you will find the citations received by my papers]

Evolving modularity:  studying the evolution of organism modular design by using Artificial Life simulations (Raffaele Calabretta, Andrea Di Ferdinando, Frank Keil, Domenico Parisi, Gunter P. Wagner)

Artificial Life

Journals: Artificial Life, Adaptive Behavior; Santa Fe Institute: Current Research Projects

Cognitive Science

The Cognitive Science Society; Journals: Cognitive Science, Cognition, Cogntive Systems Research

Neuro-science Laboratories and Seminars 

Laboratory of Brain and Cognition, National Institute of Mental Health, Bethesda, MA (Leslie Ungerleider)

Laboratory of Neuropsychology, National Ins

NIH Neuroscience Seminar Series



Modularity - Understanding the Development and Evolution of Complex Natural Systems, Altenberg Workshops in Theoretical Biology, Konrad Lorenz Institute for Evolution and Cognition Research, Altenberg (Austria), October 26-29, 2000. (See Callebaut & Rasskin-Gutman, 2005)

Modularity in development and evolution, symposium, Hanse Institute for Advanced Study, Delmenhorst (Germany), May 11-14, 2000.

Modularity of animal form: beyond homology and analogy, workshop, Friday Harbor Laboratories, September 5-8, 1997

Altenberg, L. 1995. Genome growth and the evolution of the genotype-phenotype map. In W. Banzhaf  and F. H. Eeckman (Eds.), Evolution and biocomputation. Computational models of evolution. Berlin: Springer Verlag. [abstract, pdf]

Ancel, L. W. and Fontana, W. (in press). Evolutionary Lock-in and the Origin of Modularity in RNA Structure. In W. Callabaut & D. Rasskin-Gutman (Eds.),  Modularity. Understanding the development and evolution of complex natural systems, The MIT Press, Cambridge, MA. [Preprint]

Barrett, H. C., and Kurzban, R. (2006). Modularity in cognition: Framing the debate. Psychological Review, 113, 628-647. [Full text]

Bates, E. (1994). Modularity, domain specificity and the development of language. Discussions in Neuroscience, 10:136-149. [pdf]

Brooks, R. A. (1986). A robust layered control system for a mobile robot. IEEE Journal of Robotics and Automation 2:14-23.

Calabretta, R. & Neirotti, J. (2015). Adaptive agents in changing environments: the role of modularity. Neural Processing Letters 42(2), 257-274. doi:10.1007/s11063-014-9355-8 [abstract; pdf]

Calabretta, R. (2013). A novel's structure as a complex system. International Journal of Creativity & Problem Solving 23(2), 113-120.
Calabretta, R. (2010). Doparie, dopo le primarie. Diario di un elettore errante alla ricerca della felicita'. Nutrimenti editore, Rome. [A modular scientific novel (about participatory democracy and emotions) that conveys scientific theories and results (in Italian)]
Calabretta, R. (2010). Evolution, (sequential) learning and generalization in modular and nonmodular visual neural networks. In Graeme Ruxton & Colin Tosh (Eds.), Modelling Perception with Artificial Neural Networks. Cambridge University Press, Cambridge, UK.
Calabretta, R. (2010). A hypertextual novel that dramatizes the process of its creation and proposes techniques to increase creativity. Biological Theory (MIT Press) 5(2), 102-105. [pdf
Calabretta, R., Di Ferdinando, A., Parisi, D., Keil, F. C. (2008). How to learn multiple tasks. Biological Theory (MIT Press) 3(1), 30-41.[pdf[draft: doc, pdf]
Calabretta, R. (2007, second edition). Il film delle emozioni. Alberto Gaffi Editore, Rome. [A modular scientific novel (about emotions) that conveys scientific theories and results (in Italian)] [pdf]
Calabretta, R. (2007). Genetic interference reduces the evolvability of modular and nonmodular visual neural networks. Philosophical Transactions of The Royal Society B: Biological Sciences 362(1469), 403-10. (invited paper) [abstract full text pdf] [draft: doc, pdf]
Calabretta, R. & Parisi, D. (2005). Evolutionary Connectionism and Mind/Brain Modularity. In W. Callabaut & D. Rasskin-Gutman (Eds.),  Modularity. Understanding the development and evolution of complex natural systems, pp. 309-330. The MIT Press, Cambridge, MA. [pdf] [draft: doc, pdf; updated June 4, 2001]

Calabretta, R., Di Ferdinando, A., & Parisi, D. (2004). Ecological neural networks for object recognition and generalization. Neural Processing Letters  19, 37-48 [pdf [draft: doc, pdf]

