Modular architectures and informational encapsulation: a dilemma

Abstract

Amongst philosophers and cognitive scientists, modularity remains a popular choice for an architecture of the human mind, primarily because of the supposed explanatory value of this approach. Modular architectures can vary both with respect to the strength of the notion of modularity and the scope of the modularity of mind. We propose a dilemma for these modularity approaches, no matter how they vary along these two dimensions. First, if a modular architecture commits to the informational encapsulation of modules, as it is the case for modularity theories of perception, then modules are on this account impenetrable. However, we argue that there are genuine cases of the cognitive penetrability of perception and that these cases challenge any strong, encapsulated modular architecture of perception. Second, many recent massive modularity theories weaken the strength of the notion of module, while broadening the scope of modularity. These theories do not require any robust informational encapsulation, and thus avoid the incompatibility with cognitive penetrability. However, the weakened commitment to informational encapsulation greatly weakens the explanatory force of the approach and, ultimately, is conceptually at odds with the core of modularity.

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Notes

  1. 1.

    In at least two places, Fodor himself explicitly states that “informational encapsulation is an essential property of modular systems” (Fodor 1985: 3; see also 1983: 71). Elsewhere, however, he is less clear on his commitment regarding the same claim.

  2. 2.

    So to be clear, and to foreshadow some of the discussion to come, we make no claim that perception and cognition are indistinguishable or perfectly continuous (so we do not advocate the ‘continuity thesis’ that is sometimes, perhaps wrongly, attributed to Jerome Bruner and New Look Psychology). Indeed, the very notion of cognitive penetration seems to presuppose some perception/cognition distinction, even if no one knows exactly how to mark that distinction.

  3. 3.

    It might be added here that if one makes a distinction between descriptive vision and motion-guiding vision (this is one terminological way of marking the distinction, see Matthen 2005), then these claims all concern descriptive vision. Accordingly, an effect on perceptual experience is an effect on descriptive vision which—according to a dominant theory in cognitive neuroscience—is plausibly an effect on processing in the neural pathway known as the ventral stream (see Goodale and Milner 1992, 1995).

  4. 4.

    A number of critics have questioned Pylyshyn’s conclusions in this general way (Bermudez 1999; Macpherson 2012; Moore 1999; Noë and Thompson 1999). It is also worth noting that Pylyshyn’s empirical claim can be challenged (see Boynton 2005; Kamitani and Tong 2005).

  5. 5.

    Some have argued that evidence for reentrant neural pathways is evidence for cognitive penetration (Churchland 1988). Others have argued against this line of reasoning (Fodor 1988; Gilman 1991; Raftopoulos 2001). For purposes of this discussion, we simply assume that the neurological evidence is presently insufficient to count in either direction.

  6. 6.

    For one example, see McCurdy 1956. Note also that if memory is factive as some have argued (Williamson 2001), then the memory-interpretation amounts to something like a quasi-memory interpretation.

  7. 7.

    Fodor also appeals to this general response in his debate with Paul Churchland on the theory-ladenness of perception/observation (see Fodor 1988; Churchland 1988; see also Fodor 1983). Note also that both Fodor and Pylyshyn focus on intentionally caused shifts in attention, and offer little if any discussion of sub-personal attentional mechanisms. Accordingly, the attention-shift interpretation is described here in the way that it is given by the relevant critics. It remains an open question, and one very much in need of further discussion, how evidence for non-intentional attentional effects on perception bears on questions about cognitive penetration. For some related discussion, see Connolly (forthcoming), Mole (forthcoming), Stokes (2014).

  8. 8.

    For additional discussion of these and other strategies for the cognitive impenetrability theorist, see Macpherson 2012; Stokes 2012, 2013.

  9. 9.

    Against Churchland’s appeal to subjects’ adjustment to inverting lens as evidence for diachronic cognitive penetration, Fodor appeals to an intra-perceptual interpretation (see Fodor 1988: 193). For a more recent use of this kind of interpretation, see Deroy (2013), who analyzes some of the research also discussed below.

