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Semantic knowledge is a type of long-term memory, commonly referred to as semantic memory, consisting of concepts, facts, ideas, and beliefs (e.g., Tulving 1983). Semantic memory is thus distinct from episodic or autobiographical memories, which are unique to an individual and tied to a speciﬁc time and place. For example, answering the question ‘What does the word breakfast mean?’ requires semantic memory. In contrast, answering the question ‘What did you have for breakfast yesterday?’ requires episodic memory, to retrieve information about events in our personal past, as well as semantic memory, to understand the question. Semantic memory therefore includes the information stored in our brains that represents the meaning of words and objects.
Understanding the nature of meaning, however, has proven to be a fairly intractable problem: especially regarding the meaning of words. One important reason why this is so is that words have multiple meanings. The speciﬁc meaning of a word is determined by context, and comprehension is possible because we have contextual representations (see Miller 1999 for a discussion of lexical semantics and context). Cognitive neuroscientists have begun to get traction on the problem of meaning in the brain by limiting inquiry to concrete objects as represented by pictures, and by their names.
Consider, for example, the most common meaning of two concrete objects; a camel and a wrench. Camel is deﬁned as ‘either of two species of large, domesticated ruminants (genus camelus) with a humped back, long neck, and large cushioned feet,’ the object wrench is deﬁned as ‘any number of tools used for holding and turning nuts, bolts, pipes, etc.’ (Webster’s New World Dictionary 1988). Two things are noteworthy about these deﬁnitions. First, they are largely about features; camels are large and have a humped back; wrenches hold and turn things. Second, diﬀerent types of features are emphasized for diﬀerent types of object. The deﬁnition of the camel consists of information about its visual appearance, whereas the deﬁnition of the wrench emphasizes how it is used. Diﬀerences in the types of feature that deﬁne diﬀerent objects have played, and continue to play, a central role in models of how semantic knowledge is organized in the human brain.
Another point about these brief deﬁnitions is that they include only part, and perhaps only a small part, of the information we may possess about these objects. For example, we may know that camels are found primarily in Asia and Africa, that they are known as the ‘ships of the desert,’ and that the word camel can also refer to a color and a brand of cigarettes. Similarly, we also know that camels are larger than a bread box and weigh less than a 747 jumbo jet. Although this information is also part of semantic memory, little is known about the brain bases of these associative and inferential processes. Neuroscientists are, however, beginning to gain insights into the functional neuroanatomy associated with identifying objects and retrieving information about speciﬁc object features and attributes.
1. Semantic Representations
A central question for investigators interested in the functional neuroanatomy of semantic memory has been to determine how information about object concepts is represented in the brain. A particularly inﬂuential idea guiding much of this work is that the features and attributes that deﬁne an object are stored in the perceptual and motor systems active when we ﬁrst learned about that object. For example, information about the visual form of an object, its typical color, its unique pattern of motion, would be stored in or near regions of the visual system that mediate perception of form, color, and motion. Similarly, knowledge about the sequences of motor movements associated with the use of an object would be stored in or near the motor systems active when that object was used. This idea has a long history in behavioral neurology. Indeed, many neurologists at the beginning of the twentieth century assumed that the concept of an object was composed of the information about that object learned through direct sensory experience and stored in or near sensory and motor cortices (e.g., Lissauer 1988, 1890).
2. Semantic Deﬁcits Result From Damage To The Left Temporal Lobe
The modern era of study on the organization of semantic knowledge in the human brain began with Elizabeth Warrington’s seminal paper ‘The selective impairment of semantic memory’ (Warrington 1975). Warrington reported three patients with progressive dementing disorders that provided neurological evidence for a semantic memory system. There were three main components to the disorder. First, it was selective. The disorder could not be accounted for by general intellectual impairment, sensory or perceptual problems, or an expressive language disorder. Second, the disorder was global, in the sense that it was neither materialnor modality-speciﬁc. Object knowledge was impaired regardless of whether objects were represented by pictures or their written or spoken names. Third, the disorder was graded. Knowledge of speciﬁc object attributes (e.g., does a camel have two, four, or six legs?) was more impaired than knowledge of superordinate category information (i.e., is a camel a mammal, bird, or insect?).
