Abstract
The central focus in debates over broad evolutionary psychology is whether mental abilities can be understood as adaptive functions (Davies, 1996, p. 446). Narrow evolutionary psychology1 further closely couples the claim that mental abilities are adaptive to a commitment to modularity of mental functions. This linkage is presented as quite direct— if the mind is comprised of discrete modules, then we can ask what are the selective factors that promoted each module. If, on the other hand, the mind is comprised of a single, fully integrated, general processor, then it would be much harder for natural selection to promote cognitive capacities individually2. And it would be much harder for us to give an explanation of the evolution of particular mental abilities. Cummins and Allen (1998, p. 3) provide a succinct account of the link between modularity and narrow evolutionary psychology:
Taking an evolutionary approach to the explanation of cognitive function follows naturally from the growing body of neuroscientific evidence showing that the mind is divisible. The picture that is emerging from both noninvasive studies of normal brain function and from clinically defined syndromes resulting from brain damage from strokes, injury, and neurodevelopmental disorders is one of different substrates subserving different cognitive functions... The Cartesian view of a seamless whole makes it hard to see how such a whole could have come into being, except perhaps by an act of divine creation. By recognizing the modularity of mind, however, it is possible to see how human mentality might be explained by the gradual accretion of numerous special function pieces of mind.
EDITOR’S NOTE: In this book, the term ‘narrow evolutionary psychology’ signifies the approach to evolutionary psychology developed by Cosmides, Tooby, Buss, et al. This term was chosen not to imply that this approach has an inappropriately narrow point of view, but merely to suggest that the approach adopts a narrower range of assumptions than ‘broad evolutionary psychology’ (or, just ‘evolutionary psychology’). This latter term signifies evolutionary psychology generally, practiced with any of a very broad range of assumptions possible within the general framework of evolutionary approaches to psychology. For more detail on this terminology, see the editor’s introduction, p 1
The difficulty seems comparable to that in a standard feedforward connectionist networks where acquiring a new input-output pattern disrupts already acquired ones unless the previously acquired ones are retrained along with the new one. This is known as the problem of catastrophic interference. Two ways connectionists have tried to respond to mis difficulty is to provide a principled means of continually retraining on previously learning examples (McClelland, McNaughton, & O’Reilly, 1995) and by building in modules (Jacobs, Jordan, & Barto, 1991)
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Appelbaum, I. (1988). Fodor, modularity, and speech perception. Philosophical Psychology, 11, 317–330.
Bechtel, W. (2001). Decomposing and localizing vision: An exemplar for cognitive neuroscience. In W. Bechtel, P. Mandik, J. Mundale, & R. S. Stufflebeam (Eds.), Philosophy and the Neurosciences: A Reader. Oxford, Eng.: Basil Black well.
Bechtel, W., & Richardson, R. C. (1993). Discovering Complexity: Decomposition and Localization as Scientific Research Strategies. Princeton, NJ: Princeton University Press.
Broca, P. (1861). Remarque sur le Siege de la Faculte Suivies d’une Observation d’Aphemie. Bulletins de la Societe Anatomique de Paris, 6, 343–357.
Brodmann, K. (1909/1994). Vergleichende Lokalisationslehre der Grosshirnrinde (L. J. Garvey, Trans.). Leipzig: J. A. Barth.
Buckner, R. L. (1996). Beyond HERA: Contributions of specific prefrontal brain areas to long-term memory retrieval. Psychonomic Bulletin and Review, 3, 149–158.
Carmichael, S. T., & Price, J. L. (1994). Architectonic subdivision of the orbital and medial prefrontal cortex in the macaque monkey. Journal of Comparative Neurology, 346, 366–402.
Cohen, N. J., & Squire, L. R. (1980). Preserved learning and retention of pattern-analyzing skill in amnesia: Dissociation of knowing how and knowing that. Science, 210, 207–210.
Coltheart, M. (1987). Cognitive Neuropsychology and the Study of Reading. In M. I. Posner & O. S. M. Marvin (Eds.), Attention and Performance (Vol. XI, pp. 3-37). Hillsdale, NJ: Lawrence Erlbaum.