  10. 10.

    The preferred notion of causation is of little matter so long as the internal causal dependence is maintained. For example, one could characterize the causal relation counterfactually or probabilistically. One should also note that C is a non-sufficient cause of E. There are other relevant causal factors.

  11. 11.

    In this way, CP is consistent with other recently proposed definitions of cognitive penetrability: Macpherson 2012; Siegel 2011; Wu 2013.

  12. 12.

    See Balcetis and Dunning 2006; Stokes 2012, 2013, and van Ulzen et al. 2008 for brief historical discussions of the rise and fall of the New Look movement, as well as (discussion of) new studies in the New Look spirit.

  13. 13.

    A number of theorists were critical of particular details and the broad scope of the New Look approach (Klein et al. 1951; Carter and Schooler 1949; Lysak and Gilchrist 1955). These critics challenged some of the strongest New Look claims, and by simply acquiring evidence for cases where cognition apparently fails to affect perception. But this evidence fails to undermine the more modest implication that cognition sometimes influences perception in the relevant ways. Moreover, the Bruner and Goodman 1947 results have been broadly replicated by a number of similar studies at least insofar as these studies all evidence some higher-level effect on perceptual experience. See Bruner and Postman 1948; Postman et al. 1948; Bruner et al. 1951; Dukes and Bevan 1952; Bruner and Rodrigues 1953; Bruner and Minturn 1955; Blum 1957; Holzkamp and Perlwitz 1966.

  14. 14.

    For example, each of the following studies present data that may be plausibly explained in terms of cognitive penetration: Balcetis and Dunning 2006, 2010; Payne 2001; 2005; Stefanucci and Proffitt 2008, 2009; Witt and Dorsch 2009. However, the experimental controls in these studies are such that the results could also be plausibly explained in terms of one (or more) of the mentioned alternative interpretations.

  15. 15.

    More specifically, the researchers clarify the calculation of the MCI as it is used in all three of the colour perception studies discussed here, as follows. “For the MCI the achromatic adjustments are projected on the axis of the typical adjustments that leads through the subjective grey point. The distance of this projection from the subjective grey point measures how strong the shift along this axis was. For the MCI this measure is divided by the length, i.e., the saturation, of the typical adjustment. In this way, the MCI represents the ratio of achromatic shift relative to the colourfulness of the typical colour. The sign (+/–) of the MCI reflects the direction in which the adjustment is shifted away from the subjective grey point. A positive MCI indicates an achromatic adjustment opposite to the typical adjustment. A negative MCI implies, contrary to the memory colour effect, that there is a shift of the achromatic adjustments towards the same direction as the typical adjustments. The MCI has been calculated separately for each participant using their subjective grey point” (Witzel et al 2011: 37).

  16. 16.

    This is by contrast, for example, with Fodor’s favoured explanation of the way one can shift, by attentional changes, one’s experience of the Necker cube or the duck-rabbit. See Fodor 1988: 190.

  17. 17.

    See Deroy 2013 for an analysis that partly focuses on the Olkkonen et al. 2008 study.

  18. 18.

    In their initial study to identify colour diagnosticity for artificial objects, which was performed in Germany, Witzel et al (2011) found that some stereotypically German images were highly colour diagnostic (as measured by reaction time and accuracy of typical colour identification)—for example the orange Die Maus (a German television character), the yellow German mailbox, the yellow (German-made) UHU glue tube. But some non-German objects were not sufficiently colour diagnostic (relative to German subjects)—for example, the yellow Ferrari symbol and the red Soviet flag. These researchers did not run the study using these non-colour diagnostic (relative to German subjects) objects, but presumably if they had, any memory colour effect would have been insignificant at best.

  19. 19.

    More specifically, for example, with a black-face prototype as target, subjects adjusted a white-face prototype to 4.65 levels darker (out of 256 possible greyscale levels for the computer monitor) than a white-face prototype target (where, again, both targets are of identical luminance levels).

  20. 20.

