Carruthers (Reference Carruthers2006) characterizes the mind as composed out of the interactions of a large set of mental modules, utilizing the “global workspace” provided by perception and working memory to recruit the resources of multiple specialized systems in the service of cognition and behavior. The sense of “module” in question is quite weak, however. Modules are functionally dissociable, intentionally characterized processing systems, each with its own neural realization. Modules need not be encapsulated, domain-specific, or innate (although many probably are). And the neural systems that realize them certainly need not be anatomically localized. On the contrary, modules can be realized in spatially distributed interconnected networks of brain regions. Moreover, many modules are constructed out of, and share parts with, other modules. Hence, the distinctness of different modules and their neural realizers will only be partial.
Anderson claims that the thesis that modules can share parts is inconsistent with the idea that modules are functionally dissociable and separately modifiable, committing Carruthers to a strong version of anatomical modularity. But this is a mistake. Provided that two modules sharing a part differ from one another in other respects, it will be possible to disrupt the operations of one without having any impact on the other (by disrupting only the parts of the former that are not shared), and it will be possible for natural selection to make modifications in the one without changing the other (again, by making improvements in the parts that are not shared). Indeed, at the limit, two modules could share all of their processing parts while still remaining dissociable and separately modifiable. For the differences might lie entirely in the patterns of connectivity among the parts, in such a way that those connections could be separately disrupted or improved. In short, the functional dissociation and separate modifiability of modules do not preclude the possibility of neural reuse.
The shared-parts doctrine provides a clear sense of neural reuse that is consistent with massive modularity. Moreover, each shared part can be given a dual functional characterization. Its function can either be described in univocal local semantic terms, or it can be said to be multi-functional, characterized in terms of the different longer-range uses for which its outputs are employed. (This seems to correspond to one way of understanding Anderson's distinction between “workings” and “functions,” respectively, although he himself characterizes the former in “low-level computational” rather than intentional terms [sect. 1.1, para. 5].) Consider, for example, the region of fusiform gyrus that is often characterized as a face-recognition area (Coltheart Reference Coltheart1999; Kanwisher et al. Reference Kanwisher, McDermott and Chun1997). At one level of description, this is a module that recognizes faces. But it will contribute to, and be a part of, a number of larger systems. One is a person-file system, which uses face-recognition to help collect and store information about the individuals in one's community (especially their personality traits and mental states). Another is an affiliative, social-bond-building, module which uses face-recognition as part of the process of creating and activating positive affective reactions to specific others. And a third is a Westermarck-style incest avoidance module (Fessler & Navarrete Reference Fessler and Navarrete2004), which uses the face-recognition module during childhood to track the extent to which other children are co-present in the home, and then above a certain threshold of cohabitation produces sexual disgust at the prospect of intercourse with those individuals post-adolescence. We can then say that the fusiform gyrus is a module with one local function (face-recognition) which is part of at least three other larger-scale modules (and hence is at the same time multi-functional).
Notice that nothing much needs to change in this account if one thinks that the fusiform gyrus isn't a face area, but is rather a holistic shape-processing area, which can be used for recognizing any type of object that requires a combination of local detail and overall form (Gauthier et al. Reference Gauthier, Skudlarski, Gore and Anderson2000; Reference Gauthier, Curran, Curby and Collins2003). For we can now characterize its local function in just such semantic terms; and yet on this account, there will be an even larger set of systems of which it constitutes a modular part.
However, the massive modularity hypothesis is inconsistent with a distinct, stronger, doctrine of neural reuse. This would claim that a neural region can be implicated in multiple long-range functions without there being a single semantic characterization of its local function. Perhaps Anderson endorses this stronger view. He emphasizes, for example, how the same brain regions can be involved in very different tasks like reading comprehension and manual object-manipulation (sect. 3.1, para. 5). And he thinks that local functions (or “workings”) are “low-level” and computational rather than intentional. But nothing in the evidence that Anderson presents actually supports such a view over the weaker account sketched above. Moreover, it strikes us as quite implausible. It is hard to see how the same set of computations could realize distinct representational properties on different occasions of use. For the consumer, systems for those computations would have no way of knowing which representational properties are involved on a given occasion, and hence no way of determining how the outputs should be used.
Anderson might accept a more modest position with which the data are equally consistent: Under such a view, the neural region of interest subdivides into a number of more fine-grained areas (too fine-grained to show up in fMRI data, for example), each of which has a specialized semantically characterizable function. Furthermore, for all that the data show, distinct local modules might spatially interpenetrate one another, with the neurons involved in one being interspersed among neurons involved in the other, in something like the way that mirror neurons are interspersed among purely motor-related neurons in premotor regions of macaque cortex (Rizzolatti & Craighero Reference Rizzolatti and Craighero2004). However, such a position would also be consistent with the thesis of massive modularity.
We conclude that to the extent that the data reviewed by Anderson support a thesis of massive neural reuse, the resulting thesis is fully consistent with the hypothesis of massive mental modularity, as characterized by Carruthers (Reference Carruthers2006).