Following Warrington’s report, similar patterns of semantic memory dysfunction have been reported in patients with brain damage resulting from a wide range of etiologies. These have included patients with progressive dementias such as Alzheimer’s disease and semantic dementia, herpes encephalitis, and closed head injury (for review, see Patterson and Hodges 1995). Consistent with the properties established by Warrington, these patients typically had marked diﬃculty producing object names under a variety of circumstances, including naming pictures of objects, naming from the written descriptions of objects, and generating lists of objects that belong to a speciﬁc category (e.g., animals, fruits and vegetables, furniture, etc.). In addition, the deﬁcits were associated primarily with damage to the left temporal lobe, suggesting that information about object concepts may be stored, at least in part, in this region of the brain.
3. Brain Damage Can Lead To Category-Speciﬁc Semantic Deﬁcits
Other patients have been described with relatively selective deﬁcits in recognizing, naming, and retrieving information about diﬀerent object categories. The categories that have attracted the most attention are animals and tools. This is because of a large and growing number of reports of patients with greater diﬃculty naming and retrieving information about animals (and often other living things) than about tools (and often other man-made objects). Reports of the opposite pattern of dissociation (greater for tools than animals) are less frequent. However, enough carefully-studied cases have been reported to provide convincing evidence that these categories can be doubly dissociated as a result of brain damage. The impairment in these patients is not limited to visual recognition. Deﬁcits occur when knowledge is probed visually and verbally, and therefore assumed to reﬂect damage to the semantic system or systems (for review, see Forde and Humphreys 1999).
While it is now generally accepted that these disorders are genuine, their explanation, on both the cognitive and neural levels, remains controversial. Two general types of explanation have been proposed. The most common explanation focuses on the disruption of stored information about object features. Speciﬁcally, it has been proposed that knowledge about animals and tools can be disrupted selectively because these categories are dependent on information about diﬀerent types of features stored in diﬀerent regions of the brain. As exempliﬁed by the deﬁnitions provided previously, animals are deﬁned primarily by what they look like, and functional attributes play a much smaller role in their deﬁnition. In contrast, functional information, speciﬁcally how an object is used, is critical for deﬁning tools. As a result, damage to areas where object form information is stored leads to deﬁcits for categories that are overly-dependent on visual form information, whereas damage to regions where object use information is stored leads to deﬁcits for categories overly-dependent on functional information. The ﬁnding that patients with categoryspeciﬁc deﬁcits for animals also have diﬃculties with other visual-form-based categories, such as precious stones, provides additional support for this view (e.g., WarPrington and Shallice 1984).
This general framework for explaining categoryspeciﬁc disorders was ﬁrst proposed by Warrington and colleagues in the mid to late 1980s (e.g., Warrington and Shallice 1984). Inﬂuential extensions and reformulation of this general idea have been provided by a number of investigators, including Farah and McClelland (1991), Damasio (1990), Caramazza et al. (1990), and Humphreys and Riddoch (1987).
The second type of explanation focuses on broader semantic distinctions (e.g., animate v. inanimate objects), rather than on features and attributes, as the key to understanding category-speciﬁc deﬁcits. A variant of this argument has recently been proposed by Caramazza and Shelton (1998) to counter a number of diﬃculties with feature-based formulations. Speciﬁcally, these investigators note that a central prediction of at least some feature-based models is that patients with a category-speciﬁc deﬁcit for animals should have more diﬃculty in answering questions that probe knowledge about visual information about animals (does an elephant have a long tail?), than about function information (is an elephant found in the jungle?). As Caramazza and Shelton (1998) show, at least some patients with an animal-speciﬁc knowledge disorder (and, according to their argument, all genuine cases) have equivalent diﬃculty with both visual and functional questions about animals. As a result of these and other ﬁndings, Caramazza and Shelton argue that category-speciﬁc disorders cannot be explained by feature-based models. Instead, they propose that such disorders reﬂect evolutionary adaptations for animate objects, foods, and perhaps by default, tools, and other manufactured objects (the ‘domain-speciﬁc hypothesis’; Caramazza and Shelton 1998).