    See footnote 19 for clarification regarding the grey measures.

  21. 21.

    In fact, the researchers devise a third experiment explicitly devoted to discounting an explanation where attention is drawn to facial contours (e.g., of the stereotypical black face) in a way that explains the perceptual differences that appear in the results. They construct greyscale line drawings—with either white lines or black lines providing the facial outlines, but with no other shading of facial features—of the white and black prototypes. The results are relevantly the same and statistically significant: subjects choose darker samples for the black prototype faces and lighter samples for the white prototype faces. See Levin and Banaji 2006: 506–8.

  22. 22.

    Macpherson 2012 briefly discusses both Hansen et al 2006 and Levin and Banaji 2006. She also provides a detailed analysis of an earlier study on colour perception, Delk and Fillenbaum 1965.

  23. 23.

    Recall that because the inference method here is abductive, to “disarm” an hypothesis means, at best, to render the hypothesis highly implausible and, at least, to show that the hypothesis is less plausible than competing alternatives, all things considered.

  24. 24.

    As one anonymous reviewer notes, a number of questions about the relevant background cognitive state remain insufficiently answered in existing literature. For example, it is not made clear whether the influencing cognitive state must be an occurrent mental state. And must the effect be synchronic or may it take place diachronically? We agree that these are important questions. However, note that for our purposes, the answers don’t matter. So long as the background state is cognitive and has an effect on perceptual processing (and thereby experience), then that state can be occurrent or non-occurrent, and the effect synchronic or diachronic. In other words, if a phenomenon meets the conditions specified by CP, then such a phenomenon will count against informational encapsulation no matter the answer to these other questions.

  25. 25.

    We thank Matthew Ivanowich for pressing us to consider this reply for modularity theory.

  26. 26.

    Fodor makes similar suggestions elsewhere; see, for example, his discussion of “perceptual identifications” (1983: 68–71). And Pylyshyn (1980) makes similar commitments, claiming that the reliability of perception requires cognitive impenetrability. For further discussion of the epistemic consequences of cognitive penetrability, see Lyons 2011; Siegel 2011; 2013; Stokes 2012, 2013.

  27. 27.

    Sperber (2001) is a notable exception to the view that the plausibility of massive modularity entails giving up the encapsulation requirement.

  28. 28.

    Carruthers (2006) states that “in the weakest sense, a module can just be something like: a dissociable functional component”, and that “understood in this weak way, the thesis of massive modularity would… predict that the components should be separately modifiable” (p.2). Sternberg (2011) provides the following definition of cognitive module: “two sub-processes A and B of a complex process (mental or neural) are modules if and only if each can be changed independently of the other” (p. 159). It is worth mentioning that modules have also been minimally conceived as domain specific systems (e.g., Coltheart 1999 defines ‘module’ as “a cognitive system whose application is domain specific”, p. 118). Interestingly, however, both Sternberg and Coltheart have argued that domain specificity implies separate modifiability (Coltheart 2011, Sternberg 2011a, b).

  29. 29.

    It would not, however, be reasonable to infer from this behavioral double dissociation that the face recognition and visual object recognition systems are completely distinct (or disjoint, see Lyons 2003), since the two systems evidently share some of their subsystems (e.g., the subsystems responsible for low-level visual feature analysis).

  30. 30.

    Strictly, a cognitive system could be unencapsulated with respect to a whole range of systems and never have to compute over information made available by any of them. However, this is more of a conceptual possibility than an empirically plausible one, since it is hard to see why evolution or development would invest in building the relevant connections (so that the system can have access to whatever information these other systems make available) if these are never used.

  31. 31.

    The alleged theory of mind module is another case where unencapsulated modularity might not best explain behavioural dissociations between mind reading and other cognitive capacities. See Gerrans and Stone (2008) for a discussion of this case.

  32. 32.

    This is not to say, however, that encapsulated modularity is the only plausible explanation of a double dissociation. Even with encapsulated modularity, the functional modularity inference remains abductive (Shallice 1988, Coltheart 2001).

