Skip to main content Accessibility help
×
Hostname: page-component-78c5997874-fbnjt Total loading time: 0 Render date: 2024-11-10T15:23:40.136Z Has data issue: false hasContentIssue false

6 - Effects of word imageability on semantic access: neuroimaging studies

from Part IV - Representations of Nouns and Verbs vs. Objects and Actions

Published online by Cambridge University Press:  14 September 2009

Jeffrey R. Binder
Affiliation:
Medical College of Wisconsin
John Hart
Affiliation:
University of Texas, Dallas
Michael A. Kraut
Affiliation:
The Johns Hopkins University School of Medicine
Get access

Summary

The axiom that conceptual knowledge is grounded in perceptual experience has a long history in philosophy (Locke, 1690/1959; Hume, 1739/1975) and clinical neurology (Wernicke, 1874; Freud, 1891/1953; Geschwind, 1965), and has had considerable influence on modern neuroscience (e.g. Paivio, 1971; Allport, 1985; Damasio, 1989; Barsalou, 1999; Pulvermüller, 1999; Glenberg & Robertson, 2000; Martin et al., 2000). This principle has been applied conspicuously, for example, in accounts of category-related knowledge deficits that postulate selective damage to modality-specific perceptual knowledge stores. Living things tend to have many salient, defining visual features, making access to these concepts highly reliant on knowledge about visual attributes. Conversely, tools and many other artifact concepts are distinguished on the basis of their functions, which could be partly encoded in motor programs and knowledge of the characteristic motion of artifacts (Warrington & McCarthy, 1987; Farah & McClelland, 1991; Martin et al., 2000). Implicit in this account is the notion that conceptual knowledge is partially stored in perceptual and kinesthetic representations residing in or near the modality-specific sensory–motor systems through which these concrete object concepts were originally learned.

While many neuroimaging studies have tested this theory using comparisons between different types of concrete objects (see Martin & Chao, 2001; Bookheimer, 2002; Devlin et al., 2002; Price & Friston, 2002; Thompson-Schill, 2003; Damasio et al., 2004 for excellent reviews), another testable prediction of the theory involves the qualitative distinction between concrete and abstract concepts.

Type
Chapter
Information
Publisher: Cambridge University Press
Print publication year: 2007