4. Functional Brain Imaging Reveals That Semantic Knowledge About Objects Is Distributed In Diﬀerent Regions Of The Brain
Functional brain imaging allows investigators to identify the neural systems active when normal individuals perform diﬀerent types of task. These studies have conﬁrmed ﬁndings with brain damaged subjects, and have begun to extend knowledge of the neural basis of semantic memory. Although functional brain imaging is a relatively new tool, the current evidence suggests that information about diﬀerent object features is stored in diﬀerent regions of the cerebral cortex. One body of evidence in support of this claim comes from experiments using word generations tasks. Subjects are presented with the name of an object, or a picture of an object, and required to generate a word denoting a speciﬁc feature or attribute associated with that object. In one study, positron emission tomography (PET) was used to investigate diﬀerences in patterns of brain activity when subjects generated the name of an action typically associated with an object (e.g., saying the word ‘pull’ in response to a static, achromatic line-drawing of a child’s wagon), relative to generating an associated color word e.g., saying ‘red’ in response to the wagon) (Martin et al. 1995). Relative to generating a color word, action-word generation activated a posterior region of the left temporal lobe, called the middle temporal gyrus. This location was of particular interest because it was just anterior to sites known to be active during motion perception (area MT). In contrast, relative to generating action words, color-word generation activated a region on the ventral, or underside of the temporal lobe, called the fusiform gyrus. This location was of particular interest because it was just anterior to sites known to be active during color perception. Finally, the same pattern of results was found when subjects were presented with the written names of objects, rather than an object picture (Fig. 1) (for review see Martin 2001).
These ﬁndings, and ﬁndings from other studies using a wide range of semantic processing tasks, provide support for two important ideas about the neural representation of semantic knowledge. First, there is a single semantic system in the brain, rather than separate semantic systems for diﬀerent modalities of input (visual, auditory) or types of material (pictures of objects, words) (e.g., Vandeberghe et al. 1996). This system includes multiple brain regions, especially in the temporal and frontal lobes of the left hemisphere (for review see Price et al. 1999, Martin 2001). Second, information about object features and attributes are not stored in a single location, but rather are stored as a distributed network of discrete cortical areas. Moreover, the locations of the sites appear to follow a speciﬁc plan that parallels the organization of sensory systems, and, as will be reviewed below, motor systems, as well.
5. Ventral Occipitotemporal Cortex And The Representation Of Object Form
Another body of evidence that object concepts may be represented by distributed feature networks comes from studies contrasting patterns of neural activity associated with naming, and performing other types of tasks with objects from diﬀerent categories. A feature common to all concrete objects is that they have physical shape or form. Evidence is accumulating that suggests that many object categories elicit distinct patterns of neural activity in regions involved in object form processing (ventral occipital and temporal cortex). Moreover, the locations of these category-related activations appear to be consistent across individual subjects and processing tasks (e.g., naming object pictures, matching pictures, reading object names). This seems to be especially so for objects deﬁned primarily by visual form-related features such as animals, faces, and landmarks.
Early reports using PET found that naming (Martin et al. 1996) and matching (Perani et al. 1995) pictures of animals resulted in greater activation of the left occipital cortex than performing these same tasks with pictures of tools. Because the occipital cortex is involved primarily in the early stages of visual processing, it was suggested that this activity reﬂected top-down activation from more anterior sites in the occipitotemporal object processing stream (Martin et al. 1996). This may occur whenever detailed information about visual features or form is needed to identify an object. Speciﬁcally, naming objects that diﬀer from other members of the same category by relatively subtle diﬀerences in visual form (four-legged animals) may require access to stored information about visual detail. Retrieving this information, in turn, may require participation of early visual processing areasn the occipital cortex. A subsequent report showing that unilateral occipital lesions could result in greater diﬃculty in naming and retrieving information about animals than tools provided converging evidence for this view (Tranel et al. 1997).
However, most patients with semantic deﬁcits for animals have had lesions conﬁned to the temporal lobes (for review, see Gainotti et al. 1995). Functional brain imaging of normal individuals has now provided evidence for category-related activations in the ventral region of the temporal lobes. This has been accomplished by using functional magnetic resonance imaging (fMRI), which provides better spatial resolution than was possible using PET.