  33. 33.

    It does not matter here whether the systems share some parts.

References

  1. Balcetis, E., & Dunning, D. (2006). See what you want to see: motivational influences on visual perception. Journal of Personality and Social Psychology, 91(4), 612–625.

    Article  Google Scholar 

  2. Balcetis, E., & Dunning, D. (2010). Wishful seeing: desired objects are seen as closer. Psychological Science, 21, 147–152.

    Article  Google Scholar 

  3. Barrett, H. C., & Kurzban, R. (2006). Modularity in cognition: framing the debate. Psychological Review, 113(3), 628–647.

    Article  Google Scholar 

  4. Bergeron, V. (2007). Anatomical and functional modularity in cognitive science: shifting the focus. Philosophical Psychology, 20, 175–195.

    Article  Google Scholar 

  5. Bergeron, V. (2015). Functional independence and cognitive architecture. The British Journal for the Philosophy of Science. doi:10.1093/bjps/axv005.

  6. Bermudez, J. (1999). Cognitive impenetrability, phenomenology, and nonconceptual content. Behavioural and Brain Sciences, 22(3), 367–368.

    Article  Google Scholar 

  7. Blum, A. (1957). The value factor in children’s size perception. Child Development, 28, 14–18.

    Google Scholar 

  8. Boynton, G. M. (2005). Imagining orientation selectivity: decoding conscious perception in V1. Nature Neuroscience, 8, 541–542.

    Article  Google Scholar 

  9. Bruner, J.S. (1957). On perceptual readiness. Psychological Review, 64(2), 123–52.

  10. Bruner, J. S., & Goodman, C. C. (1947). Value and need as organizing factors in perception. Journal of Abnormal and Social Psychology, 42, 33–44.

    Article  Google Scholar 

  11. Bruner, J. S., & Minturn, A. L. (1955). Perceptual identification and perceptual organization. Journal of General Psychology, 21–28.

  12. Bruner, J. S., & Postman, L. (1948). Symbolic value as an organizing factor in perception. Journal of Social Psychology, 27, 203–208.

    Article  Google Scholar 

  13. Bruner, J. S., & Rodrigues, J. S. (1953). Some determinants of apparent size. Journal of Abnormal and Social Psychology, 48, 17–24.

    Article  Google Scholar 

  14. Bruner, J. S., Postman, L., & Rodrigues, J. (1951). Expectation and the perception of color. American Journal of Psychology, 64, 216–227.

  15. Carruthers, P. (2006). The architecture of the mind. Oxford: Oxford University Press.

    Book  Google Scholar 

  16. Carter, L. F., & Schooler, K. (1949). Value need and other factors in perception. Psychological Review, 56, 200–207.

    Article  Google Scholar 

  17. Churchland, P. M. (1988). Perceptual plasticity and theoretical neutrality: a reply to Jerry Fodor. Philosophy of Science, 55, 167–187.

    Article  Google Scholar 

  18. Coltheart, M. (1999). Modularity and cognition. Trends in Cognitive Science, 3, 115–120.

    Article  Google Scholar 

  19. Coltheart, M. (2001). Assumptions and methods in cognitive neuropsychology, In B. Rapp (ed.) The handbook of cognitive neuropsychology, pp. 3-21, Psychology Press.

  20. Coltheart, M. (2011). Methods for modular modelling: additive factors and cognitive neuropsychology. Cognitive Neuropsychology, 28, 224–240.

    Article  Google Scholar 

  21. Connolly, K. (forthcoming). Perceptual learning and the contents of perception. Erkenntnis.

  22. Cowie, F. (2008). Us, them and it: modules, genes, environments and evolution. Mind & Language, 23, 284–292.

    Article  Google Scholar 

  23. Davies, M. (2010). Double dissociation: understanding its role in cognitive neuropsychology. Mind & Language, 25, 500–540.

