Cognition 110 (2009) 412–431
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Cognition journal homepage: www.elsevier.com/locate/COGNIT
Beyond perceptual symbols: A call for representational pluralism Guy Dove * Department of Philosophy and Department of Psychological and Brain Sciences, 313B Humanities Building, University of Louisville, College of Arts and Sciences, Louisville, KY 40292, United States
a r t i c l e
i n f o
Article history: Received 14 August 2007 Revised 12 November 2008 Accepted 17 November 2008
Keywords: Concepts Representation Perceptual symbol systems Imagery Empiricism
a b s t r a c t Recent evidence from cognitive neuroscience suggests that certain cognitive processes employ perceptual representations. Inspired by this evidence, a few researchers have proposed that cognition is inherently perceptual. They have developed an innovative theoretical approach that rests on the notion of perceptual simulation and marshaled several general arguments supporting the centrality of perceptual representations to concepts. In this article, I identify a number of weaknesses in these arguments and defend a multiple semantic code approach that posits both perceptual and non-perceptual representations. Ó 2008 Elsevier B.V. All rights reserved.
1. Introduction Cognitive scientists have traditionally assumed that our concepts are couched in amodal (i.e. non-perceptual) representations. On the standard view, perception and cognition are distinct mental activities that are served by different representational systems. This orthodoxy has been challenged by an ever increasing body of research that implicates the use of perceptual representations in cognitive tasks (Barsalou, 1999; Kosslyn, 1994). There have been three major types of response to this evidence: one that generalizes from this evidence and proposes that concepts are generally couched in perceptual or motor representations (Barsalou, 1999; Damasio, 1989; Glenberg,
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1997; Prinz, 2002),1 a second that explains away this evidence and reaffirms the orthodox view that concepts are couched solely in amodal representations (Caramazza, Hillis, Rapp, & Romani, 1990; Pylyshyn, 1973; Pylyshyn, 1981), and a third that interprets this evidence cautiously and posits both amodal and modal conceptual representations (Goldstone & Barsalou, 1998).2 1 This characterization of perceptually based approaches is qualified because there seems to be some variability in the degree to which proponents of perceptual symbols are committed to their universality. Prinz (2002) explicitly holds that all conceptual representations are perceptual or motor representations. Damasio (1989) does not offer a complete theory of conception so it is difficult to judge where he stands on this issue. Glenberg (1997) speaks of concepts as being embodied and grounded in perception and action, but it is not absolutely clear that this excludes the possibility of amodal symbols. Although Barsalou (1999) proposes that cognition is ‘‘inherently perceptual,” he explicitly acknowledges the possibility that some conceptual representations are amodal (Barsalou, Simmons, Barbey, & Wilson, 2003; Goldstone & Barsalou, 1998). In personal communication on this issue, Barsalou argues that his conception of perceptual symbol systems is inconsistent with the universality thesis because it assigns a central role to introspection, and introspection, as he views it, is not perceptual. 2 Goldstone and Barsalou do not explicitly embrace representational pluralism but, rather, acknowledge it as a possibility.
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While the sympathies of many active researchers lie with the more ecumenical view, the other views have received more attention in the literature. Defenses of ecumenicalism have tended to be rare and limited in scope – often invoking little more than a methodologically based agnosticism. In this article, I offer a broad defense of the view that there are diverse semantic codes, some of which are indigenous to perceptual systems and some of which are not. This defense unfolds in three stages: first, I show that the empirical evidence for perceptually based conception is fundamentally circumscribed. For the most part, it involves concrete or highly imageable concepts. The available evidence involving abstract concepts is limited in scope and incomplete. Second, I argue that the general arguments offered in support of perceptual symbols are much stronger with respect to concrete or highly imageable concepts than with respect to abstract concepts. In other words, they are more compelling with respect to just the sort of concepts for which perceptually based theories have always seemed well suited and not with respect to the sort of concepts for which they have always seemed ill-suited. Third, I offer a variety of empirical and theoretical reasons to think that some abstract concepts employ amodal representations. My core thesis is that our concepts contain both modal and amodal representations. I make no other claims concerning their realization. In other words, I remain neutral with regard to other important issues concerning representational format and cognitive architecture. While my position is consistent with the existence of a language – or languages – of thought (Fodor, 1975), it is also consistent with views that posit amodal representations that are not language-like in any important sense. Amodal symbols could be, for instance, highly distributed representations in a neural network. I emphasize this neutrality because my argument is aimed squarely at the question of modal-specificity. More is at stake than just the nature of the vehicles of thought. If representational pluralism is true, this should inform how we investigate and understand the human conceptual system. On a practical level, it offers a potential explanation for the specificity of cognitive deficits found in many lesion patients and children with developmental disorders. On a broader level, representational pluralism implies the existence of a cognitive heterogeneity and flexibility that is not implied by the other views. The general point that representational systems have distinct computational properties is a familiar one (Marr, 1982; Pani, 1996). My proposal is that the human conceptual system is characterized by a representational division of labor in which modal and amodal representations handle different aspects of our concepts. Although many of our concepts may be grounded in perception, the existence of amodal codes provides a partial explanation of how we are able to acquire semantic content that goes beyond perceptual experience. This capacity to go beyond experience may reflect a fundamental design feature of human minds.3
3 This capacity does not appear to be unique to humans. For example, evidence discussed in Section 6 of this essay suggests that some animals employ amodal symbols when they approximate quantities. The distinction between animal and human cognition with respect to amodal representations is thus likely to be a matter of degree.
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2. The empirical evidence for perceptual symbols 2.1. A circumscribed body of evidence The orthodox separation of conception and perception is threatened by an ever increasing body of evidence that perceptual symbols are important for certain cognitive activities. For instance, behavioral and brain imaging studies suggest that mental imagery (Farah, 2000; Kosslyn, 1994) and motor imagery (Grèzes & Decety, 2001; Jeannerod, 1995; Kan, Barsalou, Solomon, Minor, & Thompson-Schill, 2003) depend on sensory and motor representations, respectively. Perceptual representations have also been implicated in several aspects of memory (Glenberg, 1997; Martin, 2001). A number of recent behavioral experiments lend further support to the notion that perceptual representations are central to some cognitive tasks. For instance, Pecher, Zeelenberg, and Barsalou (2003) found a modality-switching cost in a non-imagistic property verification task. Participants verified verbally expressed facts involving one perceptual modality (such as the fact that leaves rustle) more rapidly after verifying a fact involving the same perceptual modality (such as the fact that blenders make noise) than after verifying a fact involving a different perceptual modality (such as the fact that cranberries are tart). More recently, van Dantzig, Pecher, Zeelenberg, and Barsalou (2008) found a similar modality-switching cost between a perceptual detection task and a property verification task. In a related vein, Stanfield and Zwaan (2001) asked participants to affirm whether or not pictures depicted the actions described in previously presented sentences. The actions had either a vertical or horizontal orientation (such as driving a nail into a floor or into a wall). Participants responded more quickly to the pictures that had the same orientation as the action described. Stanfield and Zwaan hypothesize that subjects generate a perceptual image of the action described in the sentence and then use this image to carry out the affirmation task. The proposal that some of our concepts are couched in perceptual codes also fits well with neuropsychological evidence showing that damage to sensory or motor areas can contribute to the loss of category-specific knowledge. Neurospychological case studies have shown that there are some patients who perform well on naming tasks involving artifacts but poorly on naming tasks involving living things and that there are other patients who exhibit the reverse pattern (Farah & McClelland, 1991; Warrington & Shallice, 1984). A common explanation of this double dissociation is that these categories are represented by different perceptual features (Warrington & McCarthy, 1987; Warrington & Shallice, 1984). Further support is provided by the fact that lesions can lead to the loss of multiple categories that share perceptual properties (Simmons & Barsalou, 2003). For instance, Adolphs, Damasio, Tranel, Cooper, and Damasio (2000) found that damage to the somatosensory cortex was correlated with deficits in the visual recognition of facial expressions. They propose that
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the simulation of producing facial expressions is involved in the recognition of facial expressions in others.4 Some recent neuroimaging data support the perceptually based interpretation of the lesion data. Martin, Wiggs, Ungerleider, and Haxby (1996), for example, found robust activation in visual areas with categories that appear to rely heavily on visual information for identification. Using a visual naming task and functional Magnetic Resonance Imaging (fMRI), Chao and Martin (2000) found increased activity in motor areas with highly manipulable objects when compared to less manipulable objects. In another fMRI study, Hauk, Johnsrude, and Pulvermüller (2004) had participants read individual words that referred to actions involving leg, arm, and head movements. They found that reading each type of action word produced increased activation in the particular areas within the motor cortex associated with performing the relevant movements. In sum, a number of studies employing distinct experimental paradigms and techniques suggest that some conceptual tasks involve perceptual representations. Positing such representations provides an economical and robust explanation for a diverse set of observed phenomena, including reaction times in behavioral studies, the functional character of some neuropathologies, and neural activation patterns in response to certain cognitive tasks. A caveat is warranted, however, because perceptual symbols are implicated in a circumscribed set of concepts. The relevant experiments involve concepts such as RUSTLING and NAIL DRIVING which seem to lend themselves to perceptual representation. To be more precise, most of the concepts employed in these studies are highly imageable (Paivio, 1971). This is important because the central point of disagreement between perceptually based views of conception and representational pluralism concerns the prevalence of perceptual symbols. Recently, investigators have gathered evidence that implicates perceptual representations in some cognitive tasks involving abstract concepts. Richardson, Spivey, Barsalou, and McRae (2003), for instance, attempted to ascertain whether or not comprehending abstract verbs such as argue and respect automatically activates spatial image schemas with a specific orientation (horizontal for argue and vertical for respect). Participants listened to short sentences while engaged in either a visual discrimination task or a picture memory task. Reaction times suggest that there was an interaction between the horizontal/vertical orientation of the image schema and the horizontal/vertical orientation of the visual stimuli. In a similar vein, Glenberg and Kaschak (2003) found that reaction times increased when response direction (a button press either away/toward the body) and the implied direction of either concrete action sentences (e.g. Andy gave you the pizza/You gave Andy the pizza) or abstract transfer sentences (e.g. Liz
4 A word of caution is needed, though, because the correlation between modality-specific damage and category-specific semantic deficits is not universal. Category-specific semantic deficits are not always associated with corresponding modality-specific perceptual impairments and, conversely, significant modality-specific perceptual impairments are not always associated with category-specific semantic deficits (Caramazza & Mahon, 2006).
