Knowing This from That : Brain Response to Objects and Events

Neuroscientific methods have become an increasingly important influence on the study of cognitive processing. In this chapter we look at how the study of patient populations in addition to neuroimaging techniques have been used to address basic questions about category knowledge. How does the brain represent category knowledge? What information is acquired during category learning? Why do people parse action streams into discrete events? In this chapter we look at how neuroscience has shaped the way we ask and answer questions about category learning and representation. There may not be agreement about the answers, but neuroscience has helped to make the questions interesting. Introduction Whether we are recognizing a friend or making a cup of coffee, the seemingly effortless and instantaneous ability to transform sensory information into meaningful concepts determines the success with which we interact with the world. However, the seeming ease with which we engage common concepts belies the complexity of the underlying brain processing that makes categorization possible. At what point in the processing of sensory information is the category decision made? Work with nonhuman subjects suggests that categorization may be traced to individual neurons. In their seminal work, Hubel and Wiesel (1962) implanted electrodes into the visual cortex of cats and found that some neurons would respond to certain types of visual input and not to others. That is, neurons in the visual cortex of the cat appeared to be dedicated, like cells in the retina of the eye, to specific types of visual input. However, unlike the retinal cells, the neurons of the visual cortex responded to more complex patterns involving shape and orientation. Based on their observations, Hubel and Wiesel argued that neurons in the visual cortex were hierarchically organized into simple and complex cells in which the complex cells were constructed from more elementary ones. The view of visual cortex as hierarchically organized was formalized by Barlow (1972) in a paper outlining the tenets of a neuron doctrine of perception, a model of perception at the neural level that has dominated neuroscience studies of perception to this day. The underlying premise of the neuron doctrine is that neurons at higher brain areas are assumed to become more selective so that “the overall direction or aim of information processing in higher sensory centres is to represent the input as completely as possible by activity in as few neurons as possible” (p. 382). Thus, as information is propagated through the system, neurons are assumed to respond to progressively more complex and invariant features. Accordingly, it should be possible to identify neurons specialized for particular objects, for example, faces. One of the first studies to demonstrate face responsive cells was conducted with Macaque monkeys (Gross, et al., 1972). Recording activity of single neurons in response to visual stimulation, Gross et al. found individual cells that responded maximally to face stimuli and even a neuron that responded maximally to a monkey hand. These specialized cells were found in the inferior temporal cortex of the monkey which is thought to correspond, in humans, to the medial temporal lobe (MTL). Later in this chapter we will discuss the data from human research that suggests the presence of face specific brain response and its implications for category processing. One major criticism of the neuron doctrine is that large parts of the brain can be damaged without correspondingly large changes in behavior (Lashley, 1929). This property of the brain known as cerebral mass action and a second principle, equipotentiality (the ability of a brain area to take on the function of a damaged area), suggest that brain function is not localized. Rather, these principles suggest that brain function is distributed across neuronal populations that are clustered into networks and circuits and are recruited opportunistically as various perceptual and cognitive tasks arise. This debate between proponents of localized and distributed processing has become particularly salient in the neuroscience literature related to categorization. As we shall see, support for both sides has been collected, although recent efforts seem to favor a distributed representation of category information over ones positing localized representation. The goal of this chapter, however, is not to argue for one view over the other, but rather to present representative research using neuroscientific techniques to study categorization. One neuroscientific approach that has been used sucessfully relies on the study of patient populations. Researchers have long been interested in neurological impairments because of what they could reveal about normal cognition. Knowing that certain lesions in specific brain areas leads to fairly predictable cognitive deficits provides the means of linking brain function to cognitive function. If a lesion in a given brain area produces a language deficit, it is highly likely that that area is important to normal language processing. Moreover, if that lesion does not affect other cognitive processes, it reveals something about the independence of cognitive functions. Over the past 10 to 15 years, interest in brain function and its relation to cognitive function has led to a dramatic increase in the use of tools and techniques such as ERP, PET, MEG, and fMRI that had long been the exclusive domain of medical practitioners. By adopting the tools of neuroscience, cognitive psychologists are now able to directly (or as directly as feasible) observe the brain as it works on various cognitive tasks. Although the methodologies associated with neuroscience are not without pitfalls (see Gabrieli, 1998 for a discussion), cognitive neuroscientists have come very close to looking inside the black box. The focus of this chapter is on the work that has applied the techniques of cognitive neuroscience to the study of category processing. Specifically, we will look at what studies using a neuroscience approach have contributed to the understanding of how categories are learned and represented. The review of work using neuroscience to study categorization is not meant to be exhaustive, but rather to provide some examples of how neuroscientific approaches have contributed to our understanding about the processing of category knowledge. This chapter looks at how category knowledge is processed in the brain. Our discussion focuses on two types of knowledge about the world; namely, objects and actions. The majority of work on categorization concerns how objects categories are represented and learned and we devote the first part of this chapter to research on object categorization. A large component of human experience, however, involves the interpretation and representation of action and we look at how the brain processes realworld events such as going to the theater or having dinner. Finally, we offer some suggestions about the future work. Representing Object Categories in the Brain The cognitive neuroscientific approaches to category representation can be divided roughly into two camps. In one camp are those researchers who believe that there exist category-specific structures in the brain (e.g., Kanwisher, McDermott, & Chun, 1997). In the other camp are those who believe that category knowledge is based on distributed feature topologies (e.g., Haxby et al., 2000). A different approach is taken by Gauthier (2000) who sees brain structures as being linked to how category information is processed rather than to any specific category content. In the following pages we will review what each of these positions has contributed to our understanding of how categories are represented in the brain. Category-specific Representation One way in which the brain may represent categories is to dedicate a set of neurons to the task. That is, the brain could allocate particular areas to individual categories so that whenever a category exemplar was encountered the dedicated area would be activated. Moreover, areas dedicated to a particular category would be unresponsive when exemplars of a different category were encountered. Thus, the brain area that responded to category A would not respond to category B and vice versa. Moreover, if category information was selectively represented in particular brain structures, damage to those structures should disrupt knowledge associated with those categories. Category-specific disorder, a disorder in which patients demonstrate a selective dysfunction in retrieving category exemplars or features, has been associated with brain damage resulting from a wide range of etiologies including herpes encephalitis, brain abscess, anoxia, stroke, head injury, or dementia of Alzheimer type (DAT). The most common form of category-specific disorder involves animate objects, inanimate biological objects, and artifacts (Capitani, Laiacona, Mahon, & Caramazza, 2003). Figure 1. Human brain with important cortical areas labeled Category-specific disorder often affects one type of category while sparing another. Much of the extant work in this area has found that a patient suffering from category-specific disorder will have difficulty with either the category of animate objects or the category of artifacts. Rarely does a patient have difficulty with both categories. Research with patients has found that damage to areas in the infero-temporal cortex, the mesial temporo-limbic structures, and the temporal pole (Gainotti, 2000) disrupts access to knowledge about living things. In contrast, knowledge about artifacts seems to be most often associated with damage in fronto-parietal areas (Gainotti, et al., 1995; Saffran and Schwartz, 1994) and in posterior left middle temporal gyrus (Martin and Chao, 2001; Phillips et al., 2002). See Figure 1 for a picture of a brain labeled with areas of interest. Functional neuroimaging work