Corkin, S. (1968). Acquisition of motor skill after bilateral medial temporal-bole excision. Neuropsychologia, 6, 255–265.
Cosmides, L., & Tooby, J. (1994). Origins of domain specificity: The evolution of functional organization. In L. S. Hirschfeld & S. A. Gelman (Eds.), Mapping the Mind (pp. 85–116). Cambridge, Eng.: Cambridge University Press.
Cummins, D. D. (1998). Social norms and other minds: The evolutionary roots of higher cognition. In D. D. Cummins & C. Allen (Eds.), The Evolution of Mind. Oxford, Eng.: Oxford University Press.
Cummins, D. D., & Allen, C. (1998). Introduction. In D. D. Cummins & C. Allen (Eds.), The Evolution of Mind (pp. 3–8). Oxford, Eng.: Oxford University Press.
Davies, P. S. (1996). Preface: Evolutionary theory in cognitive psychology. Minds and Machines, 6, 445–462.
Deacon, T. W. (1997). The Symbolic Species. New York: Norton.
Deacon, T. (1998). Language evolution and neuromechanisms. In W. Bechtel & G. Graham (Eds.), A Companion to Cognitive Science (pp. 212–225). Oxford, Eng.: Basil Blackwell.
Farah, M. (1988). Is visual imagery really visual? Overlooked evidence from neuropsychology. Psychological Review, 95, 307–317.
Feinberg, T. E., & Farah, M. J. (2000). A historical perspective on cognitive neuroscience. In M. J. Farah & T. E. Feinberg (Eds.), Patient-based Approaches to Cognitive Neuroscience (pp. 3–20). Cambridge, MA: MIT Press.
Felleman, D. J., & van Essen, D. C. (1991). Distributed hierarchical processing in the primate cerebral cortex. Cerebral Cortex, 1, 1–47.
Fodor, J. (1984). Observation reconsidered. Philosophy of Science, 51, 23–43.
Fodor, J. A. (1983). The Modularity of Mind. Cambridge, MA: MIT Press.
Gigerenzer, G. (1997). The modularity of social intelligence. In A. Whiten & R. W. Byrne (Eds.), Machiavellian Intelligence II. Extensions and Evaluation (pp. 264–288). Cambridge, Eng.: Cambridge University Press.
Goldman-Rakic, P. S. (1987). Circuitry of primate prefrontal cortex and regulation of behavior by representational memory. In J.M. Brookhart, V.B. Mountcastle, and S.R. Greiger (Eds.). Handbook of Physiology: The Nervous System (Vol. 5, pp. 373–417). Bethesda, Md: American Physiological Society.
Hinton, G. E., & Shallice, T. (1991). Lesioning a connectionist network: Investigations of acquired dyslexia. Psychological Review, 98, 74–95.
Hintzman, D. L. (1990). Human learning and memory: connections and dissociations. Annual Review of Psychology, 41, 109–139.
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.
Kosslyn, S. M. (1994). Image and Brain: The Resolution of the Imagery Debate. Cambridge, MA: MIT Press.
Marr, D. C. (1982). Vision: A Computation Investigation into the Human Representational System and Processing of Visual Information. San Francisco: Freeman.
McClelland, J. L., McNaughton, B. L., & O’Reilly, R. C. (1995). Why there are complementary learning systems in the hippocampus and neocortex: Insights from the successes and failures of connectionist models of learning and memory. Psychological Review, 102, 419–457.
Mundale, J. (1998). Brain mapping. In W. Bechtel & G. Graham (Eds.), A Companion to Cognitive Science. Oxford: Basil Blackwell.
Petersen, S. E., & Fiez, J. A. (1993). The processing of single words studied with positron emission tomography. Annual Review of Neuroscience, 16, 509–530.
Plaut, D. C. (1995). Double dissociation without modularity: Evidence from connectionist neuropsychology. Journal of Clinical and Experimental Neuropsychology, 17, 291–321.