    Article  Google Scholar 

  24. De Renzi, E., & Di Pellegrino, G. (1998). Prosopagnosia and alexia without object agnosia. Cortex, 34, 403–415.

    Article  Google Scholar 

  25. Delk, J. L., & Fillenbaum, S. (1965). Differences in perceived color as a function of characteristic color. The American Journal of Psychology, 78, 290–293.

    Article  Google Scholar 

  26. Deroy, O. (2013). Object-sensitivity versus cognitive penetrability of perception. Philosophical Studies, 162(1), 87–107.

  27. Dukes, W. F., & Bevan, W. (1952). Size estimation and monetary value: a correlation. Journal of Psychology, 34, 43–53.

    Article  Google Scholar 

  28. Dunn, J. C., & Kirsner, K. (2003). What can we infer from double dissociations? Cortex, 39(1), 1–7.

    Article  Google Scholar 

  29. Farah, M. (1994). Neuropsychological inference with an interactive brain: a critique of the locality assumption. Behavioral and Brain Sciences, 17, 43–104.

    Article  Google Scholar 

  30. Fodor, J. (1983). The modularity of mind. Cambridge: MIT Press.

    Google Scholar 

  31. Fodor, J. (1985). Précis of The modularity of mind. The Behavioral and Brain Sciences, 8, 1–5.

  32. Fodor, J. (1988). A reply to Churchland’s “Perceptual plasticity and theoretical neutrality,”. Philosophy of Science, 55, 188–198.

    Article  Google Scholar 

  33. Gerrans, P., & Stone, V. E. (2008). Generous or parsimonious cognitive architecture? Cognitive neuroscience and theory of mind. British Journal for the Philosophy of Science, 59, 121–141.

  34. Gilman, D. J. (1991). The neurobiology of observation. Philosophy of Science, 58(3), 496–502.

  35. Goodale, M. A., & Milner, D. (1992). Separate visual pathways for perception and action. Trends in Neurosciences, 15(1), 20–25.

    Article  Google Scholar 

  36. Hagen, E. H. (2005). Controversial issues in evolutionary psychology. In D. M. Buss (Ed.), The handbook of evolutionary psychology (pp. 5–67). Hoboken: Wiley.

    Google Scholar 

  37. Hansen, T., Olkkonen, M., Walter, S., & Gegenfurtner, K. R. (2006). Memory modulates color appearance. Nature Neuroscience, 9, 1367–1368.

    Article  Google Scholar 

  38. Holzkamp, K., & Perlwitz, E. (1966). Absolute oder relative Größenakzentuierung? Eine experimentelle Studie zur sozialen Wahrnehmung. Zeitschrift für Experimentelle und Angewandte Psychologie, 13, 390–405.

    Google Scholar 

  39. Juola, P. & Plunkett, K. (2000). Why double dissociations don’t mean much. In G. Cohen, R. A. Johnston, & K. Plunkett (Eds.), Exploring cognition: damaged brains and neural networks. (pp. 319–327). Psychology Press.

  40. Kamitani, Y., & Tong, F. (2005). Decoding the visual and subjective contents of the human brain. Nature Neuroscience, 8, 679–685.

    Article  Google Scholar 

  41. Klein, G. S., Schlesinger, H. J., & Meister, D. E. (1951). The effect of personal values on perception—an experimental critique. Psychological Review, 58, 96–112.

    Article  Google Scholar 

  42. Levin, D., & Banaji, M. (2006). Distortions in the perceived lightness of faces: the role of race categories. Journal of Experimental Psychology: General, 135, 501–512.

  43. Lyons, J. C. (2003). Lesion studies, spared performances, and cognitive systems. Cortex, 39, 145–147.

    Article  Google Scholar 

  44. Lyons, J. C. (2011). Circularity, reliability, and cognitive penetrability of perception. Philosophical Issues, 21(1), 289–311.

    Article  Google Scholar 

  45. Lysak, W., & Gilchrist, J. C. (1955). Value, equivocality, and goal availability as determinants of size judgments. Journal of Personality, 23, 500–501.