A number of investigators have found that distinct regions of the ventral temporal cortex show diﬀerential responses to diﬀerent object categories. In one study, viewing, naming, and matching pictures of animals, as well as answering written questions about animals, were found to activate the lateral region of the fusiform gyrus, relative to performing these tasks with pictures and names of tools. In contrast, the medial fusiform was more active for tools than animals. A similar, but not identical, pattern of activation was found for viewing faces (lateral fusiform) relative to viewing houses (medial fusiform) (Chao et al. 1999). Other investigators have also reported face-related activity in the lateral region of the fusiform gyrus, and houserelated activity in more medial regions of the ventral temporal lobe, including the fusiform, lingual, and parahippocampal gyrus (Fig. 2) (for review, see Kanwisher et al. 2001, Martin 2001).
These ﬁndings suggest that diﬀerent object categories elicit activity in diﬀerent regions of ventral temporal cortex, as deﬁned by the location of their peak activation. Moreover, the typological arrangement of these peaks was consistent across subjects and tasks. Importantly, however, the activity associated with each object category was not limited to a speciﬁc region of the ventral occipitotemporal cortex, but rather was distributed over much of the region (Chao et al. 1999).
Additional evidence for the distributed nature of object representations in the ventral temporal cortex comes from single cell recordings from intracranial depth electrodes implanted in epileptic patients (Kreiman et al. 2000a). Recordings from the regions of the medial temporal cortex (entorhinal cortex, hippocampus, and amygdala), which receive major inputs from the ventral temporal regions described above, identiﬁed neurons that showed highly selective responses to diﬀerent object categories, including animals, faces, and houses. Moreover, the responses of the neurons were category-speciﬁc rather than stimulus-speciﬁc. That is, animal-responsive cells responded to all pictures of animals, rather than to one picture or a select few.
Studies reporting similar patterns of neural activity when subjects view and imagine objects provide further support that object information is stored in these regions of cortex. For example, regions active during face perception are also active when subjects imagine famous individuals (O’Craven and Kanwisher 2000). Similar ﬁndings have been reported for viewing and imagining known landmarks (O’Craven and Kanwisher 2000), houses, and even chairs (Ishai et al. 2000). In addition, the majority of category-selective neurons recorded from human temporal cortex also responded selectively when the patients were asked to imagine these objects (Kreiman et al. 2000b).
Taken together, the data suggest that the ventral occipitotemporal cortex may be best viewed, not as a mosaic of discrete category-speciﬁc areas, but rather as a lumpy feature-space, representing stored information about features of object form shared by members of a category. How this feature space is organized, and why its topological arrangement is so consistent from one subject to another, are critical questions for future investigations.
6. Lateral Temporal Cortex And The Representation Of Object Motion
Information about how objects move through space, and patterns of motor movements associated with their use, are other features that could aid object identiﬁcation. This would be especially true for categories of manufactured objects such as tools that have a more variable mapping between their name and their visual form than a category such as four-legged animals. Thus access to these additional features may be required to identify them as unique entities. Here again, evidence is accumulating that naming and identifying objects with motion-related attributes activate areas close to regions that mediate perception of object motion (posterior region of the lateral temporal lobe) with diﬀerent patterns of activity associated with biological and manufactured objects.
A number of laboratories using a variety of paradigms with pictures and words have reported that tools elicit greater activity in the posterior, left middle temporal gyrus than animals and other object categories (for review, see Martin 2001). Moreover, the active region was just anterior to area MT, and overlapped with the region active in the verb generation studies discussed above. Damage to this region has been reported selectively to impair tool recognition and naming (Tranel et al. 1997). In contrast, naming animals and viewing faces elicits greater activity in the superior temporal sulcus (STS) (Fig. 2). This region is of particular interest because of its association with the perception of biological motion in monkeys as well as humans (for review, see Allison et al. 2000). As suggested for the ventral temporal cortex, neurons in the lateral temporal cortex may also be tuned to features that objects within a category share. The nature of these features is unknown; however, based on its anatomical proximity to visual motion processing areas, this region may be tuned to features of motion associated with diﬀerent objects. In support of this conjecture, increased activity in the posterior lateral temporal cortex has been found when subjects viewed static pictures of objects that imply motion (Kourtzi and Kanwisher 2000, Senior et al. 2000), and when subjects focused attention on the direction of eye gaze (Hoﬀman and Haxby 2000). Investigation of the diﬀerences in the properties of motion associated with biological and manufactured objects may provide clues to the organization of this region.
