The study of human cognition is, in many ways, linked to the study of animal cognition. This is perhaps most apparent if one considers the large number of animal models of human cognitive functions developed in the past few decades. In memory research, for example, various forms of memory or memory systems have been modeled extensively in other species – for example, long-term memory in rats, working memory in nonhuman primates. Vision research provides another good example, where a great deal of our current knowledge of the human visual system comes from an extensive mapping of the macaque monkey's visual system. A less obvious candidate is the study of language. Despite it being a uniquely human cognitive capacity, there is mounting evidence that experimental work in nonhuman primates may illuminate various aspects of language processing (Petrides et al. Reference Petrides, Cadoret and Mackey2005; Rauschecker & Scott Reference Rauschecker and Scott2009; Schubotz & Fiebach Reference Schubotz and Fiebach2006).
In using animal data to explain human cognitive functions, one must assume that there is sufficient evolutionary continuity between the human brain and that of other species. Not all animal data are equally relevant, of course, and whether a piece of data in a given species appears to be relevant to human studies depends on the interplay between several different factors, such as the kind of cognitive systems involved, the evolutionary distance between the two species, and the particular experimental methods used. For example, basic neurobiological mechanisms like long-term potentiation can be studied in evolutionarily distant animals such as Aplysia and rats, whereas higher cognitive functions like executive functions are best studied in evolutionarily closer species such as nonhuman primates.
In its simplest form, this evolutionary continuity assumption is uncontroversial. The human brain shares many of its principles and functions with that of other species; and for any human cognitive function, we can expect that (at least) some component(s) of it could be found in the cognitive repertoire of another species. What is less clear, however, is how best to exploit this evolutionary continuity in building models of human cognition. This is the challenge of finding precisely which components of human cognitive functions can be successfully studied in other species. Anderson's target article, and neural reuse theories in general, provide a unique perspective on how to accomplish this task.
Central to the concept of neural reuse is a distinction between two concepts of function, namely, “working” and “use.” The cognitive workings of a brain structure (e.g., Broca's area) are the low-level operations that it performs, whereas the cognitive uses of that structure are the higher-level operations (or capacities) to which it contributes. What neural reuse theories suggest is that, in the course of evolution, a brain structure may acquire or lose a number of cognitive uses while maintaining its cognitive workings fixed. This, in turn, suggests that homologous structures may contribute to very different cognitive capacities, and thus have very different cognitive uses, while sharing essentially the same low-level internal operations or workings. And this, one might think, is homology thinking applied to brain function.
The idea of functional homology may seem confused at first (Love Reference Love2007). After all, the concept of homology was originally defined as “the same organ in different animals under every variety of form and function” (Owen Reference Owen1843, p. 379), where sameness is defined by common phylogenetic origin. And in fact, homologous brain structures will often have very different functions. For example, Broca's area, unlike its homologue in the macaque monkey (Petrides et al. Reference Petrides, Cadoret and Mackey2005), is heavily involved in language and music processing (Patel Reference Patel2003). However, as we have just seen, the fact that these two structures appear functionally dissimilar based on a comparison of their cognitive uses obscures the fact that they may share the same workings. By specifying the workings of the two structures independently of their specific uses, as neural reuse theories suggest we do, one could test whether this is in fact the case. Recent models of Broca's area's workings (Schubotz & Fiebach Reference Schubotz and Fiebach2006) provide a first step. For example, Fiebach and Schubotz (Reference Fiebach and Schubotz2006) propose that Broca's area may function as a hypersequential processor that performs the “detection, extraction, and/or representation of regular, rule-based patterns in temporally extended events” (p. 501). As the model attempts to explain Broca's area's contribution to complex, behaviorally relevant sequences that are also present in nonhuman primates (e.g., action sequencing and the manipulation of objects), and because there is a homologue of the area in the macaque monkey, Fiebach and Schubotz's account of Broca's area's workings appears be a good candidate for a cognitive homology – that is, the same workings in different animals regardless of cognitive use, where sameness is defined by the common phylogenetic origin of the associated structures (see also Love Reference Love2007 for a similar proposal regarding “homology of function”).
Anderson's discussion of the spatial-numerical association of response codes (SNARC) effect (Dehaene et al. Reference Dehaene, Bossini and Giraux1993) provides another illustration of how homology thinking might apply to cognitive function. When subjects are asked to classify numbers as even or odd by making their responses on either the right or the left side of space, their responses to larger numbers are faster when made on the right side of space, whereas responses to smaller numbers are faster when made on the left side of space. Hubbard et al. (Reference Hubbard, Piazza, Pinel and Dehaene2005) review several lines of evidence in monkeys and humans that point to a region in the intraparietal sulcus as the site of this interaction between numerical and spatial cognition. They hypothesize that the interaction arises because of the common involvement, in both attention to external space and internal representations of numbers, of a particular circuit in this region. Here again, we can think of their account of the workings of this brain structure in both monkeys and humans as a cognitive homology.
Homology thinking applied to brain structures is already an integral part of cognitive neuroscience. The perspective offered by neural reuse theories allows us to extend homology thinking to brain function.