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adler, C. M., Sax, K. W., Holland, S. K., Schmithorst, V., Rosenberg, L., and Strakowski, S. M. (2001). Changes in neuronal activation with increasing attention demand in healthy volunteers: An fMRI study. Synapse, 42: 266–72.CrossRefGoogle Scholar
Allport, D. A. (1985). Distributed memory, modular subsystems and dysphasia. In Newman, S. K. and Epstein, R. (eds.), Current Perspectives in Dysphasia. Edinburgh: Churchill Livingstone, pp. 207–44.Google Scholar
Awh, E., Jonides, J., Smith, E. E., Schumacher, E. H., Koeppe, R. A., and Katz, S. (1996). Dissociation of storage and rehearsal in verbal working memory: evidence from positron emission tomography. Psychological Science, 7: 25–31.CrossRefGoogle Scholar
Badgaiyan, R. D. and Posner, M. I. (1998). Mapping the cingulate cortex in response selection and monitoring. Neuroimage, 7: 255–60.CrossRefGoogle Scholar
Balota, D. A. and Chumbley, J. I. (1984). Are lexical decisions a good measure of lexical access? The role of word frequency in the neglected decision stage. Journal of Experimental Psychology: Human Perception and Performance, 10: 340–57.Google ScholarPubMed
Balota, D. A., Cortese, M. J., Sergent-Marshall, S. D., Spiele, D. H., and Yap, M. J. (2004). Visual word recognition of single-syllable words. Journal of Experimental Psychology: General, 133: 283–316.CrossRefGoogle ScholarPubMed
Barde, L. H. F. and Thompson-Schill, S. L. (2002). Models of functional organization of lateral prefrontal cortex in verbal working memory: Evidence in favor of the process model. Journal of Cognitive Neuroscience, 14: 1054–63.CrossRefGoogle ScholarPubMed
Barsalou, L. W. (1999). Perceptual symbol systems. Behavioral Brain Science, 22: 577–660.Google ScholarPubMed
Berlin, B., Breedlove, D. E., and Raven, P. H. (1966). Folk taxonomies and biological classification. Science, 154: 273–5.CrossRefGoogle ScholarPubMed
Binder, J. R. and Price, C. J. (2001). Functional imaging of language. In Cabeza, R. and Kingstone, A. (eds.), Handbook of Functional Neuroimaging of Cognition. Cambridge, MA: MIT Press, pp. 187–251.Google Scholar
Binder, J. R., Frost, J. A., Hammeke, T. A., Bellgowan, P. S. F., Rao, S. M., and Cox, R. W. (1999). Conceptual processing during the conscious resting state: a functional MRI study. Journal of Cognitive Neuroscience, 11: 80–93.CrossRefGoogle ScholarPubMed
Binder, J. R., McKiernan, K. A., Parsons, M., Westbury, C. F., Possing, E. T., Kaufman, J. N., and Buchanan, L. (2003). Neural correlates of lexical access during visual word recognition. Journal of Cognitive Neuroscience, 15: 372–93.CrossRefGoogle ScholarPubMed
Binder, J. R., Liebenthal, E., Possing, E. T., Medler, D. A., and Ward, B. D. (2004). Neural correlates of sensory and decision processes in auditory object identification. Nature Neuroscience, 7: 295–301.CrossRefGoogle ScholarPubMed
Binder, J. R., Westbury, C. F., Possing, E. T., McKiernan, K. A., and Medler, D. A. (2005a). Distinct brain systems for processing concrete and abstract concepts. Journal of Cognitive Neuroscience, 17: 905–17.CrossRefGoogle Scholar
Binder, J. R., Medler, D. A., Desai, R., Conant, L. L., and Liebenthal, E. (2005b). Some neurophysiological constraints on models of word naming. Neuroimage, 27: 677–93.CrossRefGoogle Scholar
Bird, H., Franklin, S., and Howard, D. (2001). Age of acquisition and imageability ratings for a large set of words, including verbs and function words. Behavior Research Methods, Instruments, & Computers, 33: 73–9.CrossRefGoogle ScholarPubMed
Bookheimer, S. Y. (2002). Functional MRI of language: new approaches to understanding the cortical organization of semantic processing. Annual Review of Neuroscience, 25: 151–88.CrossRefGoogle ScholarPubMed
Botvinick, M., Nystrom, L. E., Fissel, K., Carter, C. S., and Cohen, J. D. (1999). Conflict monitoring versus selection-for-action in anterior cingulate cortex. Nature, 402: 179–81.CrossRefGoogle ScholarPubMed
Braver, T. S., Barch, D. M., Gray, J. R., Molfese, D. L., and Snyder, A. (2001). Anterior cingulate cortex and response conflict: Effects of frequency, inhibition and errors. Cerebral Cortex, 11: 825–36.CrossRefGoogle ScholarPubMed
Breedin, S. D., Saffran, E. M., and Coslett, H. B. (1995). Reversal of a concreteness effect in a patient with semantic dementia. Cognitive Neuropsychology, 11: 617–60.CrossRefGoogle Scholar
Brown, G. D. and Watson, F. L. (1987). First in, first out: word learning age and spoken frequency as predictors of word familiarity and word naming latency. Memory and Cognition, 15: 208–16.CrossRefGoogle ScholarPubMed