told you a story/You told Liz a story) matched. They suggest that this ‘‘action-sentence compatibility effect” is the result of competition for resources by the motor planning associated with the action and the language processing associated with the sentence. Casasanto and Boroditsky (2008) describe six psychophysical experiments involving judgments about distance or duration using non-linguistic stimuli. Their findings suggest that irrelevant spatial information often interferes with judgments of duration, but the converse is not true. Casasanto and Boroditsky infer from these studies that temporal judgments rely on spatial representations. Casasanto (in press) provides a summary of evidence suggesting that the dominant spatial metaphor in a participant’s first language predicts performance on such non-linguistic tasks and that this performance can be altered by training a participant to use a different metaphor. 2.2. Interpreting the evidence While the evidence for perceptual symbols is suggestive, it is important to recognize that it does not conclusively establish that conceptual representations are perceptual. Indeed, the inference to perceptually based cognition can be questioned on a number of grounds. For one, the observed phenomena could be the result of perceptual processes merely correlating with conceptual processes served by amodal representations (Adams & Campbell, 1999). In other words, perceptual representations could be a consequence of thinking rather the vehicles of thinking. Second, amodal systems exist that can mimic the behavior of any perceptually based system (Anderson, 1978; Pylyshyn, 1973). Although this flexibility does not provide sufficient reason to posit amodal symbols – indeed it can be seen as problematic – it remains a fact that amodal representational systems can exhibit the behaviors outlined above. If there are independent reasons to posit amodal symbols, then they remain a live possibility. Third, amodal accounts are not monolithic. Indeed, some types will exhibit the features cited in support of perceptual symbols (Machery, 2007). For instance, despite the fact advocates of perceptual symbols often point to evidence of analogue representations as support for their approach, amodal symbol systems can also employ analogue representations. Although these epistemological and methodological considerations should give us pause, they do not prevent us from making a reasonable inference to the best explanation. Much of the evidence outlined above strongly suggests that highly imageable concepts involve perceptual representations. The skeptical hypothesis that the observed perceptual activity is epiphenomenal fits poorly with the lesion data and is undermined by some recent studies. For example, Pulvermüller, Hauk, Nikulin, and Ilmonlemi (2005) carried out a transcranial magnetic stimulation study in which they found that stimulation over motor areas affects action word processing (see also Buccino et al., 2005). The situation is different with respect to abstract concepts. Here the evidence is limited and incomplete. Although it gives provisional support for the notion that
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some abstract conceptual processing is handled by sensorimotor representations, it falls well short of establishing that abstract concepts are generally couched in such representations. Our notion of RESPECT may involve a vertical metaphor, but there is certainly more to this concept. The significance of the data concerning judgment of duration is also far from clear. Although the findings are surprising and provide intriguing evidence of the influence of cognitive metaphors on a non-linguistic task, a number of questions remain. For one, the extant literature on temporal processing suggests that it involves the interaction of multiple brain regions (Bhattacharjee, 2006). In addition, the proposition that all temporal processing is based on spatial metaphors seems unlikely because our ability to think about events depends centrally on both spatial and temporal information (Shipley, 2008). Indeed, the cited experiments could be interpreted as involving spatial and temporal judgments of individual events (a growing line, a moving dot and – more controversially – the presence of a line). Understood this way, Casasanto and Boroditsky’s findings suggest that the spatial extent of an event can affect our judgment of its duration. This would certainly be interesting and important, but it seems to have limited empirical reach with respect to the issue of perceptually based cognition. All in all, the available evidence suggests that some of our concepts employ perceptual representations – particularly concrete or highly imageable concepts – but fails to support the conclusion that perceptual symbols are the lingua franca of concepts.
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In order to properly evaluate the claim that concepts are perceptually based, we need to have an appreciation of the nature of perceptual symbol systems. Here and throughout the paper, I rely heavily on the work of Barsalou (1999); Prinz (2002) and Prinz (2005) because I believe that they have developed the most sophisticated and complete perceptually based approaches to concepts. This is not to say that they speak with one voice. Indeed, meaningful differences exist between their respective views. Whenever these differences are substantial and relevant to the topic at hand, I will address their views separately. The first question that arises is just what makes a mental representation perceptual or modal. Both Barsalou and Prinz maintain that a representation is modal if it is part of a specific sensory code: that is, if it is contained within a neural system specifically designed through natural selection to detect internal or external objects or events.5 They both extend this notion to include motor representations. By these lights, a key feature of perceptual symbol systems is that concepts are couched largely in sensorimotor representations. Prinz (2002) extends this idea and proposes that
all conceptual representations are indigenous to a sensory or motor modality. He refers to this as the modal-specificity hypothesis and claims that it can be thought of as a modern version of Hume’s dictum, ‘‘All our ideas are nothing but copies of our impressions” (Hume, 1748/1975, p. 686). Barsalou thinks that Prinz’s hypothesis goes too far. In particular, he believes that some amodal representations are needed to explain the functioning of introspection (personal communication). Both Barsalou and Prinz are committed to the idea that perceptual symbols involve simulations of experience.6 Roughly put, they propose that our conceptualization of a category consists of simulations of the experiences of perceiving exemplars of that category. Such simulations are the result of a kind of neurophysiological reenactment (Barsalou, 1999). Information concerning the neural activation patterns associated with the perception of an object or event that have been captured and stored by conjunctive neurons in neighboring association areas or convergence zones (Damasio, 1989; Damasio & Damasio, 1994) are used later, in the absence of perceptual input, to generate a partial reactivation of the sensory representations. These simulations are thought to have a number of important properties that make them well suited to serve as the vehicles for cognition (Barsalou, 1999; Barsalou, 2003a; Barsalou, 2003b; Barsalou, Solomon, & Wu, 1999). First, simulations need not be conscious. In other words, they may contain unconscious perceptual representations. This property removes some of the traditional objections to imagistic theories based on the unreliability or vagueness of introspection. Second, simulations will often be schematic in the sense they contain only some of the perceptual representations involved in the experience being simulated. For instance, a simulation in the visual modality of the concept CAT might involve shape representations but not color representations. Third, they will typically be multi-modal in the sense that they involve the reactivation of perceptual representations in several sensorimotor modalities. Finally, these simulations will generally be context-sensitive. In other words, they will be tailor-made in some sense for each circumstance. For instance, the simulation of CAT might re-enact the perception of a running cat on one occasion and the perception of a meowing cat on another. Part of the appeal of perceptual symbol systems is that they hold the promise of providing a revisionist explanation of important aspects of the human conceptual system. For instance, a benefit of perceptual symbols is that they can account for the demonstrated flexibility of cognition (Barclay, Bransford, Franks, McCarrell, & Nitsch, 1974; Barsalou, 1982). Because concepts are not associated with individual simulations but are instead variable constructions which occur temporarily within working memory (Prinz, 2002), simulations will vary relative to the task demands of a given context
5 Aydede (1999) argues that this definition of a perceptual symbol casts its net too widely because arbitrary and abstract representations could be located within sensory systems. This is an excellent point, but I am not going to belabor it because my arguments for amodal representations succeed even if we adopt this liberal definition of a perceptual symbol.
6 I am using Barsalou’s terminology here because it seems both more intuitive and general than Prinz’s. Prinz employs the notion of a ‘‘proxytype,” a technical term of his own invention that is more intimately tied to details of his specific position. It does not do terrible violence to the notion of a proxytype to say that it involves simulation.
