Conceptual Combination

Much has been learned about how individual concepts and semantic dimensions are represented in the human brain using methods from the field of cognitive neuroscience; however, the process of conceptual combination, in which a new concept is created from preexisting concepts, has received far less attention. We discuss theories and findings from cognitive science and cognitive neuroscience that shed light on the processing stages and neural systems that allow humans to form new conceptual combinations. We review systematic and creative applications of cognitive neuroscience methods, including neuroimaging, neuropsychological patients, neurostimulation, and behavioral studies, that have yielded fascinating insights into the cognitive nature and neural underpinnings of conceptual combination. Studies have revealed important features of the cognitive processes central to successful conceptual combination. Furthermore, we are beginning to understand how regions of the semantic system, such as the anterior temporal lobe and angular gyrus, integrate features and concepts, and how they evaluate the plausibility of potential resulting combinations, bridging work in linguistics and semantic memory. Despite the relative newness of these questions for cognitive neuroscience, the investigations we review give a very strong foundation for ongoing and future work that seeks to fully understand how the human brain can flexibly integrate existing concepts to form new and never before experienced combinations at will. Conceptual Combination Our ability to construct complex concepts from simpler constituents, referred to as conceptual combination, is fundamental to many aspects of cognition. One can, often effortlessly, comprehend a novel utterance, event, or idea via the manipulation, integration, or synthesis of other simpler or more familiar concepts; for example, upon hearing a news report that as a result of climate change the Pacific Northwest robin hawk is under threat of extinction, you might construct one of several plausible interpretations of the meaning of robin hawk (see figure 71.1). In order to understand such novel concepts, one must recruit a series of cognitive processes that might include identifying combinable features of the attributing and receiving concepts; selecting which of these features are to be transferred between concepts; integrating the selected features into a unitary conceptual representation; and confirming the plausibility of the resulting concept. Methods of cognitive neuroscience can be deployed to investigate the neural signatures for combined concepts and the subprocesses that create them in order to understand conceptual combination more broadly. Investigating how individuals combine concepts can shed unique light on different aspects of conceptual knowledge, including the cognitive mechanisms that enable the generative and flexible use of language. Figure 71.1 Two plausible interpretations of the novel concept robin hawk. Top, A hawk with the red breast of a robin. Bottom, A hawk that preys on robins. One might protest that it is premature to attempt to explain the processes by which simple or familiar concepts are combined to form complex or new concepts, and the representations of the resulting combined concepts, prior to having a more developed understanding of the cognitive and neural architecture of their building blocks. Several of the other chapters in this volume describe the progress—and also the many, many open questions that remain—in our quest to understand the representation of concepts and the processes by which they are learned, stored, and retrieved. Why would one embark on a quest to understand how concepts are combined before we better understand the seemingly more fundamental questions about conceptual representation? We suggest that questions that arise when considering the processes and resulting representations of conceptual combination may help shed light on—or at least, suggest lines of fruitful inquiry into—more basic questions of conceptual representation. For example, what conceptual structures are flexible enough to allow for the decomposition and recomposition of features into novel combinations? In addition, some of the processes that govern the integration of simple concepts (such as finger and lime) into complex concepts (such as a finger lime) might also govern how simple sensory features (such as round, tart, and green) are integrated into so-called simple concepts (such as lime). In other words, combination occurs at multiple levels of semantic processing, even for so-called simple concepts. As such, we can potentially advance our understanding of conceptual processing of all sorts by asking questions about how concepts are combined. That is our undertaking in this chapter: How do we construct meaning out of ideas represented in, for example, noun-noun phrases such as robin hawk? What neural systems are recruited as we understand these newly combined concepts? We view these questions as critical to understanding not only one of the most fundamental and generative aspects of cognition but also basic questions about conceptual systems. One note before we begin: Familiar phrases that are now treated as “simple concepts,” such as doorstop or straightjacket, were at one time novel combinations of existing concepts. As certain conceptual combinations fall into common use, they can become integrated into language as unitary lexical entities (compound words). When examining the process of conceptual combination, we will not consider these established phrases, which might be treated as a singular word after repeated use. Indeed, some investigations explicitly regress out the natural frequency of combinations to ensure that any identified neural substrate is not driven by the familiarity of a compound word or phrase (e.g., Graves, Binder, Desai, Conant, & Seidenberg, 2010). This is not to say that once a combination becomes familiar, it ceases to act in a combinatorial manner. Though familiar and novel combinations differ in their lexical retrieval, their respective patterns of response times suggest that both undergo similar computations (Estes & Jones, 2008; Gagné & Spalding, 2004). But we have found that studies of novel combinations provide a unique opportunity to explore critical questions about conceptual processing, and for this reason these studies are the focus of this chapter. The Structure of Conceptual Combinations The two interpretations of robin hawk depicted in figure 71.1 illustrate a potentially useful distinction: certain conceptual combinations (canary crayon) are feature-based (or attributive), which are understood by selecting a property from a modifier noun (yellow from canary), mapping this onto a dimension of the head noun (the color of a crayon), and then integrating them to form the combined concept (a yellow crayon). Schema-based theories of conceptual structure frame this process in terms of each concept containing a set of different dimensions into which alternative properties can be placed (in this case, through a modifier noun; e.g., Murphy, 1988). Comprehending a combined concept involves understanding the transference of a correct property into the other concept’s appropriate dimension. Other conceptual combinations (crayon box) are relational. For these combinations, understanding the relation between items (e.g., containment) is crucial and allows a person to understand that a crayon box is a box that contains crayons. The precise relationship between attributive and relational combinatorial processing has been a topic of debate in the field of cognitive science (e.g., Estes, 2003; Gagné & Shoben, 1997). One contribution of cognitive neuroscience has been to shed new light on questions such as this (e.g., Boylan, Trueswell, & Thompson-Schill, 2017, discussed later in this chapter). A large variety of relations can exist between constituent concepts, and the precise relation between two concepts is extremely significant. Bird nest involves one concept (bird) inhabiting another (nest); flower girl involves the temporary possession of an object (flower) by an agent (girl). Work in this area shows that we represent the relation between concepts in a relatively precise way. Concept combinations with particular combinatorial relationships can prime other concept compounds that are represented in the same way (e.g., bird nest primes fish pond; Estes, 2003; Estes & Jones, 2006; Gagné, 2001). Yet the priming combinations can be remarkably specific. For example, bird nest does not prime toy box (Estes & Jones, 2006). Though the relationships involved in bird nest and toy box are superficially similar, the presence of a potential common relation (such as containment) is not sufficient to induce priming. Instead, bird nest is more accurately characterized by the relationship of habitation, allowing it to prime fish pond but not toy box. This example illustrates the broader idea that conceptual combinations are represented as very particular interactions between composing concepts. The identification of these precise interactions often requires the empirical study of behavioral responses in carefully designed tasks. Cognitive Processes in Conceptual Combination The cognitive process of combining concepts appears to be automatic and implicit, without requiring top-down instruction. This is well illustrated by behavioral priming, in which a person’s behavioral response speeds up after perceiving two items that share a particular stimulus characteristic in quick succession. The presence of a priming effect based on a particular stimulus dimension informs theories of cognitive and neural architecture (Churchland, 1998); for example, priming based on word phonology or meaning indicates an organization of language and memory systems that reflects those characteristics. A priming effect has also been identified based on the compatibility of two c