    Google Scholar 

  46. Machery, E. (2012). Dissociations in neuropsychology and cognitive neuroscience. Philosophy of Science, 79, 490–518.

    Article  Google Scholar 

  47. Macpherson, F. (2012). Cognitive penetration of colour experience: rethinking the issue in light of an indirect mechanism. Philosophy and Phenomenological Research, 84(1), 24–62.

    Article  Google Scholar 

  48. Marr, D. (1976). Early processing of visual information. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences, 275(942), 483–519.

    Article  Google Scholar 

  49. Matthen, M. (2005). Seeing, doing, and knowing: a philosophical theory of sense perception. Oxford University Press.

  50. McCurdy, H. G. (1956). Coin perception studies and the concept of schemata. Psychological Review, 63, 160–168.

    Article  Google Scholar 

  51. Milner, D. and Goodale, M. (1995). The visual brain in action. Oxford: Oxford University Press.

  52. Mole, C. (forthcoming) Attention-mediated cognitive penetration. in A. Raftopoulos and J. Zeimbekis (Eds) Cognitive Penetrability, Oxford: Oxford University Press

  53. Moore, C. (1999). Cognitive impenetrability of early vision does not imply cognitive impenetrability of perception. Behavioral and Brain Sciences, 22(3), 385–386.

    Article  Google Scholar 

  54. Noë, A., & Thompson, E. (1999). Seeing beyond the modules toward the subject of perception. Behavioral and Brain Sciences, 22(3), 386–387.

    Article  Google Scholar 

  55. Olkkonen, M., Hansen, T., & Gegenfurtner, K. R. (2008). Color appearance of familiar objects : effects of object shape, texture and illumination changes. Journal of Vision, 8, 1–16.

    Article  Google Scholar 

  56. Payne, K. (2001). Prejudice and perception: the role of automatic and controlled processes in misperceiving a weapon. Journal of Personality and Social Psychology, 8, 181–192.

    Article  Google Scholar 

  57. Payne, K., Shimizu, Y., & Jacoby, L. (2005). Mental control and visual illusions: toward explaining race-biased weapon misidentifications. Journal of Experimental Social Psychology, 41, 36–47.

    Article  Google Scholar 

  58. Plaut, D. C. (1995). Double dissociation without modularity: evidence from connectionist neuropsychology. Journal of Clinical and Experimental Neuropsychology, 17(2), 291–321.

    Article  Google Scholar 

  59. Postman, L., Bruner, J. S., & McGinnies, E. (1948). Personal values as selective factors in perception. Journal of Abnormal and Social Psychology, 43, 142–154.

    Article  Google Scholar 

  60. Pylyshyn, Z. (1980). Computation and cognition: issues in the foundations of cognitive science. Behavioral and Brain Sciences, 3, 111–132.

    Article  Google Scholar 

  61. Pylyshyn, Z. (1999). Is vision continuous with cognition? The case for cognitive impenetrability of visual perception. Behavioral and Brain Sciences, 22(3), 341–365.

    Google Scholar 

  62. Raftopoulos, A. (2001). Reentrant neural pathways and the theory-ladenness of perception. Philosophy of Science, 68(3), S187–S199.

  63. Robbins, P. (2013). Modularity and mental architecture. Wiley Interdisciplinary Reviews: Cognitive Science, 4(6), 641–649.

    Google Scholar 

  64. Rumiati, R. I., & Humphreys, G. W. (1997). Visual object agnosia without alexia or prosopagnosia. Visual Cognition, 4, 207–217.

    Article  Google Scholar 

  65. Shallice, T. (1988). From neuropsychology to mental structure. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  66. Shallice, T. & Cooper, R. P. (2011) The organisation of mind. Oxford University Press.