3. Perceptual symbol systems 3.1. Simulation and conception
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and will typically involve only a small subset of the information stored in memory. Another intriguing aspect of a perceptual symbol system approach is that it provides a novel means of distinguishing types from tokens. Barsalou (1999) and Barsalou (2003) suggests that the conceptual system should be understood in terms of both simulators and simulations. A simulator is a distributed system spanning association and perceptual areas that generates simulations. To possess a concept such as DOG is to have a skill or ability to generate appropriate perceptual representations of dogs in a given situation. Any particular simulation will contain a subset of the modal representations contained within the simulator. Categorization can in turn be explained in terms of the degree of fit between actual perception and simulation. The productivity of concepts can also be explained through the interaction of simulators. Simulators can be combined in a combinatorial fashion to produce complex perceptual simulations (Barsalou, 1999; Barsalou & Prinz, 1997). Concepts support a number of cognitive functions. They help explain our ability to appropriately categorize objects and to draw inferences about category members. More generally, they play fundamental roles in language, memory, and thought. Barsalou and Prinz provide three general arguments for their claim that cognition is handled by a perceptual symbol system: one that straightforwardly appeals to recent empirical results, a second that extols to the general advantages of perceptual symbols, and a third that attacks the empirical basis for amodal symbols. I have already shown that the first argument is insufficient; in subsequent sections, I critically assess the other two. 3.2. The problem of non-perceptual memory processes Supporters of perceptual symbol systems recognize that the ability to partially re-enact perceptual experiences cannot fully explain our ability to generalize and abstract away from particular exemplars. They typically propose that long-term memory integration processes underlie our ability to create appropriate simulations (Barsalou, 2003a). This move offloads significant aspects of conceptualization into non-perceptual association areas of the brain. It also raises a significant problem: because category knowledge across modalities must be integrated to produce adequate simulations, it seems likely that convergence zones will contain amodal symbols. Both Barsalou and Prinz are aware of this problem and adopt deflationary strategies to defuse it. Although the details differ, both argue that the conceptual role played by long-term memory processes is somehow constrained enough to not require conceptual representations. For instance, after Barsalou et al. (2003, p. 87) concede that ‘‘. . .conjunctive neurons in convergence zones constitute a somewhat amodal mechanism for capturing and reenacting modality-specific states,” they go on to argue that the role of this mechanism is simply to enable the activation of appropriate perceptual symbols that then support conceptual processing. They also contend that alternative explanations of this capacity are available that do not re-
quire amodal symbols.7 Prinz (2002) argues that long-term memory networks form various types of links between perceptual representations in various different codes. Although he admits that these links can be more than bare associations – he proposes, for instance, that some are transformational and others are situational – he claims that they are insufficiently rich to count as conceptual representations. In the end, both Barsalou and Prinz seek to preserve their commitment to perceptual symbols by limiting the scope of influence of any possible representations within relevant long-term memory systems. Whether or not these deflationary arguments can be sustained remains an open question. Their fate will ultimately be decided by further empirical work. It is important to recognize, however, that there is a place in the very conception of a perceptual symbol system where amodal symbols might be effective. The functional argument for amodal symbols has always rested in large part on their capacity to encode, integrate, and transfer information obtained from different modalities. If association areas contained amodal symbols, this would provide an economical explanation of how coordinated multi-modal perceptual simulations were possible. 4. The argument from methodological parsimony Proponents of perceptual symbols often argue that considerations of methodological parsimony favor their position (Barsalou, 1999; Prinz, 2002). Their reasoning is roughly that adopting perceptual symbols frees us from having to posit a separate class of amodal representations. According to Occam’s razor, less is more when it comes to theoretical posits. A theory that only posits perceptual representations should therefore be preferred over one that posits both perceptual and amodal representations. Three factors undermine the argument from methodological parsimony. The first is that it rests on a partial accounting. While perceptual symbol theories are clearly more parsimonious than pluralistic theories with regard to the representations that they posit, this does not mean that they are more parsimonious overall. An assumption shared by all of the theories under consideration is that two things are constitutive of concepts: representations and mental operations involving those representations. A consequence of this is that we need to assess the relative complexity of the mental operations associated with a hypothesized perceptual symbol system in order to adjudicate the issue of its overall parsimony. There are reasons, however, to suspect that the mental operations needed for an adequate perceptual symbol system will be appreciably complex. As mentioned above, perceptual simulators need to be more than systems for replaying recorded information. Barsalou (1999) proposes that simulators employ introspection and Barsalou et al. (2003) propose that they employ processes of abstraction, generalization, and evaluation. Given that the extent and complexity of the 7 On more than one occasion, Barsalou has suggested that simulators might contain ‘‘supramodal” representations. I am not convinced that it is possible to make a principled distinction between supramodal and amodal representations.
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mental operations needed to explain these processes remains in question, we are not yet in a position to judge the overall complexity the perceptual symbol approach. The second difficulty with the argument from methodological parsimony is that parsimony considerations are defeasible. It is not difficult to come up with examples from the history of psychology and neuroscience where analogous reasoning would have lead researchers astray. For example, at the time of its inception, the reflex arc theory of memory was parsimonious in the sense outlined above (Finger, 1994). Unfortunately, the theory turned out to be incompatible with a host of behavioral and neuropsychological evidence (Lashley, 1950). None of this is to suggest that parsimony considerations are irrelevant; it is just that they cannot be viewed in isolation. The central question within any scientific debate is ultimately which theoretical explanation enjoys the greatest empirical support. Parsimony may factor into this judgement, but so should other considerations such as the degree to which each theory fits with the available evidence, the testable predictions that each theory makes, the background assumptions behind each theory, and so on. Parsimony considerations come into play primarily when other things are equal. The third problem with the argument from parsimony is that other things are not likely to be equal. As I will argue in subsequent sections, empirical evidence and theoretical considerations support the notion that abstract concepts are handled at least in part by amodal representations.
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which we identify dogs and the natural kind itself. The notion of nominal content is important for two reasons. The first is that it provides an explanation of how we are able to use our concepts to carry out actions such as tracking and categorizing objects. The second is that the ability to carry out these actions helps explain how our concepts are able to represent real contents. In terms of our example, the ability to recognize dog appearances helps us track real dogs. Prinz’s idea is that nominal contents associated with perceptual symbols make them well suited for bearing real contents. His argument for this turns on two claims. The first is that mental states represent entities and properties because they stand in certain nomic relations to them. Prinz, in other words, adopts an information-based approach to meaning. On this approach, mental representations have intentional content because, under certain conditions (to be specified by the particular semantic theory), they causally co-vary with their contents.8 The second is that perceptual symbols can secure these nomic relations in a way that amodal symbols cannot because they are already causally connected to the referents. Prinz (2005, p. 684) explains that, ‘‘The mechanisms that allow us to identify objects and interact with them also, thereby, establish reliably causal relations with those objects.” The fact that perceptual representations are already causally engaged with the intentional objects of our concepts presumably helps us enter into appropriate causal relations with them. 5.1. A reformulation of the abstract ideas objection
5. The argument from intentionality A central issue for any theory of concepts is how mental states come to represent things or events in the world. Both Barsalou and Prinz argue that, because of their dual role as vehicles for perception and conception, perceptual symbols are better situated for bearing content than amodal symbols. Comparing the relative merits of amodal and perceptual symbols, Barsalou writes (1999, p. 597; emphasis in the original), Where perceptual symbols do have an advantage [over amodal symbols] is in the ability of their content to play a heuristic role in establishing reference. Although perceptual content is rarely definitive for intentionality, it may provide a major source of constraint and assistance in determining what a symbol is about. A perceptual symbol consists of a neurophysiological re-enactment of a collection of perceptual representations. It can be thought of as having perceptual content because there are certain states of affairs in the world that would be likely to elicit these representations under normal conditions. Barsalou’s suggestion is that this perceptual content can facilitate the possession of intentional content. Following Locke (1690/1979), Prinz (2002) claims that perceptual simulations bear two distinct kinds of content: nominal (or cognitive) content and real content. To put it roughly, his position is that perceptual symbols refer both to the appearances of objects and their essences. By these lights, our concept DOG refers both to the properties by
The argument from intentionality has weak and strong versions that need to be kept distinct. The weak version is that a system containing some perceptual representations is better situated to solve the problem of intentionality than one that contains no perceptual symbols. Both Barsalou and Prinz point out that a system containing only amodal symbols struggles to explain how individual symbols come to be associated with things and events in the world (see also Glenberg & Robertson, 2000). This weak form of the argument does not threaten representational pluralism because a representational pluralist can concede that perceptual symbols are well suited for bearing certain contents while maintaining that they are poorly suited for bearing others. Both Barsalou and Prinz also make statements that express a strong version of the argument from intentionality. This form of the argument from intentionality holds that perceptual symbols are better situated to represent most concepts (including abstract concepts). The strong form of the argument from intentionality is the one needed to exclude representational pluralism. In order to defeat it, I need to show that there is some class of concepts for which perceptual symbols have no clear
8 It is possible to criticize Prinz for his appeal to information-based semantics (e.g. DeMoss, 2004). I do not have the space to assess this semantic approach here, but it is worth pointing out that it allows both Prinz and Barsalou to avoid many of the traditional problems associated with imagistic theories of concepts. Adopting a different approach might very well require significant changes to the overall conception of perceptual symbol systems.