Plaut, D. C., McClelland, J. L., Seidenberg, M. S., & Patterson, K. E. (1996). Understanding normal and impaired word reading: Computational principles in quasi-regular domains. Psychological Review, 103, 56–115.
Posner, M. I. (1978). Chronometric Explorations of Mind. Hillsdale, NJ: Lawrence Erlbaum Associates.
Roediger III, H. L., Buckner, R. L., & McDermott, K. B. (1999). Components of processing. In J. K. Foster & M. Jelicic (Eds.), Memory: Systems, Process, or Function (pp 32–65). Oxford, Eng.: Oxford University Press.
Schacter, D. L. (1987). Implicit memory: History and current status. Journal of Experimental Psychology: Learning, and Memory, 13, 501–518.
Semenza, C. (1996). Methodological issues. In J. G. Beaumont, P. M. Kenealy, & M. J. C. Rogers (Eds.), The Blackwell Dictionary of Neuropsychology. Oxford, Eng.: Basil Blackwell.
Shallice, T. (1988). From Neuropsychology to Mental Structure. New York: Cambridge University Press.
Shall ice, T. (1991). Precis of From Neuropsychology to Mental Structure. Behavioral and Brain Sciences, 14, 429–437.
Sherry, D. F., & Schacter, D. L. (1987). The evolution of multiple memory systems. Psychological Review, 94, 439–454.
Shettleworth, S. (2000). Modularity and the evolution of cognition. In C. Heyes & L. Huber (Eds.), The Evolution of Cognition (pp. 43–60). Cambridge, MA: MIT Press.
Simon, H. A. (1969). The Sciences of the Artificial. (2nd ed.). Cambridge, MA: MIT Press.
Smolensky, P. (1988). On the proper treatment of connectionism. Behavioral and Brain Science, 11, 1–74.
Teuber, H. L. (1955). Physiological psychology. Annual Review of Psychology, 9, 267–296.
Tulving, E. (1972). Episodic and semantic memory. In E. Tulving & W. Donaldson (Eds.), Organization of Memory (pp. 381–403). New York: Academic.
Tulving, E. (1984). Multiple learning and memory systems. In K. M. J. Lagerspetz & P. Niemi (Eds.), Psychology in the 1990s (pp. 163–184). North Holland: Elsevier.
Tulving, E. (1999). Study of memory: Processes and systems. In J. K. Foster & M. Jelicic (Eds.), Memory: Systems, Process, or Function (pp. 11–30). Oxford, Eng.: Oxford University Press.
Tulving, E., Heyman, C. A. G., & MacDonald, C. A. (1991). Long-lasting perceptual priming and semantic learning in amnesia. A case experiment. Journal of Experimental Psychology, 17, 595–617.
van Essen, D. C. (1997). A tension-based theory of morphogenesis and compact wiring in the central nervous system. Nature, 385, 313–318.
van Essen, D. C, Anderson, C. H. and Felleman, D. J. (1992). Information processing in the primate visual system: An integrated systems perspective. Science, 255, 419–423.
van Essen, D. C, & deYoe, E. A. (1995). Concurrent processing in the primate visual cortex. In M. Gazzaniga (Ed.), The Cognitive Neurosciences (pp. 383-440). Cambridge, MA: MIT Press.
van Essen, D. C., & Gallant, J. L. (1994). Neural mechanisms of form and motion processing in the primate visual system. Neuron, 13, 1–10.
Waskan, J., & Bechtel, W. (1997). Directions in connectionist research: Tractable computations without syntactically structured representations. Metaphilosophy, 28, 31–62.
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer Science+Business Media New York
About this chapter
Cite this chapter
Bechtel, W. (2003). Modules, Brain Parts, and Evolutionary Psychology. In: Scher, S.J., Rauscher, F. (eds) Evolutionary Psychology. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-0267-8_10
Download citation
DOI: https://doi.org/10.1007/978-1-4615-0267-8_10
Publisher Name: Springer, Boston, MA
Print ISBN: 978-1-4613-4995-2
Online ISBN: 978-1-4615-0267-8
eBook Packages: Springer Book Archive