  67. Siegel, S. (2007). How Can We Discover the Contents of Experience? Southern Journal of Philosophy, 45 (S1),127-42.

  68. Siegel, S. (2011) Cognitive penetrability and perceptual justification. Noûs, 46(2).

  69. Siegel, S. (2013). The epistemic impact of the etiology of experience. Philosophical Studies, 162(3), 697–722.

  70. Simon, H. A. (1969). The sciences of the artificial. M.I.T. Press.

  71. Sperber, D. (1994). The modularity of thought and the epidemiology of representations. In L. A. Hirschfeld & S. A. Gelman (Eds.), Mapping the mind: domain specificity in cognition and culture. New York: Cambridge University Press.

    Google Scholar 

  72. Sperber, D. (2001). Defending massive modularity. In E. Dupoux (Ed.), Language, brain and cognitive development: essays in honor of Jacques Mehler. Cambridge: MIT Press.

    Google Scholar 

  73. Stefanucci,  J. K., & Proffitt, D. R. (2008). Skating down a steeper slope: fear influences the perception of geographical slant. Perception, 37, 321–323.

  74. Stefanucci, J. K., & Proffitt, D. R. (2009). The roles of altitude and fear in the perception of height. Journal of Experimental Psychology, 35, 424–438.

  75. Sternberg, S. (2001). Separate modifiability, mental modules, and the use of pure and composite measures to reveal them. Acta Psychologica106(1), 147-246.

  76. Sternberg, S. (2011). Modular processes in mind and brain. Cognitive Neuropsychology, 28(3 & 4), 156–208.

    Article  Google Scholar 

  77. Stokes, D. (2012). Perceiving and desiring: a new look at the cognitive penetrability of experience. Philosophical Studies, 158, 479–492.

    Article  Google Scholar 

  78. Stokes, D. (2013). The cognitive penetrability of perception’. Philosophy Compass, 8, 646–663.

    Article  Google Scholar 

  79. Stokes, D. (2014). Cognitive penetration and the perception of art. Dialectica, 68, 1–34.

    Article  Google Scholar 

  80. Vallar, G. (2000) The methodological foundations of human neuropsychology: studies in brain-damaged patients. In F. Boller and J. Grafman (Eds.) Handbook of Neuropsychology, pp. 305–344, Elsevier.

  81. Van Orden, G. C., Pennington, B. F., & Stone, G. O. (2001). What do double dissociation prove? Cognitive Science, 25, 111–172.

    Article  Google Scholar 

  82. Van Ulzen, N. R., Semin, G. R., Oudejans, R., & Beek, P. (2008). ‘Affective stimulus properties influence size perception and the Ebbinghaus illusion’. Psychological Research, 72, 304–310.

  83. Williamson, T. (2001) Knowledge and its limits. Oxford: Oxford University Press.

  84. Wilson, R. (2008). The drink you have when you’re not having a drink. Mind & Language, 23, 273–283.

    Article  Google Scholar 

  85. Witt, J. K., & Dorsch, T. E. (2009). Kicking to bigger uprights: field goal kicking performance influences perceived size. Perception, 38, 1328–1340.

    Article  Google Scholar 

  86. Witzel, C., Valkova, H., Hansen, T., & Gegenfurtner, K. (2011). Object knowledge modulates colour appearance. i-Perception, 2, 13–49.

    Article  Google Scholar 

  87. Wu, W. (2013). Visual spatial constancy and modularity: does intention penetrate vision? Philosophical Studies, 165(2), 647–669.

    Article  Google Scholar 

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Acknowledgments

The authors gratefully acknowledge helpful comments and criticism from members of audiences at Carleton University and the Canadian Philosophical Association and in particular from Steve Downes, Matt Haber, Matthew Ivanowich, Susanna Siegel, Wayne Wu, and two anonymous referees.

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Correspondence to Vincent Bergeron.

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This work was thoroughly collaborative and the paper thoroughly co-authored—the order of authors was chosen randomly.

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Stokes, D., Bergeron, V. Modular architectures and informational encapsulation: a dilemma. Euro Jnl Phil Sci 5, 315–338 (2015). https://doi.org/10.1007/s13194-015-0107-z

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Keywords

  • Cognitive architecture
  • Modularity
  • Informational encapsulation
  • Cognitive penetrability
  • Dissociation