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heuristic advantage with respect to their intentionality. I contend that abstract concepts are just such a class. This claim builds on a traditional objection to perceptual representations. As many have noted, perceptual representations seem ill-suited for representing abstract concepts. Some of the most obvious candidates are logical concepts such as NEGATION, OR, and TRUTH. Other commonly cited exemplars are theoretical concepts about unobservable entities such as ELECTRON and mathematical concepts such as NUMBER. Perhaps the largest category includes social concepts such as JUSTICE, DEMOCRACY, or MORALITY. Within philosophy, critics of perceptually based approaches to cognition have traditionally argued that perceptual symbols cannot possibly represent abstract concepts. This is too strong. The hypothesis that abstract concepts are represented by perceptual symbols may be empirically implausible, but it is not impossible. Indeed, I take it that Barsalou (1999) has shown that a perceptual symbol system can exhibit many of the necessary conditions for representing concepts (abstract or otherwise), including productivity, implementing a type/token distinction, supporting inferences, and the ability to represent propositions. Below, I defend a weaker assessment of the problem posed by abstract concepts that is nevertheless sufficient to undermine the strong version of the argument from intentionality. My claim is that proponents of perceptual symbols have failed to show that modal-specificity confers any special benefit on perceptual symbols as vehicles for abstract concepts. For the sake of expedience, I focus on a particular abstract concept, DEMOCRACY. I have chosen this example because it seems fairly pedestrian, and any problems associated with it are likely to be the rule rather than the exception. Because Prinz and Barsalou offer distinct approaches to abstract concepts, I discuss each separately. 5.2. Prinz on abstract concepts Supporters of perceptual symbols typically argue that they can, at least in principle, account for abstract concepts. In keeping with this, Prinz (2002, p. 148) argues that, ‘‘. . . the failure to see how certain properties can be perceptually represented is almost always a failure of the imagination.” In order to support this claim, he identifies several possible means by which perceptual symbols might handle abstract ideas: including mental operations, sign tracking, metaphorical projection, and labeling. In order to undermine the argument from intentionality therefore, I need to demonstrate that none of these strategies manifests a heuristic advantage for perceptual symbols. 5.2.1. Mental operations The modal-specificity hypothesis applies to mental representations but not to mental operations. Therefore, a possible strategy for handling problematic cases is to claim that they involve the latter rather than the former. Advocates of perceptual symbols have adopted this strategy with a number of abstract concepts. For instance, Barsalou (1999) explicates our everyday notion of TRUTH in terms of a matching operation that compares our expectations
to our perceptual experiences. On this view, in other words, our everyday notion of TRUTH involves a recognized correspondence between our beliefs and our perceptions. Information that has been stored in long-term memory is used to generate perceptual simulations for sentences. These simulations are then compared to the perceptual representations produced by our experience of and interaction with the world. A sentence is judged to be true when there is a sufficient match between the perceptual simulation associated with it and our actual perceptual experience. Prinz (2002) similarly explicates NEGATION as an inversion of the matching function. According to his view, the thought that rocks are not animals will be judged to be true if there is a failed mapping between our experience and the perceptual simulations associated with the thought that rocks are not animals. As a defense of modal-specificity, the key idea is that the thought associated with a sentence and the thought associated with a negation of that sentence are purported to contain the same conceptual constituents. These thoughts are distinguished by the mental operations carried out on these constituents. These proposals have generated a great deal of controversy. A number of intertwined criticisms are common. One is that they conflate truth with perceptual similarity (Mitchell & Clement, 1999). Another is that they leave something out because TRUTH is more than matched expectations (Adams & Campbell, 1999). Recall that perceptual symbol theorists typically appeal to perceptual matching in their account of categorization. But categorizing something as a dog is not the same as thinking that it is true that it is a dog. A third criticism is that these proposals are simply too verificationist. It seems possible to accept a statement as true without having a clear set of perceptually based expectations for that statement. Both Barsalou (1999) and Prinz (2002) offer responses to these criticisms. Rather than wade more deeply into these turbulent waters, though, I am going to acknowledge the controversies and move on to the question of applying this strategy to DEMOCRACY. This seems reasonable because the subject of truth is a contentious topic within both philosophy and psychology. Requiring that a general theory of conceptual representation solve this problem seems to be setting the bar too high. Given the long history of disagreement on this topic, there are also just too many positions and nuances to consider. In addition, logical concepts seem to be a special and circumscribed class of abstract concepts. For this reason, it seems possible and perhaps even reasonable to bracket off our concerns about this class of concepts. Even if we assume that logical concepts can be treated as mental operations, there is no reason to think that the mental operation strategy will be able to capture the full content of DEMOCRACY – a concept that likely involves a number of social concepts, such as GOVERNMENT, CONSENSUS, ELECTION, etc. that are neither straightforwardly perceptual nor fully explainable in terms of internal mental dynamics. This is not to say that mental operations may not be important to some aspects of DEMOCRACY. Certainly, representing this concept may involve a number of logical operators. In addition, it is conceivable that
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aspects of the decision making involved in voting can be partially explained in terms of mental operations. Nevertheless, it remains the case that significant aspects of the concept of democracy cannot be captured by mental operations. 5.2.2. Sign tracking The basic idea behind Prinz’s second strategy is that perceptual representations of contingently correlated perceptual features can be used as a symbol for an abstract category. Applying this strategy to DEMOCRACY, one might propose that it is represented on a given occasion by a schematic perceptual simulation of people carrying out one or some of the actions associated with democracy (placing ballots in a box, punching out chads, pulling levers in a booth, penciling-in bubbles on a scantron sheet, dipping fingers in ink, and so on). A challenge faced by this proposal is that there are many actions and events associated with democracy. This seems to imply that a complex set of simulations may be needed. How complex though? Do we need to simulate the counting of the ballots, the official declaration of a winner, the transfer of power, the functioning of government, the rule of law, and so on? Any proposal that we simulate a large subset of the relevant events faces a number of difficulties. At some point, considerations of cognitive economy may come into play because the perceptual symbol representing the concept cannot completely tax our cognitive resources. Processing load is only one consideration, though. A further problem with positing complex simulations is that the more complex a simulation associated with an abstract concept is, the more difficult it is to envision how it could productively combine with other concepts. It even seems doubtful that people actually have a rich enough knowledge of the functioning of democracies to create a sufficiently complex symbol. Furthermore, we seem able to think about DEMOCRACY in situations where we have incomplete knowledge. For example, I can wonder about whether or not Moldova is a democracy without knowing many of the details concerning how elections are held, power is transferred, etc. Given my palpable lack of knowledge about Moldova, any simulations of these events (even highly schematic ones) would likely contain many inaccurate details. Despite this deficit with regard to my simulation abilities, I am able to draw general inferences about what would be the case if Moldova is in fact a democracy. Given these considerations, it seems reasonable to propose that the relevant schematic simulations should only encompass the perceptual features associated with a circumscribed subset of the activities associated with democracy. These features are also likely to be idiosyncratic because there are many physical ways to hold an election. Does this sort of perceptual symbol enjoy a clear advantage over an arbitrary amodal one? It does not for the simple reason that the perceptual properties it contains are not a reliable means of tracking democracies. The argument from intentionality turns on the idea that perceptual properties give us a leg up with regard to entering into the appropriate nomic relationships between the symbol and its referent. This strategy seems to work with a concept
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like DOG because one can track dogs by their appearances. The problem with an abstract concept such as DEMOCRACY is that the correlation between the perceptual features likely to be contained within a perceptual symbol for this concept and the presence of its referent is loose at best. The problem is not just that there are hard cases or even that false positives are likely; instead, it is that little direct connection exists between these perceptual features and what makes a government a democracy. Recently, Prinz (2005) has suggested that an appeal to internal perceptual states, particularly ones associated with emotions, might be employed to help with abstract concepts. Applying this strategy to the issue at hand, one might try to enrich the perceptual simulation of the act of voting by including certain internal somatic perceptions. If we assume that different emotions can be broadly distinguished by somatic state (Prinz, 2004), we should be able to associate the act of voting with a certain type of emotion. Unfortunately, there is little reason to think that it will provide any help. The trouble is that genuine acts of voting are not distinguished from false ones by the emotion experienced by the voters at the time of voting. Fear, for instance, can be associated with both freely chosen and coerced votes. The only way an appeal to emotions can help is if one is allowed to include the conceptual content of the emotion (such as the fear that one will be punished by the government for voting the wrong way). This will not work as an attempt to provide a perceptual symbol for the concept DEMOCRACY, though, because the relevant conceptual content of an emotion is itself likely to contain abstract concepts (such as GOVERNMENT). The main problem with the sign tracking strategy is that a perceptual symbol of democracy is likely to be a poor democracy-detector. If it is a poor democracy-detector, however, there is little reason to suppose that it has an advantage over an amodal symbol with regard to representing DEMOCRACY. Because perceptual properties generally fail to distinguish true from false instances of democracy, perceptual symbols appear to be at a disadvantage when it comes to entering into the appropriate nomic relations needed for possession of the concept. 5.2.3. Metaphorical projection Prinz’s third strategy for addressing the abstract ideas objection, metaphorical projection, emerges from work in cognitive linguistics. Several cognitive linguists have proposed that metaphor plays a fundamental role in our conceptual system (Lakoff, 1987; Lakoff & Johnson, 1980). To give an example, Lakoff and Johnson (1980) claim that our understanding of the concept ARGUMENT is shaped by the metaphor of ARGUMENT IS WAR. This metaphor appears to explain aspects of our linguistic behavior, such as the fact that we use words associated with war to describe arguments. For example, one defends a position in an argument while attempting to attack, demolish, and shoot down the claims of one’s interlocutor. There are a number of reasons to be skeptical of the attempt to infer metaphoric representation from this sort of linguistic evidence. For one, it is not clear that linguistic patterns such as those outlined above directly reflect
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conceptual structure. Indeed, alternative explanations of metaphors that do not require positing metaphoric representations are available (Murphy, 1997). Another problem is that the proposed metaphoric projections seem developmentally implausible (Murphy, 1996). It seems unlikely that an understanding of the complexities of war is required to understand the nature of arguments. Furthermore, evidence suggests that children’s understanding of metaphor remains quite poor before the ages of 8–10 (Winner, Rosenstiel, & Gardner, 1976). Applying the metaphor strategy to DEMOCRACY would most likely involve two steps. The first would be to decompose this concept into a set of sub-concepts such as FREEDOM and CONTROL. The second would be to offer an explanation of these sub-concepts in terms of a perceptual metaphor. FREEDOM might, for instance, be interpreted as a metaphorical extension of an absence of physical restraint. For this two stage strategy to work as a defense of the modal-specificity hypothesis, it must be the case that all of the content of FREEDOM can be captured by the application of a perceptually based metaphor. There is an inherent difficulty faced by the attempt to capture conceptual content in terms of metaphor, however: while a metaphor enables us to highlight the similarities between two concepts, it cannot capture the important differences. Arguments, after all, are not really wars. Freedom is both more and less than a lack of physical restraint. Recognizing the appropriate connections between a perceptual experience and what it is being metaphorically extended to cover seems to require a prior understanding of the concept. Without such an understanding, it is difficult to see how one can arrive at a correct interpretation of a metaphor. 5.2.4. The labeling strategy The labeling strategy co-opts a common strategy for handling abstract content by means of amodal symbols. On this strategy, a concept such as DEMOCRACY is understood in terms of a complex network of inferentially related concepts such as GOVERNMENT, ELECTION, CONSENSUS, FREEDOM, and RULE OF LAW. The labeling strategy reconstitutes this strategy within a perceptual symbol system. The general idea is that abstract concepts can be captured in terms of networks of verbal labels rather than networks of inferentially related amodal symbols. DEMOCRACY would then be represented by means of a lexical network connecting the English word democracy to the English words government, election, consensus, rule of law, etc.9 With the labeling strategy, language becomes a virtual amodal symbol system because external labels are abstract, non-analogical representations. Unlike other perceptual symbols, external labels are not simulations of experience with the referent of the concept. They are only modal in the sense that they are simulations of verbal experience. In other words, the connection between the modal-specificity of the symbol and its ability to refer 9 Burgess and Lund (1997) and Landauer and Dumais (1997) provide examples of how the labeling strategy might be realized in a semantic theory.
has been removed. Unfortunately, it is precisely this connection that is supposedly responsible for the advantage of perceptual symbols over amodal ones. Adopting the labeling strategy therefore abandons the argument from intentionality precisely when it seems most needed. Little appears to be gained by adopting the label strategy other than the preservation of the nomological possibility of a perceptual symbol approach. Something appears to be lost, however, because special challenges face the label strategy. For instance, it is not clear how to handle something as basic as semantic ambiguity or polysemy. In a system employing amodal representations, the same external label can be associated with separate internal labels, which in turn bear distinct contents. This technique is not available if our concepts are tied to the external label itself. One might propose that ambiguity occurs when distinct networks are associated with the same label, but this just raises the question of how we individuate and track these networks. To get an idea of the nature of the problem of posed by polysemy, consider the external label value. When used as a noun, this label can express a number of different meanings including, but not limited to, a fair return in an exchange of goods, services, or money; monetary worth; relative worth; an intrinsically desirable or worthwhile principle or quality; an assigned numerical quantity; the relative duration of a musical note; and the relative luminosity of a color. The current proposal would distinguish the different meanings of such external labels by networks containing associations with different external labels. This only shifts the problem, though, since many of these labels will also be polysemous. Moreover, these networks are associated with each other because they are associated with the same label. What makes them separate networks as opposed to just a single network? What enables us to track these networks? Similar issues arise with synonymy. The supporter of perceptually based conception needs to show how two terms with distinct networks of associations can be synonymous. Similarity alone is unlikely to be a sufficient condition. For example, the networks associated with the labels buy and sell are likely to be very similar because every instance of buying is also an instance of selling. The difficulty posed by polysemy and synonymy is part of a more general problem faced by the labeling strategy. Any theory of lexical concepts must be able to distinguish associations that have to with conceptual content and those that do not. Amodal approaches typically handle this problem by associating external labels with internal symbols that are part of a semantic representation system. External labels, though, have any number of associations that have nothing to do with semantic content. For example, external labels have phonological associations that manifest themselves in speech errors. If the labeling strategy is to be considered a viable alternative to amodal approaches, it needs to provide at least an outline of how to distinguish between those associations that are relevant to a particular concept expressed by an external label and those that are not. Appealing to a vague notion of simulation competence does little more than rename the problem.