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The study of human cognition is, in many ways, linked to the study of animal cognition. This is perhaps most apparent if one considers the large number of animal models of human cognitive functions developed in the past few decades. In memory research, for example, various forms of memory or memory systems have been modeled extensively in other species – for example, long-term memory in rats, working memory in nonhuman primates. Vision research provides another good example, where a great deal of our current knowledge of the human visual system comes from an extensive mapping of the macaque monkey's visual system. A less obvious candidate is the study of language. Despite it being a uniquely human cognitive capacity, there is mounting evidence that experimental work in nonhuman primates may illuminate various aspects of language processing (Petrides et al. Reference Petrides, Cadoret and Mackey2005; Rauschecker & Scott Reference Rauschecker and Scott2009; Schubotz & Fiebach Reference Schubotz and Fiebach2006).
In using animal data to explain human cognitive functions, one must assume that there is sufficient evolutionary continuity between the human brain and that of other species. Not all animal data are equally relevant, of course, and whether a piece of data in a given species appears to be relevant to human studies depends on the interplay between several different factors, such as the kind of cognitive systems involved, the evolutionary distance between the two species, and the particular experimental methods used. For example, basic neurobiological mechanisms like long-term potentiation can be studied in evolutionarily distant animals such as Aplysia and rats, whereas higher cognitive functions like executive functions are best studied in evolutionarily closer species such as nonhuman primates.
In its simplest form, this evolutionary continuity assumption is uncontroversial. The human brain shares many of its principles and functions with that of other species; and for any human cognitive function, we can expect that (at least) some component(s) of it could be found in the cognitive repertoire of another species. What is less clear, however, is how best to exploit this evolutionary continuity in building models of human cognition. This is the challenge of finding precisely which components of human cognitive functions can be successfully studied in other species. Anderson's target article, and neural reuse theories in general, provide a unique perspective on how to accomplish this task.
Central to the concept of neural reuse is a distinction between two concepts of function, namely, “working” and “use.” The cognitive workings of a brain structure (e.g., Broca's area) are the low-level operations that it performs, whereas the cognitive uses of that structure are the higher-level operations (or capacities) to which it contributes. What neural reuse theories suggest is that, in the course of evolution, a brain structure may acquire or lose a number of cognitive uses while maintaining its cognitive workings fixed. This, in turn, suggests that homologous structures may contribute to very different cognitive capacities, and thus have very different cognitive uses, while sharing essentially the same low-level internal operations or workings. And this, one might think, is homology thinking applied to brain function.
The idea of functional homology may seem confused at first (Love Reference Love2007). After all, the concept of homology was originally defined as “the same organ in different animals under every variety of form and function” (Owen Reference Owen1843, p. 379), where sameness is defined by common phylogenetic origin. And in fact, homologous brain structures will often have very different functions. For example, Broca's area, unlike its homologue in the macaque monkey (Petrides et al. Reference Petrides, Cadoret and Mackey2005), is heavily involved in language and music processing (Patel Reference Patel2003). However, as we have just seen, the fact that these two structures appear functionally dissimilar based on a comparison of their cognitive uses obscures the fact that they may share the same workings. By specifying the workings of the two structures independently of their specific uses, as neural reuse theories suggest we do, one could test whether this is in fact the case. Recent models of Broca's area's workings (Schubotz & Fiebach Reference Schubotz and Fiebach2006) provide a first step. For example, Fiebach and Schubotz (Reference Fiebach and Schubotz2006) propose that Broca's area may function as a hypersequential processor that performs the “detection, extraction, and/or representation of regular, rule-based patterns in temporally extended events” (p. 501). As the model attempts to explain Broca's area's contribution to complex, behaviorally relevant sequences that are also present in nonhuman primates (e.g., action sequencing and the manipulation of objects), and because there is a homologue of the area in the macaque monkey, Fiebach and Schubotz's account of Broca's area's workings appears be a good candidate for a cognitive homology – that is, the same workings in different animals regardless of cognitive use, where sameness is defined by the common phylogenetic origin of the associated structures (see also Love Reference Love2007 for a similar proposal regarding “homology of function”).
Anderson's discussion of the spatial-numerical association of response codes (SNARC) effect (Dehaene et al. Reference Dehaene, Bossini and Giraux1993) provides another illustration of how homology thinking might apply to cognitive function. When subjects are asked to classify numbers as even or odd by making their responses on either the right or the left side of space, their responses to larger numbers are faster when made on the right side of space, whereas responses to smaller numbers are faster when made on the left side of space. Hubbard et al. (Reference Hubbard, Piazza, Pinel and Dehaene2005) review several lines of evidence in monkeys and humans that point to a region in the intraparietal sulcus as the site of this interaction between numerical and spatial cognition. They hypothesize that the interaction arises because of the common involvement, in both attention to external space and internal representations of numbers, of a particular circuit in this region. Here again, we can think of their account of the workings of this brain structure in both monkeys and humans as a cognitive homology.
Homology thinking applied to brain structures is already an integral part of cognitive neuroscience. The perspective offered by neural reuse theories allows us to extend homology thinking to brain function.