Calabretta, R., Di Ferdinando, A., Wagner, G. P. & Parisi, D. (2003). What does it take to evolve behaviorally complex organisms? BioSystems 69, 245-262 [pdf] [draft: doc, pdf]

Calabretta, R., Nolfi, S., Parisi, D. & Wagner, G. P. (2000). Duplication of modules facilitates the evolution of functional specialization. Artificial Life 6:69-84. [pdf] [draft: abstract, pdf]

Calabretta, R., Nolfi, S., Parisi, D., and Wagner, G. P. (1998a). Emergence of functional modularity in robots. In Pfeifer, R., Blumberg, B., Meyer, J.-A., and Wilson, S.W. (Eds.), From Animals to Animats 5, pp. 497-504. The MIT Press, Cambridge, MA. [pdf[draft: abstract, pdf]

Calabretta, R., Nolfi, S., Parisi, D., and Wagner, G. P. (1998b). A case study of the evolution of modularity: towards a bridge between evolutionary biology, artificial life, neuro- and cognitive science. In Adami, C., Belew, R. Kitano, H., and Taylor, C. (Eds.), Proceedings of the Sixth International Conference on Artificial Life, pp. 275-284. The MIT Press, Cambridge, MA.[pdf] [draft: abstract, pdf]

Callabaut, W. & Rasskin-Gutman, D. (2005, 2007, 2009). Modularity. Understanding the development and evolution of complex natural systems. Cambridge, MA: MIT Press.
Carruthers, P. (2003). Is the mind a system of modules shaped by natural selection? In: C. Hitchcock (Ed.), Contemporary Debates in the Philosophy of Science. Blackwell, Oxford.
Chalmers, D. J. (?). A Computational Foundation for the Study of Cognition.  Unpublished paper; parts of it have appeared as "On Implementing a Computation" in Minds and Machines (1994). [pdf]
Cho, S-B. and Shimohara, K. (1997). Emergence of Structure and Function in Evolutionary Modular Neural Networks. In Husbands, P. and Harvey, I., editors, Proceedings of Fourth European Conference on Artificial Life. The MIT Press, Cambridge, MA.
Chomsky, N. (1980). Rules and representations. Columbia University Press, New York.
Clark, A. (1997). Being there: Putting brain, body, and world together again. The MIT Press, Cambridge, MA.
Clune, J., Mouret, J.-B., Lipson, H. (2013). The evolutionary origins of modularity. Proceedings of the Royal Society B 280: 20122863. [pdf
Cosmides, L. and Tooby, J. (1994). The evolution of domain specificity: the evolution of functional organization. In Hirschfeld, L. A., and Gelman, S. A. (Eds.), Mapping the Mind: Domain Specificity in Cognition and Culture. The MIT Press, Cambridge, MA.
Di Ferdinando, A., Calabretta, R., & Parisi, D. (2001). Evolving modular architectures for neural networks. In R. French & J. Sougne' (Eds.), Proceedings of the Sixth Neural Computation and Psychology Workshop Evolution, Learning, and Development, pp. 253-262, London: Springer Verlag. [pdf] [draft: abstract, pdf, doc]
Edelman, G. (1987). Neural Darwinism. Basic Books.

Elman, J. L., Bates, E. A., Johnson, M. H., Karmiloff-Smith, A., Parisi, D. & Plunkett, K. (1996). Rethinking innateness. A connectionist perspective on development. The MIT Press, Cambridge, MA.

Elman, J.L. (1998). Generalization, simple recurrent networks, and the emergence of structure. In M.A. Gernsbacher and S.J. Derry (Eds.) Proceedings of the Twentieth Annual Conference of the Cognitive Science Society. Mahwah, NJ: Lawrence Erlbaum Associates. [pdf]
Elman, J. L. (1998). Connectionism, artificial life, and dynamical systems: New approaches to old questions. In W. Bechtel and G. Graham (Eds.) A Companion to Cognitive Science. Oxford: Basil Blackwood. [pdf]
Emiliani, F., Mazzara, B.M. (2015). Dalla naturalizzazione delle scienze umane alla naturalità dell'ovvio. Le ragioni sociali per le quali la mente non è il cervello. Giornale Italiano di Psicologia 1-2, 36-56 [Target Article, in Italian]
Farah, M. J. (2014), Brain Images, Babies, and Bathwater: Critiquing Critiques of Functional Neuroimaging. Hastings Center Report, 44: S19–S30. doi: 10.1002/hast.295 [html, pdf]

Fodor, J. (1983). The Modularity of mind. The MIT Press, Cambridge, MA.