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My point is not that amodal symbols provide an easy solution to the difficult problems of psychosemantics. Instead, I am appealing to the fact that internal amodal representations seem to make these difficult problems more tractable than they would be otherwise. Prinz claims that perceptual symbols are better suited to representing our concepts than amodal symbols. The burden of proof thus falls on him to show that external labels can handle fundamental semantic phenomena such as polysemy and synonymy more effectively than amodal symbols. No such demonstration has been supplied. 5.3. Barsalou on abstract concepts Barsalou offers a single general strategy for representing abstract categories (Barsalou, 1999). This strategy has two stages: first, one identifies the conceptual content of the abstract concept under consideration. Second, one creates a perceptually based representation of this content by applying three core mechanisms: framing, selectivity, and introspective symbols. Barsalou maintains that once we have the right content, it is possible to represent that content ‘‘directly” through perceptual reenactment. According to Barsalou (2003b), amodal theorists have insufficiently considered the conceptual content of abstract concepts. Despite the widespread recognition of the existence of situation effects on cognitive performance, the situational nature of our concepts has been overlooked by the mainstream because researchers have generally assumed that details concerning background situations have been lost in the process of abstraction. The standard view is that conceptual representations capture relatively invariant properties of category members. In contrast to this view, Barsalou proposes that extensive information about background situations is preserved in the process of abstraction and is stored in long-term memory. Within a particular context, this situational information can become active and influence cognitive processing. The notion that our concepts are embedded within knowledge of background situations is supported by evidence from feature generation experiments. In a preliminary study, Barsalou and Wiemer-Hastings (2005) asked participants to generate typical properties for three abstract concepts (TRUTH, FREEDOM, and INVENTION), three concrete concepts (BIRD, CAR, and SOFA) and three intermediate concepts (COOKING, FARMING, and CARPETING). Barsalou and Wiemar-Hastings coded these responses into various property types, such as taxonomic, entity, setting/ event, and introspective properties. They make much of two findings: the finding that participants generated situational properties with both concrete and abstract concepts and the finding that participants tended to generate more event and introspective properties with abstract concepts. In a more fully realized experiment employing similar methodology, Wiemar-Hastings and Xu (2005) found support for quantitative and qualitative differences between abstract and concrete concepts. Their participants tended to produce fewer entity properties, more introspective properties, and more relational properties with abstract concepts than with concrete concepts.
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Wiemar-Hastings and Xu propose that abstract and concrete concepts are generally associated with different aspects of situations: abstract concepts tend to focus on introspective and social aspects of situations while concrete concepts tend to focus on physical entities and actions. Even if it is true that all concepts are situated, this alone does not establish that they are represented by perceptual symbols. One could reasonably argue that amodal symbols are well suited for representing the objects and events that make up situations. Barsalou and his colleagues make the further argument that perceptual symbols are in a better position than amodal symbols to account for situation effects. They claim that, if perceptual simulation underlies conception, this imposes a de facto constraint on our concepts because simulations are likely to involve relevant settings, actions, and events. Yeh and Barsalou explain (2006, p. 352): If a perceptual experience takes the form of a situation, and if a conceptual representation simulates perceptual experience, then the form of a conceptual representation should take the form of a perceived situation. When people construct a simulation to represent a category, they should tend to envision it in a relevant perceptual simulation, not in isolation. When people conceptualize chair, for example, they should attempt to simulate not only a chair but a more complete perceptual simulation, including not only a chair but a more complete perceptual situation, including surrounding space and any relevant agents, objects and events. According to this approach, people represent a category of simulating perceptual experiences of it members. These simulations are likely to include features of background situations because objects are typically not perceived in isolation but, rather, within a context. Barsalou proposes that information about the typical background situations of category exemplars is stored in long-term memory during category learning and becomes active when a concept is being processed. Barsalou’s counter-argument to the traditional abstract ideas objection is essentially an inductive one. He provides a recipe for representing abstract concepts and proposes that one can derive an empirically promising account of an abstract concept using this recipe. He writes (1999, pp. 600–601). First, identify an event sequence that frames the abstract concept. Second, categorize the multimodal symbols that represent not only the physical events in the sequence but also the introspective and proprioceptive events. Third, identify the focal elements of the simulation that constitutes the core representation of the abstract concept of the event background. Finally, repeat the above processes for any other event sequences that may be relevant to representing the concept (abstract concepts often refer to multiple events, such as marriage referring to a ceremony, interpersonal relations, domestic activities, etc.).
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Barsalou challenges his critics to attempt the same with any proposed counterexamples. I am going to take up that challenge and apply his recipe to the concept DEMOCRACY. A reasonable initial hypothesis concerning an event sequence that frames the concept DEMOCRACY is that of voting in an election. With respect to this event sequence, a context-specific perceptual simulation should include not only some of the relevant physical actions but also the introspective states of individuals carrying out those actions. Certain elements of the simulation (such as those aspects of voting that are associated with the process being free and fair) should be selected as more central than other aspects of the event sequence. Since democracy involves more than elections, a the DEMOCRACY simulator should also be able to simulate event sequences associated with the counting of votes, the orderly transfer of power, the rule of law, etc. Just how many relevant events need to be included remains an open question. Introspective events play an important role in Barsalou’s approach. They help distinguish concepts that do not seem initially to be perceptually distinct. For instance, from the perspective of a third-person observer, there is little perceptual difference between signing and forging a check (Anderson, 2005). The first-person experience of these two events, though, is presumably different. A perceptual simulation that involves introspective events would thus be able, at least in principle, to disambiguate these concepts. Introspective events could also play a similar role in distinguishing freely chosen votes from coerced ones. I do not dispute that introspective events can serve such a functional role. Instead, I contend that the appeal to introspection fails to provide compelling support for the existence of perceptual symbols. Barsalou himself denies that introspection is perceptual and from this concludes that at least some conceptual representations are not perceptual (personal communication). This appears to make him a representational pluralist on some level. Interestingly, Barsalou (1999) and Barsalou (2008a) maintains that introspective events are more central to abstract concepts than concrete ones. His solution to the problem of abstract concepts thus involves, at least in part, an appeal to amodal symbols. Within cognitive science, there are two basic approaches to introspection: one that treats it as a form of higher-order thought and another that treats it as a form of higher-order perception (Güzeldere, 1999). It is thus possible to view introspection as perceptual. This move, however, is not enough to exclude amodal symbols. The problem is that the question of what is being perceived arises. What does the ‘‘mind’s eye” see? Consider an act of voting. Whether or not it is freely chosen or coerced depends on a complex set of emotions, beliefs, and cognitive operations. The relevant introspective events, therefore, require access to complex judgments. If these judgments involve amodal symbols, however, the appeal to introspection provides little help as a defense of perceptual symbols. In order for introspection to help as a defense of perceptual symbols, it should be the case that the introspected appraisals themselves contain only perceptual representations. The most straightforward means of
accomplishing this would be to suggest that what is introspected is a perceptual simulation associated with forming the judgment. This will not work though because the relevant judgment itself is likely to contain abstract concepts. If so, then further introspective events, perhaps ones that also contain abstract concepts, will need to be simulated. This raises the specter of a problematic regress of multiply embedded perceptual simulations. In the end, the appeal to introspection leads to something of a dilemma for the proponent of perceptual symbol systems: either one accepts that introspection involves amodal symbols or one places unwieldy and implausible constraints on theories of introspection. The other important finding from property generation studies is that abstract concepts often involve social properties. This is certainly the case with an inherently social concept such as DEMOCRACY. Applying Barsalou’s strategy to this concept leads to the proposal that it is represented by situated perceptual simulations of the event sequences such as voting that are associated with democracies. A significant problem emerges with respect to the perceptual simulations of such social events. What makes a particular event sequence an instance of voting is not its sensorimotor details but rather a series of institutional and relational properties. Voting is a performative act that depends crucially on external social factors. Carrying out an appropriate action in the wrong social context achieves nothing. Indeed, the difficult task of deciding whether an election was free and fair can often turn on factors that are external to individual perceptual experiences (such as whether or not there was ballot stuffing, whether or not the voting machines functioned properly, or whether or not the counting process was interrupted by an act of the judiciary branch of government). Barsalou’s proposal that our concepts, including abstract ones, are fundamentally situated is intriguing and has the potential to transform the field. Manifestly, it warrants further empirical investigation. In the end, though, it is not enough to secure the argument from intentionality. Many abstract concepts focus on introspective and social properties. It is far from clear, though, that these properties can be adequately represented using perceptual symbols. 5.4. Intentionality and the problem of abstract concepts A common complaint about perceptually based approaches to conception is that they are poorly suited for representing abstract concepts. In defense of perceptual symbols, supporters have endeavored to show that perceptual symbol systems have, in principle, the conceptual resources to deal with abstract concepts. To this end, they have identified a number of possible strategies. The very difficulty of this exercise, however, undercuts the argument from intentionality. While there are manifold reasons to believe that perceptual symbols are particularly well suited to represent many concepts – particularly those associated with perceptually identifiable categories – advocates of perceptual symbols have yet to provide compelling reasons to believe that they are similarly well equipped to handle abstract concepts.