7. Ventral Premotor Cortex And The Representation Of Use-Associated Motor Movements
If activations associated with diﬀerent object categories reﬂect stored information about object properties, then one would expect tools to elicit activity in motor-related regions. Several laboratories have reported this association. Speciﬁcally, greater activation of the left ventral premotor cortex has been found for naming tools relative to naming animals, viewing pictures of tools relative to viewing pictures of animals, faces, and houses, and generating action words to tools (Fig. 2). Mental imagery (e.g., imagining manipulating objects with the right hand) has also resulted in ventral premotor activation (Fig. 2) (for review, see Martin 2001).
Electrophysiological studies have identiﬁed cells in monkey ventral premotor cortex that responded not only when objects were grasped, but also when the animals viewed objects they had had experience of manipulating (Jeannerod et al. 1995). The ventral premotor activation noted in the human neuroimaging studies may reﬂect a similar process. These ﬁndings are consistent with reports of patients with greater diﬃculty in naming tools than animals following damage to the left lateral frontal cortex (for review, see Gainotti et al, 1995) and suggest that the left ventral premotor cortex may be necessary for naming and retrieving information about tools.
8. Conclusions And Future Directions
Evidence from functional brain imaging studies provides considerable support for feature-based models of semantic representation. However, some of the ﬁndings could be interpreted as evidence for the ‘domainspeciﬁc’ hypothesis as well. For example, the clustering of activations associated with animals and faces, on the one hand, and tools and houses, on the other, may be viewed as consistent with this interpretation. Other evidence suggests, however, that all nonbiological object representations do not cluster together. For example, it has been reported that activity associated with a category of objects of no evolutionary signiﬁcance (chairs) was located lateral to the face-responsive region (in the inferior temporal gyrus), rather than medially where tools and houses elicit their strongest activity (Ishai et al. 1999). Both functional brain imaging and patient studies suggest that object knowledge is represented in distributed cortical networks. There do not seem to be single regions that map on to whole object categories. Nevertheless, there may be a broader organization of these networks that reﬂects evolutionarily adapted, domain-speciﬁc knowledge systems for biological and nonbiological kinds of object. This possibility remains to be explored.
Although progress is being made in understanding the neural substrate of some aspects of meaning, many important questions and issues remain. For example, semantic representations are prelexical. Yet, to be of service, they must be linked intimately to the lexicon. Little is known about how the lexicon is organized in the brain, and how lexical and semantic networks interact (Damasio et al. 1996).
Another important issue concerns the neural basis of retrieval from semantic memory. Semantic knowledge, like all stored information, is not useful unless it can be retrieved eﬃciently. Studies of patients with focal lesions have shown that the left lateral prefrontal cortex is involved critically in word retrieval, even in the absence of a frank aphasia (e.g., Baldo and Shimamura 1998). Functional brain imaging studies have conﬁrmed this association (Fig. 2). Moreover, recent evidence suggests that diﬀerent regions of the left inferior prefrontal cortex may mediate selection among competing alternatives in semantic memory, whereas other regions may be involved in retrieving, manipulating, and maintaining semantic information in working memory (for review, see Martin and Chao 2001). Much additional work will be needed to describe the role that diﬀerent regions of prefrontal cortex play in semantic processing.
Another critical question will be to determine how semantic object representations are modiﬁed by experience. Some of the ﬁndings discussed here suggest that the typological arrangement among object categories in the cortex is relatively ﬁxed. Other evidence suggests a much more ﬂexible organization, in which the development of expertise with an object category involves a particular portion of the fusiform gyrus (Gauthier et al. 1999). Longitudinal studies tracking changes in the brain associated with learning about completely novel objects should help to clarify this issue.
There is also little known about where object information unrelated to sensory or motor properties is stored (e.g., that camels live in Asia and Africa). Similarly, little is known about the representation of abstract concepts (e.g., honor, liberty, and justice), metaphors, and the like.
Finally, questions concerning the neural systems involved in object category formation have been almost totally neglected. E. E. Smith and colleagues have shown that exemplar-based and rule-based categorization activate diﬀerent neural structures (Smith et al. 1999). This ﬁnding suggests that categorization processes may be a fruitful area for future investigation. The advent of techniques to converge fMRI data with technologies such as magneto encephalography (MEG) that provide temporal information on the order of milliseconds, should provide a wealth of new information on the neural basis of semantic knowledge.
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