Fodor, J. (1998). The Trouble with Psychological Darwinism. London Review of Books Vol 20, No 2 (cover date 15 January 1998). [pdf]

Fodor, J. (2000). The Mind Doesn't Work That Way:The Scope and Limits of Computational Psychology. The MIT Press, Cambridge, MA. First chapter

Frazier, Lyn (1999). Modularity and Language. In R. A. Wilson and F. C. Keil (Eds.), The MIT encyclopedia of the cognitive sciences, pp. 558-560. The MIT Press, Cambridge, MA.
French, R. M. (1999). A review of catastrophic forgetting in connectionist networks. Trends in Cognitive Sciences, 3(4), 128-135.
Friston, K. J. & Price, C. J. (2011). Modules and brain mapping. Cognitive Neuropsychology 28(3-4), 241-50. [pdf]

Gardner, H. (1985). Frames of mind: the theory of multiple intelligences. Heinemann, London.

Goldstone, R. L., & Barsalou, L. (1998). Reuniting perception and conception. Cognition, 65, 231-262. (reprinted as: Goldstone, R. L., & Barsalou, L. (1998).  Reuniting perception and conception.  In S. A. Sloman and L. J. Rips (Eds.) Similarity and symbols in human thinking.  (pp. 145-176).  Cambridge, MA: MIT Press). [pdf, html]

Gruau, F. (1994). Automatic definition of modular neural networks. Adaptive Behavior, 2:151-183.

Jacobs, R. A., Jordan, M. I. & Barto, A. G. (1991). Task decomposition through competition in a modular connectionist architecture: The what and where vision tasks. Cognitive Science 15:219-250.

Jacobs, R.A., Jordan, M.I., Nowlan, S.J., and Hinton, G.E. (1991). Adaptive mixtures of local experts. Neural Computation, 3, 79-87. [pdf]

Jacobs, R. A. & Jordan, M. I. (1992). Computational consequences of a bias toward short connections. Journal of Cognitive Neuroscience 4:323-335.

Jacobs, R.A. and Kosslyn, S.M. (1994). Encoding shape and spatial relations: The role of receptive field size in coordinating complementary representations. Cognitive Science, 18, 361-386. [pdf]
Jen, E. (2003). Stable or robust? What’s the difference? Santa Fe Institute Working Paper 2002. Complexity 8(3), 12-18. [pdf]
Johnson, M. H. & Morton, J. (1991). Biology and cognitive development: The case of face recognition. Blackwell, Cambridge, MA.

Karmiloff-Smith, A. (1992). Beyond modularity: A developmental perspective on cognitive science. The MIT Press, Cambridge, MA.

Karmiloff-Smith, A. (1999). Modularity of mind. In R. A. Wilson and F. C. Keil (Eds.), The MIT encyclopedia of the cognitive sciences, pp. 558-560. The MIT Press, Cambridge, MA.

Kashtan, N. & Alon, U. (2005). Spontaneous evolution of modularity and network motifs. PNAS 102 (39), 13773-13778. [pdf]

Keil, F. C. (1999). Nativism. In R. A. Wilson and F. C. Keil (Eds.), The MIT encyclopedia of the cognitive sciences, The MIT Press, Cambridge, MA

Lalonde, C. E. (2001). Physical Knowledge in Infancy according to Cognitivist Developmental Psychologists: Web demo.
Leslie, A.M., & Keeble, S. (1987). Do six-month-old infants perceive causality? Cognition 25, 265–288. [pdf]
  Leslie, A.M., & Thaiss, L. (1992). Domain specificity in conceptual development: Neuropsychological evidence from autism. Cognition 43, 225–251. [pdf]
Marcus, G. F. (1998). Rethinking eliminative connectionism. Cognitive Psychology.
Marcus, G. F. (1998a). Can connectionism save constructivism? Cognition 66:153-182.
Marcus, G. F., Vijayan, S., Bandi Rao, S. and Vishton, P.M. (1999).  Rule learning in seven-month-old infants.  Science.
Marcus, G. F. (2006). Cognitive architecture and descent with modification. Cognition 101, 443-465. [pdf]
Milner, A.D. & Goodale, M.A. (1995). The visual brain in action. Oxford University Press, Oxford. [see Symposium on-line]

Moscovitch, M. and Umilta', C. (1990). Modularity and neuropsychology: implications for the organization of attention and memory in normal and brain-demaged people. In Schwartz, M. F. (eds.), Modular Deficits in Alzheimer-type dementia. The MIT Press, Cambridge, MA. 

Murre, J. M. J. (1992). Learning and categorization in modular neural networks. Harvester, New York, NY.

Nolfi, S. (1997). Using emergent modularity to develop control systems for mobile robots. Adaptive Behavior, 5:343-363.