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The fact that perceptual symbols do not seem to be well suited to representing abstract concepts does not completely rule out an appeal to intentionality. After all, it could be the case that amodal symbols are substantially worse off than perceptual symbols when it comes to representing abstract content. There are four reasons why this negative defense of perceptual symbols is not promising: first, the burden of proof falls on defenders of perceptual symbols who appeal to intentionality to demonstrate that perceptual symbols are better suited to representing abstract concepts. They need to show that there is a clear way in which the modal-specificity of perceptual symbols confers an advantage on them with respect to representing abstract concepts. So far, they have not succeeded in this endeavor. Second, amodal symbols have proved to be flexible and robust. As supporters of perceptual symbols often point out, they are posited by most current accounts of concepts. Although it is true that too little attention has been paid to the empirical investigation of abstract concepts, the fact remains that there are number of well established theoretical options for providing an amodal account of abstract concepts (definitions, exemplars, prototypes, theories, and massively distributed representations to name a few). An advantage of representational pluralism is that it enables one to appeal to any one of these types. Third, it is possible to turn the tables on the advocate of perceptual symbol systems. Several of the proposed strategies would be strengthened by the presence of amodal symbols. For instance, positing internal amodal symbols would enable us to avoid many of the problems associated with the external label strategy. Fourth, a split-decision between modal and amodal approaches (one in which both are found to be equally deficient with respect to abstract concepts) would be enough to block the argument from intentionality. This section should not be seen as providing a conclusive argument that abstract concepts are handled by amodal symbols. Amodal symbols may be better positioned to handle abstract concepts, but this does not establish that our conceptual system actually employs them. Reverse engineering in the biological and psychological sciences is a tricky business. The proper conclusion to draw is that general considerations about intentionality do not resolve the empirical issue of how abstract concepts are represented. Any advantage that perceptual symbols might enjoy over amodal symbols with regard to intentionality appears to evaporate with respect to abstract concepts. Because of this, the argument from intentionality cannot be used to decide between a perceptually based approach to concepts and a pluralistic one. 6. Positive evidence for amodal symbols: the case of number approximation 6.1. Barsalou’s criticism of the evidence for amodal symbols The most straightforward justification for amodal symbols is that they are theoretically expedient. Almost no one disagrees that amodal systems have a number of desirable qualities. Barsalou himself concedes (1999, p. 579):
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Amodal systems have many powerful and important properties that any fully functional conceptual system must exhibit. These include the ability represent types and tokens, to produce categorical inferences, to combine symbols productively, to represent propositions, and to represent abstract concepts. In other words, researchers have favored amodal symbol systems because in general they appear to have design-specs that seem suited to fulfill the desiderata for theories of concepts. After conceding that amodal symbols seem well suited for supporting a conceptual system, Barsalou (1999) goes on to lament that, ‘‘. . .there is little direct empirical evidence that amodal symbols exist” (see also Barsalou, 2008b; Barsalou et al., 2003). As he sees it, researchers have failed to adequately address the issue of whether or not conceptual representations are perceptually based, and the predominance of amodal symbol systems is the result of theoretical considerations and preconceptions concerning the limitations of modal systems rather than an assessment of a substantial body of evidence. An immediate problem with Barsalou’s charge is that evidence in cognitive science is rarely direct. Barsalou himself follows this charge with the introduction of indirect evidence supporting perceptual symbols. The requirement of directness is therefore dubious and should be removed. The real question is whether or not there is any empirical support for the existence of amodal symbols. The answer to this question is that researchers in the cognitive sciences have, in fact, gathered a great deal of evidence for amodal symbols. We can see this clearly through an example: research on number approximation.10 6.2. Number approximation Several different species have been examined for their ability to make numerical judgments, including dolphins, pigeons, raccoons, rats, and monkeys (for general summaries of this literature see Flombaum, 2002; Gallistel, 1990; Hauser, 2000). Sensitivity to numerical properties has been measured in the wild and in the lab using a number of different research paradigms. In many experiments, researchers have been careful to distinguish between sensitivity to the relative cardinality of sets from sensitivity to other scalar physical attributes of the stimuli. One reason to think that a form of numerical competence is involved is the ease with which animals can transfer numerosity between modalities (Hauser & Spelke, 2004). A striking example of this is that rats trained to respond to numerical sequences in one modality are able to generalize to novel sequences involving stimuli in other modalities or, even, two modalities (Meck & Church, 1983). A common feature of this research is that number discrimination varies with the ratio of the two numerosities in accordance with Weber’s law: that is, in order to obtain the same level of performance with larger numerical quantities that is obtained with smaller quantities, the difference between the compared
10 After developing this example, I discovered that Machery (2007) also appeals to it. I take this convergence as evidence of its aptness.
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quantities must be greater. In other words, there is typically a numerical distance effect. Behavioral research on adult humans suggests a similar capacity. In a common experimental paradigm, adults are given brief presentations of stimuli containing large cardinalities in order to prevent them from using explicit verbal counting. Another paradigm involves responses (such as sequential button presses) at rates that exclude the possibility of vocal or subvocal counting. These studies indicate that adults are able to represent approximate cardinality despite not having access to verbal representations. Their judgments are at above chance and vary in accuracy in proportion to size of the compared sets (Cordes, Gelman, & Gallistel, 2002; Hauser & Spelke, 2004). As was the case with the animal studies, there are several reasons to believe that amodal representations underlie this capacity. One indication is that similar performance has been found using various types of stimuli presented in various different modalities (Whalen, Gallistel, & Gelman, 1999). Another is that adults are just as successful when comparing sets across modalities as they are within a modality (Barth, Kanwisher, & Spelke, 2003; Barth et al., 2005). A body of research indicates that pre-verbal infants have a similar capacity for number approximation. Several studies have shown that infants as young as 6 months have the ability to distinguish sets involving 8 vs. 16 or, even, 16 vs. 32 elements when other continuous variables such as element size and total filled area are controlled for (Lipton & Spelke, 2003; Xu, Spelke, & Goddard, 2005). It appears that this ability requires large ratios at first, but becomes more precise over development (Lipton & Spelke, 2003; Xu, 2003; Xu & Arriaga, 2007).11 As was true with the adult studies, these abilities have been shown in experiments involving different modalities. A body of evidence from neuropsychology and cognitive neuroscience provides further support for a number approximation system. Lesion studies establish a double dissociation between number processing and semantic processing. In general, cases in which there is preserved linguistic and semantic processing but deficient number processing involve damage to one of several areas of the parietal cortex (Dehaene, Piazza, Pinel, & Cohen, 2003). Piazza and Dehaene (2004) argue that previous research indicates that one area of the parietal cortex in particular, the HIPS (horizontal segment of the intraparietal sulcus), is the best candidate for a domain-specific numerical estimation system. Some of their reasons for this claim are the following: the HIPS is more active during estimation tasks than those involving accurate computation; activation in
11 There is an ongoing controversy concerning infant number perception that centers on small number (1, 2, or 3) discrimination. A great deal of interest was generated by early studies which seemed to indicate that infants were able to discriminate small numbers (Starkey & Cooper, 1980; Strauss & Curtis, 1981). This research, though, failed to account for potential confounds between number and other continuous variables. More recent studies which have controlled for these factors have found no evidence of small number discrimination (Clearfield & Mix, 2001; Feigenson, Carey, & Spelke, 2002,). Interestingly, small number discrimination has been shown in monkey studies that control for these factors (e.g. Brannon & Terrace, 2000).
the HIPS correlates with numerical distance between compared sets; the HIPS shows higher activation when processing numbers than when processing other continuous categories such as colors or letters; and stimuli presented in different modalities can activate the HIPS in number-related tasks. While it is too soon to definitively identify the HIPS or any other part of the parietal cortex as where number approximation is localized, the results of the imaging studies are suggestive and fit well with the behavioral results described above. The existence of amodal symbols for approximate quantities is thus buttressed by a diverse, multi-disciplinary, and convergent body of research using various research measurements and methodologies. Pace Barsalou, there is at least one area of cognition where extensive research supports amodal symbols. Two responses to this argument are possible. The first is that alternative explanations may be available. We should not rush to conclude that the representations employed in number approximation are amodal because one could explain this cognitive ability without appealing to extrasensory representations. This response can be cashed out in one of two ways. One possibility is that number approximation is handled by mapping operations between representations in different modalities (Prinz, 2002). The evidence outlined above, however, suggests that we are able to estimate number both within and across modalities. Given this, number estimation cannot be fully explained in terms of a mapping operation between modalities. Another weakness of this proposal is that it does not specify the mechanism by which the mapping is carried out. This is problematic because an effective means of carrying out such a mapping is to have an amodal symbol system tracking approximate numerosity (Meck & Church, 1983). A second possibility is that number approximation is handled by perceptual representations within a single modality. In other words, input from different modalities could be translated into a representational format indigenous to a particular sensory modality. The trouble with this response is that it actually makes the case for amodal symbols rather than speaks against them. Recall that modal-specificity is defined with regard to input. Representations contained within a mechanism that has been shaped by natural selection to handle inputs from multiple modalities are amodal by definition.12 The second plausible response to the literature on number approximation is a deflationary one. The evidence only shows that amodal symbols are used in a single cognitive domain. Perhaps, concepts generally contain perceptual symbols, and number approximation is just an exception to the rule (Machery, 2007). This deflationary move faces three main challenges: First, it sets foot on a slippery slope because the difference between it and representational
12 In order to make this defense of perceptual symbols work, one would need to provide a new, non-circular definition of a perceptual symbol. Not only would this be suspiciously ad hoc, but it would require making an already fairly broad definition of a perceptual symbol even broader. Given the well known existence of top-down influences on perception, there is a real danger of making every cognitive representation a perceptual one as matter of definition (Aydede, 1999).