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Carruthers (Reference Carruthers2006) characterizes the mind as composed out of the interactions of a large set of mental modules, utilizing the “global workspace” provided by perception and working memory to recruit the resources of multiple specialized systems in the service of cognition and behavior. The sense of “module” in question is quite weak, however. Modules are functionally dissociable, intentionally characterized processing systems, each with its own neural realization. Modules need not be encapsulated, domain-specific, or innate (although many probably are). And the neural systems that realize them certainly need not be anatomically localized. On the contrary, modules can be realized in spatially distributed interconnected networks of brain regions. Moreover, many modules are constructed out of, and share parts with, other modules. Hence, the distinctness of different modules and their neural realizers will only be partial.
Anderson claims that the thesis that modules can share parts is inconsistent with the idea that modules are functionally dissociable and separately modifiable, committing Carruthers to a strong version of anatomical modularity. But this is a mistake. Provided that two modules sharing a part differ from one another in other respects, it will be possible to disrupt the operations of one without having any impact on the other (by disrupting only the parts of the former that are not shared), and it will be possible for natural selection to make modifications in the one without changing the other (again, by making improvements in the parts that are not shared). Indeed, at the limit, two modules could share all of their processing parts while still remaining dissociable and separately modifiable. For the differences might lie entirely in the patterns of connectivity among the parts, in such a way that those connections could be separately disrupted or improved. In short, the functional dissociation and separate modifiability of modules do not preclude the possibility of neural reuse.
The shared-parts doctrine provides a clear sense of neural reuse that is consistent with massive modularity. Moreover, each shared part can be given a dual functional characterization. Its function can either be described in univocal local semantic terms, or it can be said to be multi-functional, characterized in terms of the different longer-range uses for which its outputs are employed. (This seems to correspond to one way of understanding Anderson's distinction between “workings” and “functions,” respectively, although he himself characterizes the former in “low-level computational” rather than intentional terms [sect. 1.1, para. 5].) Consider, for example, the region of fusiform gyrus that is often characterized as a face-recognition area (Coltheart Reference Coltheart1999; Kanwisher et al. Reference Kanwisher, McDermott and Chun1997). At one level of description, this is a module that recognizes faces. But it will contribute to, and be a part of, a number of larger systems. One is a person-file system, which uses face-recognition to help collect and store information about the individuals in one's community (especially their personality traits and mental states). Another is an affiliative, social-bond-building, module which uses face-recognition as part of the process of creating and activating positive affective reactions to specific others. And a third is a Westermarck-style incest avoidance module (Fessler & Navarrete Reference Fessler and Navarrete2004), which uses the face-recognition module during childhood to track the extent to which other children are co-present in the home, and then above a certain threshold of cohabitation produces sexual disgust at the prospect of intercourse with those individuals post-adolescence. We can then say that the fusiform gyrus is a module with one local function (face-recognition) which is part of at least three other larger-scale modules (and hence is at the same time multi-functional).
Notice that nothing much needs to change in this account if one thinks that the fusiform gyrus isn't a face area, but is rather a holistic shape-processing area, which can be used for recognizing any type of object that requires a combination of local detail and overall form (Gauthier et al. Reference Gauthier, Skudlarski, Gore and Anderson2000; Reference Gauthier, Curran, Curby and Collins2003). For we can now characterize its local function in just such semantic terms; and yet on this account, there will be an even larger set of systems of which it constitutes a modular part.
However, the massive modularity hypothesis is inconsistent with a distinct, stronger, doctrine of neural reuse. This would claim that a neural region can be implicated in multiple long-range functions without there being a single semantic characterization of its local function. Perhaps Anderson endorses this stronger view. He emphasizes, for example, how the same brain regions can be involved in very different tasks like reading comprehension and manual object-manipulation (sect. 3.1, para. 5). And he thinks that local functions (or “workings”) are “low-level” and computational rather than intentional. But nothing in the evidence that Anderson presents actually supports such a view over the weaker account sketched above. Moreover, it strikes us as quite implausible. It is hard to see how the same set of computations could realize distinct representational properties on different occasions of use. For the consumer, systems for those computations would have no way of knowing which representational properties are involved on a given occasion, and hence no way of determining how the outputs should be used.
Anderson might accept a more modest position with which the data are equally consistent: Under such a view, the neural region of interest subdivides into a number of more fine-grained areas (too fine-grained to show up in fMRI data, for example), each of which has a specialized semantically characterizable function. Furthermore, for all that the data show, distinct local modules might spatially interpenetrate one another, with the neurons involved in one being interspersed among neurons involved in the other, in something like the way that mirror neurons are interspersed among purely motor-related neurons in premotor regions of macaque cortex (Rizzolatti & Craighero Reference Rizzolatti and Craighero2004). However, such a position would also be consistent with the thesis of massive modularity.
We conclude that to the extent that the data reviewed by Anderson support a thesis of massive neural reuse, the resulting thesis is fully consistent with the hypothesis of massive mental modularity, as characterized by Carruthers (Reference Carruthers2006).