Nolfi, S., Baldassarre G., Calabretta R., Hallam J., Marocco D., Meyer J-A., Parisi, D. (2006). From animals to animats 9: Proceedings of the Ninth International Conference on Simulation of Adaptive Behaviour, LNAI. Volume 4095. Springer Verlag, Berlin.
Pereira-Leal, J. B. and Teichmann, S. A.  (2005). Novel specificities emerge by stepwise duplication of functional modules. Genome Research 15:552-559. [pdf]

Pinker, S. (1994). The Language Instinct: how the mind creates language. New York: William Morrow.

Philosophy of mind: a field guide

Pylyshyn, Z. W. (1999). Is Vision Continuous With Cognition? The Case for Cognitive Impenetrability of Visual Perception. Behavioral & Brain Science 22(3): 341-423. [version on line]

Rueckl, J. G., Cave, K. R. & Kosslyn, S. M. (1989). Why are "what" and "where" processed by separate cortical visual systems? A computational investigation. Journal of Cognitive Neuroscience 1:171-186.

Rumelhart, D. E. & McClelland, J. L. (1986). On Learning the Past Tenses of English Verbs. In McClelland, J. L. and D.E. Rumelhart (eds.), Parallel Distributed Processing. Volume 2. The MIT Press, Cambridge, MA.

Scholl, B.J., &  Leslie, A.M. (1999b). Modularity, development and 'theory of mind’. Mind & Language, 14, 131-153. [pdf]
Seidenberg, M., & Elman, J.L. (1999). Do infants learn grammar with algebra or statistics? Letter to Science commenting on Marcus et al., 1999. Science, 284, April 16, 1999; p 433. [html]

Spelke, E. S., Breinlinger, K., Macombe, J. & Jacobson, K. (1992). Origins of knowledge. Psychological Review 99, 605-632.

Sperber, D. (2002). In Defense of massive modularity. In E. Dupoux (Ed.), Language, Brain and Cognitive Development: Essays in Honor of Jacques Mehler, 47-57. The MIT Press, Cambridge, MA. [pdf]

Sperber, D., Hirschfeld, A.(2004). The cognitive foundations of cultural stability and diversity. Trends in Cognitive Sciences 8, Issue 1, 40-46. [pdf]
Sternberg, S. (2001) Separate modifiability, mental modules, and the use of pure and composite measures to reveal them. Acta Psychologica, 106, 147-246. [pdf]
Tosh, C R. &  McNally, L. (2015). The relative efficiency of modular and non-modular networks of different size. Proceedings of the Royal Society of London B: Biological Sciences 282, 20142925.

Ungerleider, L. G. & Mishkin, M. (1982). Two cortical visual systems. In D. J. Ingle, M. A. Goodale & R. J. W. Mansfield (Eds.), The Analysis of Visual Behavior. The MIT Press, Cambridge, MA.

Uttal, W. R. (2001). The New Phrenology. The Limits of Localizing Cognitive Processes in the Brain. The MIT Press, Cambridge, MA.

Yao, X. & Liu, Y. (1997). A new evolutionary system for evolving artificial neural networks. IEEE Transactions on Neural Networks, 8(3):694-713.

Wagner, G. P. (2014). Homology, genes, and evolutionary innovation. Princeton University Press. [introduction]

Wagner, G. P., Mezey, J. & Calabretta, R. (2005). Natural selection and the origin of modules. In W. Callabaut & D. Rasskin-Gutman (Eds.), Modularity. Understanding the development and evolution of complex natural systems, pp. 33-49. Cambridge, MA: MIT Press. [pdf] [draft: doc, pdf]

Wagner, G. P., Pavlicev, M. & Cheverud,  J. M. (2007). The road to modularity. Nature Reviews Genetics 8, 921-931. [pdf]

Wagner, G. P., and Altenberg, L. 1996. Complex adaptations and the evolution of evolvability. Evolution 50:967-976.

Wagner, G. P. 1995. Adaptation and the modular design of organisms. In Moran, F., Moreno, A., Merelo, J.J., and Chacon, P. eds. Lecture notes in artificial intelligence: advances in artificial life, 317-328. Berlino-Heidelberg: Springer-Verlag.

Wagner, G. P. 1996. Homologues, natural kinds and the evolution of modularity. American Zoologist 36:36-43.

Watson, R. A. (2006). Compositional Evolution. The Impact of Sex, Symbiosis, and Modularity on the Gradualist Framework of Evolution. Cambridge, MA: MIT Press. 

Wynn, K. (1992). Addition and subtraction by human infants. Nature, August 27, 749-750.

If you think of anything else that could be added to this list, please e-mail me

Raffaele Calabretta
Institute of Cognitive Sciences and Technologies 
Italian National Research Council (C.N.R.)

The Modularity Home Page ('la Home Page della Modularita'):

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Last Update: 08/08/2016
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