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pluralism is at best a matter of degree. Second, the extant data provides no clear reason to prefer this deflationary proposal over representational pluralism since the positive evidence for perceptual symbols is itself limited in scope. Given the limited evidence, why should we think that most concepts are couched in perceptual representations? Third, there are other cognitive domains that seem to involve amodal representations. For example, psycholinguists have long argued that many linguistic representations are amodal. If other domains involve amodal representations, then we should be open to the possibility of amodal semantic representations. While neither of the counter-argument strategies is particularly effective, two intriguing speculations emerge from the discussion. The first is that amodal codes may be a fairly common solution to the problem of information integration within cognitive systems that receive input from diverse sources. This proposal is in keeping with the ever increasing evidence of cross-modal effects (Shimojo & Shams, 2001). The second is that modality might be, in the end, a degree property. Some codes may be more closely tied to a particular modality than others. Although I do not have the space to defend either of these hypotheses here, both are worth exploring and fit naturally with representational pluralism. In the end, the literature on number approximation shows that Barsalou’s assertion that there is little evidence for amodal symbols is far too strong. A question remains, though, with regard to the frequency of amodal symbols. In the next section, I outline a body of evidence that suggests that amodal symbols play a more widespread role in our concepts.
7. Imageability and the need for representational pluralism Part of the appeal of a deflationary interpretation of the data on number approximation may lie in the fact that it enables one to avoid pluralism. Admittedly, there are prima facie reasons to be skeptical of pluralistic solutions to scientific questions. Compromise may be an effective way to govern, but it is generally not a good research strategy, and scotch-verdicts are rare in science.13 Furthermore, pluralistic theories tend to be overly flexible and difficult to falsify. Given these inherent drawbacks, pluralism should only be adopted when there strong reasons to do so. In this section, I will argue that the literature on imageability effects provides such reasons. A theme that has emerged in this essay is that there appears to be a qualitative difference between abstract and concrete concepts. While some tantalizing evidence implicates perceptual representations in the latter, proponents of perceptual symbols have failed to provide compelling reasons to think that they are involved in the former. There is also positive evidence with regard 13 They are not, however, unheard of. A classic example comes from vision science: two theories of color vision, the trichromatic and the opponentprocess theories, proposed different basic mechanisms. It turned out that distinct components of the retina realize each of these mechanisms.
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to at least one cognitive domain, number approximation, that some abstract concepts are handled by amodal representations. I propose that the empirical literature on imageability provides evidence of a further, more general neurophysiological dichotomy between abstract and concrete concepts. Converging evidence from cognitive science, neuropsychology and cognitive neuroscience supports the conclusion that abstract and perceptually derived concepts are handled by different representations and mechanisms.14 Imageability effects have been found in multiple disciplines by different investigators using different research methodologies and measures. Typically, imageability is defined as the ease with which a word gives rise to a sensorymotor mental image (Paivio, 1971).15 Highly reliable imageability ratings on number scales have been gathered for linguistic concepts by number of researchers (Bird, Franklin, & Howard, 2001; Paivio, Yuille, & Madigan, 1968; Toglia & Battig, 1978). Much of the original research on imageability was behavioral and demonstrated a processing advantage for highly imageable concepts in a number of cognitive tasks.16 For instance, lexical access has been shown to be quicker for highly imageable words than for abstract ones (Coltheart, Patterson, & Marshall, 1980). Highly imageable words are also recalled more quickly in memory tasks than abstract words (Paivio, 1971; Paivio, 1987; Wattenmaker & Shoben, 1987). A similar advantage is also found in word comprehension tasks (Schwanenflugel, Harnishfeger, & Stowe, 1988). Two major accounts of imageability effects dominate the literature on imageability: the context-availability theory and the dual code theory. The core idea behind the context-availability theory is that highly imageable words have greater contextual information stored in semantic memory networks. Imageability effects are explained by the facilitation of processing associated with increased activation in these networks. The reason that participants respond more quickly in a lexical decision task to a word such as ‘‘fingertip” than to one such as ‘‘idea” is that the former has more semantic associations than the latter. According to the so-called dual code theory (Paivio, 1987), two semantic systems exist, one supported by linguistic representations and the other supported by percep-
14 The imageability literature admittedly implicates different cortical areas than those implicated by the research on number sense. Clearly, this is compatible with representational pluralism. 15 Strictly speaking, imageability is a property of lexical concepts rather than words. However, a convention exists among researchers to refer to words as having high or low imageability. For the sake of convenience, I follow this convention in this essay. 16 Some researchers compare concrete and abstract words. Imageability is a broader concept than concreteness because in addition to including the perceptual images of concrete objects it includes sensory images of bodily states and motor images. It is generally recognized that imageability supports more robust generalizations than concreteness.
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tual representations.17 Words with low imageability are associated primarily with verbal representations while highly imageable words are associated with both linguistic representations and perceptual ones. Imageability effects are then explained in terms of the greater availability of perceptually encoded information. The debate between the context-availability and the dual code theories has proven to be difficult to settle through behavioral studies because supporters of each theory can point to some behavioral evidence. For example, supporters of the context-availability theory can point to studies that show imageability effects can be nullified when a rich supporting context is provided (Schwanenflugel & Shoben, 1983; Schwanenflugel et al., 1988). Supporters of the dual code theory can point to divided visual field studies that show a concreteness advantage for words presented to the right hemisphere (Day, 1979; Deloche, Seron, Scius, & Segui, 1987). A further problem is that these theories are not mutually exclusive. The dual code theory, for instance, is compatible with the existence of context-availability effects. Such effects are only threatening to the dual code theory if all imageability effects are reducible to the context-availability effect. This sort of universal negative claim, however, is difficult to establish. Recently, investigators have increasingly turned to neuropsychology and cognitive neuroscience in order to resolve this debate. In general, evidence from these fields supports the notion that there are distinct neural processes associated with context-availability and imageability effects. Below, I focus on the evidence for the latter because this evidence is more directly relevant to the issue of representational pluralism. Within neuropsychology, it has long been observed that some patients exhibit a processing impairment for verbs, but not for nouns, and other patients exhibit the reverse pattern. Researching this noun–verb dissociation is complicated by the fact that nouns and verbs tend to have different semantic properties (Druks, 2002). A number of studies, for instance, use only names of concrete things for nouns and actions for verbs. In response to this potential confound, some researchers have examined the degree to which imageability is a factor in the performance of aphasic patients. For instance, Bird, Howard, and Franklin (2003) examined three ‘‘verb-impaired” patients. They found that when imageability is taken into account, the purported verb-impairment disappears. Based on this finding, they propose that there are no true verb-selective deficits.18 More recent evidence suggests that many, but not all, 17 Paivio (1986) proposes that the linguistic representations used to encode semantic content are perceptual (i.e. they are auditory, visual, or motor representations). I part company with Paivio on this point and instead propose that the relevant linguistic representations are likely to be amodal. Paivio’s commitment to perceptual representations is problematic because there are independent reasons to posit amodal linguistic representations. For example, some aphasia patients exhibit deficits with regard to meaning related tasks such as providing definitions or object naming without exhibiting a corresponding deficit with respect to word form related tasks such as repetition or reading aloud (Caplan, 1987). 18 Bird et al. (2003) also examined three ‘‘verb spared” patients. They did not find a reverse imageability effect per se but found evidence that these patients have difficulties with concepts defined in terms of certain sensory features. This is compatible with the idea that highly imageable concepts involve collections of sensorimotor representations.
verb deficits are reducible to imageability differences. To give an example that is consistent with other studies, Crepaldi et al. (2006) examined 16 verb-impaired patients and found that 14 did not show a verb-impairment after imageability was controlled for (see also Berndt, Haendiges, Burton, & Mitchum, 2002; Luzzatti et al., 2002). The reverse dissociation, with preserved abilities for abstract words but a deficit for high imageable words, is attested but less common. For instance, Marshall, Pring, Chiat, and Robson (1996) describe a nonfluent patient, RG, who uses a disproportionate amount of abstract nouns in natural speech, exhibits better comprehension of abstract nouns than concrete nouns and performs poorly on object naming tasks. In a follow up paper, Marshall, Chiat, Robson, and Pring (1996) provide evidence that RG has similar difficulties with verbs that are distinguished by perceptual features. In general, the neuropsychological literature suggests that patients can be selectively impaired for concepts of high or low imageability, although the latter seems more common than the former. A number of electrophysiological experiments employing event-related potentials (ERPs) support a neuroanatomical distinction between concepts of high and low imageability. Often these experiments involve the elicitation of a specific electrophysiological component known as the N400 (a negatively directed waveform that tends to peak at 400 ms after the onset of the stimulus). This component has been shown to be sensitive to both contextual and semantic manipulations and is likely to be associated with several neurally distinct generators (Key, Dove, & Maguire, 2005). Several studies have found imageability effects on the N400 (Kounios & Holcomb, 1994; West & Holcomb, 2000). Nittono, Suehiro, and Hori (2002), for example, found that low imageable words elicited a smaller and more left-laterialized N400 than high ones in a reading task. In an effort to evaluate the claims of the context-availability and the dual code theories, Holcomb, Kounios, Anderson, and West (1999) created a task that involved a manipulation of both context and concreteness. ERP recordings were time-locked to sentence final words in a word-by-word reading task in which participants made semantic congruency judgments (e.g. Armed robbery implies that the thief used a weapon vs. Armed robbery implies that the thief used a rose). The researchers found that sentence final concrete words generated a larger and more anterior N400 in both neutral and semantically anomalous sentential contexts. Although it is difficult to precisely localize the neural generators from electrical potentials recorded at the scalp, the fact that concrete and abstract words elicited distinct topographic patterns suggests that they are caused by activity in different populations of neurons. Some critics have proposed that this evidence has limited implications with regard to concreteness effects because of the use of a sentential context rather than a single word presentation. Further studies, though, have found context-independent topographic effects associated with imageability in single word presentations (Kellenbach, Wijers, Hovis, Mulder, & Mulder, 2002; Swaab, Baynes, & Knight, 2002). For example, Kellenbach and colleagues visually presented three subclasses of nouns
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and verbs (abstract, high visual, and high visual and motor) in the context of a recognition memory task. They found that grammatical class and imageability were associated with robust but distinct electrophysiological effects. In sum, various ERP studies employing diverse tasks support the notion that different cognitive systems are associated with the semantic processing of high and low imageable words. The evidence from functional brain imaging studies is somewhat variable, with different studies finding that different patterns of activation are associated with the semantic processing of high and low imageable concepts. This may in part be due to the number of different tasks used. These include, but are not limited to, lexical decision, imageability judgment, mental imagery, memory encoding, semantic judgment and sentence verification. Despite the variability in the findings, the idea that neural activity is modulated by imageability is generally supported. A number of studies find that abstract words elicit greater activation in superior regions of the left temporal lobe (Binder, Westbury, McKiernan, Possing, & Medler, 2005; Giesbrecht, Gamblin, & Swaab, 2004; Kiehl et al., 1999; Mellet, Tzourio, Denis, & Mazoyer, 1998; Noppeney & Price, 2004; Perani et al., 1999; Sabsevitz, Medler, Seidenberg, & Binder, 2005; Wise et al., 2000) and inferior regions of the left prefrontal cortex (Binder et al., 2005; Fiebach & Friederici, 2003; Giesbrecht et al., 2004; Jessen et al., 2000; Kiehl et al., 1999; Noppeney & Price, 2004; Perani et al., 1999; Sabsevitz et al., 2005). When researchers look for areas of increased activity in response to high imageable words when compared to low imageable ones, the pattern is less clear. Whereas some studies find no areas of increased activation (Grossman et al., 2002; Kiehl et al., 1999; Noppeney & Price, 2004; Perani et al., 1999; Tyler, Russell, Fadili, & Moss, 2001), others find increased activation in right hemisphere areas (Binder et al., 2005; Jessen et al., 2000; Mellet et al., 1998; Sabsevitz et al., 2005). The fact that there is a more distinct pattern of increased activation elicited by low imageable words than by high imageable words fits with the neuropsychological observation that patients are more likely to have a selective deficit for low imageable concepts than for high imageable concepts. Although I do not have the space to adequately address the complexities of the imaging data in this essay, two recent experiments are particularly suggestive and worth discussing. Responding to the inconsistencies in the literature, Sabsevitz and colleagues (2005) attempted to control for some of the possible confounds. Their fMRI study incorporated a larger sample (28 adults) than previous studies and a task (judgment of semantic similarity) that is more likely to elicit deep semantic processing than a more superficial task such as lexical decision. Participants were visually presented with three words (e.g. cheetah, wolf, and tiger) in the form of a triangle. The task was to decide which of the two bottom words was most semantically similar to the top word. In this task, abstract nouns elicited greater activation in the left superior temporal and left inferior frontal cortex than concrete nouns, while concrete nouns elicited greater activation in a bilateral network of association areas than abstract nouns. Given that the left superior temporal and left inferior frontal cortex have been
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associated with language processing in previous studies (Bookheimer, 2002), these results fit well with the dual code theory. In an effort to test the context-availability and dual code theories, Giesbrecht et al. (2004) manipulated both imageability and semantic priming (a measure of the influence of context) in an event-related fMRI study. Participants were presented with prime word followed by a target word. The words were either semantically related (bread and butter) or unrelated (wheat and slipper). In addition, half of the pairs consisted of two high imageable words and half of the pairs consisted of two low imageable words. Both of these manipulations modulated activity in anatomically distinct areas of the left hemisphere. This study thus provides further support for the notion that context effects are distinct from imageability effects. Current evidence from cognitive neuroscience does not give us an unequivocal picture of how the lexical properties of high and low imageable words are represented in the brain. Many questions remain, and further research is needed to resolve conflicting results, disentangle possible confounds, and adjudicate outstanding theoretical issues. Despite the somewhat inchoate state of the field, however, the general hypothesis that distinct brain systems process high and low imageable concepts is supported by a diverse collection of behavioral, clinical, electrophysiological, and functional imaging studies. The functional distinction between concepts of high and low imageability implied by this body of evidence creates a serious problem for supporters of perceptual symbols because the strongest empirical evidence for their position involves highly imageable concepts. Research on imageability undermines their project because, if there are distinct cognitive mechanisms for processing high and low imageable concepts, then we cannot infer that one system uses perceptual representations from evidence that the other system uses them. Recently, Barsalou, Santos, Simmons, and Wilson (2008) offer a variant of the dual code theory. They propose that the imageability literature supports the existence of two modal-specific systems of knowledge representation: one employing linguistic representations and the other employing situated simulations. They refer to this as the LASS (language and situated simulation) theory of conceptual processing. There is a temporal dimension to this theory. Although conceptual processing involves a continuous interaction between these two systems, the more superficial linguistic processing tends to predominate early on and the deeper processing associated with the simulation system tends to predominate later. The key difference between this version of the dual code theory and a pluralistic one is its commitment to the modal-specificity of linguistic representations. Barsalou et al. (2008) are very clear on this point: According to this approach, there is no underlying system of amodal symbols that correspond to language – there are only linguistic forms (i.e. words). The intriguing proposition is that statistical distributions of linguistic forms represent knowledge. For example, the representation of bird is not an amodal symbols
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but is instead the distribution of words that co-occur with ‘‘bird” in natural language. This amounts to a partial adoption of Prinz’s labeling strategy because some semantic processing involves associations between perceptual representations of external labels. The novel aspect of this theory is that linguistic representations are only involved in superficial processing. They act as pointers to potentially relevant perceptual simulations that then perform the heavy lifting of conceptual processing. The appeal to language forms has a number of problems. First, there are a number of independent reasons to think that the some of the representations of language forms themselves are amodal. Psycholinguists have implicated amodal representations at many levels of linguistic analysis, including phonology, morphology and syntax. For example, amodal phonological representations are often posited to explain the fact that phonological generalizations hold with respect to both speech production and comprehension. While it is possible that all of the relevant information is encoded redundantly in both motor and auditory codes, the existence of amodal representations provides a parsimonious explanation of how auditory and motor information is integrated. Similar considerations apply to morphology. Furthermore, morphology involves properties such as agreement that do not seem tied to any particular perceptual modality. Syntax correspondingly employs abstract grammatical categories and constructions that apply equally to language production and comprehension. The case for amodal language representations is further bolstered by evidence that natural sign languages exhibit similar structure to natural spoken languages at all of these levels of analysis (Poizner, Klima, and Bellugi, 1987). Brain imaging research also finds increased activation in speech processing areas when profoundly deaf individuals view signs (Petito et al., 2000). For the appeal to language forms to work as a defense of perceptual symbols, one must show that the phonological, morphological, and syntactic generalizations at the heart of psycholinguistics can be captured in an empirically plausible way by a system employing only modal representations. Whether this can be achieved remains to be seen. Without this demonstration, though, LASS accomplishes little more than exchanging one controversial modal-specificity hypothesis for another. A further problem with the appeal to language forms is that it faces the same challenges with respect to polysemy and synonymy that Prinz’s labeling strategy faces. As we saw earlier, excluding an independent level of semantic representations has clear costs. Additionally, a robust body of ERP literature suggests that distinct syntactic and semantic processing begins almost immediately after a word stimulus is presented in the context of a sentence. While semantic incongruency is associated with the N400 (a negative deflection in the brainwave that peaks at around 400 ms), grammatical violations are associated with both the ELAN (an early left anterior negativity that typically occurs between 100 ms and 300 ms), and the P600 (a positive shift that tends to be largest at 600 ms; Friederici, 2002). Finally, several lines of evidence within cognitive neuroscience suggest that phonological,
syntactic and semantic processes are handled by distinct portions of the left inferior frontal gyrus or IFG (Bookheimer, 2002). There is a clear affinity between the pluralistic explanation of imageability effects that I favor and the LASS explanation. Both explanations hold that perceptual simulations play an important role in highly imageable concepts and linguistic representations play an important role in abstract concepts. Where the two approaches differ is with respect to how they view linguistic representations. On the LASS view, linguistic representations are purely modal and there is no independent level semantic representation. Neither of these claims is well supported by the extant psycholinguistic or cognitive neuroscience evidence.
8. Conclusion A revolution is occurring in cognitive science. Researchers are beginning to recognize that the orthodox distinction between perception and conception is no longer tenable. Part of the reason for this revolution is an emerging body of evidence that suggests that some semantic information is perceptually encoded. A question that remains is whether or not any semantic information is encoded by amodal representations. In this essay, I have defended a form of representational pluralism that posits perceptual and amodal semantic codes. This defense has negative and positive aspects. On the negative side, I have argued that the empirical evidence cited in support of perceptual symbols is fundamentally circumscribed. It is compelling with respect to concrete or highly imageable concepts but has limited reach with respect to abstract concepts. I have also argued that the general arguments offered in support of perceptual symbols are unconvincing. Neither the argument from parsimony nor the argument from intentionality provides compelling support for the view that our concepts are generally grounded in perception. On the positive side, I have argued that theoretical considerations and a growing body of empirical evidence suggest that amodal symbols are used to represent aspects of abstract concepts. Research on number approximation and imageability strongly suggest that amodal symbols play an important role in some of our concepts. Acknowledgements I have benefited greatly from discussions with Murat Aydede, Cara Cashon, Julia Chariker, Mandy Maguire, John Pani, and Jesse Prinz. A section of this paper was presented at the 33rd annual meeting of the Society for Philosophy and Psychology, Toronto, 2007, and I am grateful for the questions and suggestions provided by participants. I also thank Larry Barsalou, Arthur Glenberg, and an anonymous reviewer for their helpful comments on previous versions of this paper. References Adams, F., & Campbell, K. (1999). Modality and abstract concepts. Behavioral and Brain Sciences, 22, 610.
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