Cappa, S. F., Perani, D., Schnur, T., Tettamanti, M., and Fazio, F. (1998). The effects of semantic category and knowledge type on lexical–semantic access: A PET study. Neuroimage, 8: 350–9.CrossRefGoogle ScholarPubMed
Caramazza, A. and Shelton, J. R. (1998). Domain-specific knowledge systems in the brain: the animate–inanimate distinction. Journal of Cognitive Neuroscience, 10: 1–34.CrossRefGoogle ScholarPubMed
Carello, C., Turvey, M. T., and Lukatela, G. (1992). Can theories of word recognition remain stubbornly nonphonological? In Frost, R. and Katz, L. (eds.), Orthography, Phonology, Morphology, and Meaning: Advances in psychology. Amsterdam: North-Holland, pp. 211–26.Google Scholar
Carter, C. S., Braver, T. S., Barch, D. M., Botvinick, M. M., Noll, D., and Cohen, J. D. (1998). Anterior cingulate cortex, error detection, and the online monitoring of performance. Science, 280: 747–9.CrossRefGoogle Scholar
Chao, L. L. and Martin, A. (1999). Cortical regions associated with perceiving, naming, and knowing about colors. Journal of Cognitive Neuroscience, 11: 25–35.CrossRefGoogle ScholarPubMed
Chao, L. L., Haxby, J. V., and Martin, A. (1999). Attribute-based neural substrates in temporal cortex for perceiving and knowing about objects. Nature Neuroscience, 2: 913–19.CrossRefGoogle ScholarPubMed
Chiarello, C., Senehi, J., and Nuding, S. (1987). Semantic priming with abstract and concrete words: differential asymmetry may be postlexical. Brain and Language, 31: 302–14.CrossRefGoogle ScholarPubMed
Coltheart, M., Patterson, K., and Marshall, J. (1980). Deep Dyslexia. London: Routledge & Kegan Paul.Google Scholar
Coltheart, M., Curtis, B., Atkins, P., and Haller, M. (1993). Models of reading aloud: dual-route and parallel-distributed-processing approaches. Psychological Review, 100: 589–608.CrossRefGoogle Scholar
Coltheart, M., Rastle, K., Perry, C., Langdon, R., and Ziegle, J. (2001). DRC: a dual route cascaded model of visual word recognition and reading aloud. Psychological Review, 108: 204–56.CrossRefGoogle ScholarPubMed
Coltheart, V., Laxon, V. J., and Keating, C. (1988). Effects of word imageability and age of acquisition on children's reading. British Journal of Psychology, 79: 1–12.CrossRefGoogle Scholar
Corbetta, M. and Shulman, G. L. (2002). Control of goal-directed and stimulus-driven attention in the brain. Nature Review Neuroscience, 3: 201–15.CrossRefGoogle Scholar
Cortese, M. J. and Fugett, A. (2004). Imageability ratings for 3,000 monosyllabic words. Behavior Research Methods, Instruments, and Computers, 36: 384–7.CrossRefGoogle ScholarPubMed
Coslett, H. B. and Saffran, E. M. (1989). Evidence for preserved reading in “pure alexia”. Brain, 112: 327–59.CrossRefGoogle Scholar
Coslett, H. B. and Monsul, N. (1994). Reading with the right hemisphere: evidence from transcranial magnetic stimulation. Brain and Language, 46: 198–211.CrossRefGoogle ScholarPubMed
Crutch, S. J. and Warrington, E. K. (2005). Abstract and concrete concepts have structurally different representational frameworks. Brain, 128: 615–27.CrossRefGoogle ScholarPubMed
D'Esposito, M., Detre, J. A., Aguirre, G. K., Stallcup, M., Alsop, D. C., Tippet, L. J., and Farah, M. J. (1997). A functional MRI study of mental image generation. Neuropsychologia, 35: 725–30.CrossRefGoogle ScholarPubMed
D'Esposito, M., Postle, B. R., Ballard, D., and Lease, J. (1999). Maintenance versus manipulation of information held in working memory: an event-related fMRI study. Brain and Cognition, 41: 66–86.CrossRefGoogle Scholar
Damasio, A. R. (1989). Time-locked multiregional retroactivation: a systems-level proposal for the neural substrates of recall and recognition. Cognition, 33: 25–62.CrossRefGoogle ScholarPubMed
Damasio, H., Grabowski, T. J., Tranel, D., Hichwa, R. D., and Damasio, A. R. (1996). A neural basis for lexical retrieval. Nature, 380: 499–505.CrossRefGoogle ScholarPubMed
Damasio, H., Tranel, D., Grabowski, T., Adolphs, R., and Damasio, A. (2004). Neural systems behind word and concept retrieval. Cognition, 92: 179–229.CrossRefGoogle ScholarPubMed
Day, J. (1979). Visual half-field word recognition as a function of syntactic class and imageability. Neuropsychologia, 17: 515–19.CrossRefGoogle ScholarPubMed
Dehaene, S., Posner, M. I., and Tucker, D. M. (1994). Localization of a neural system for error detection and compensation. Psychological Science, 5: 303–5.CrossRefGoogle Scholar
Deloche, G., Seron, X., Scius, G., and Segui, J. (1987). Right hemisphere language processing: lateral difference with imageable and nonimageable ambiguous words. Brain and Language, 30: 197–205.CrossRefGoogle ScholarPubMed
Démonet, J.-F., Chollet, F., Ramsay, S., Cardebat, D., Nespoulous, J.-L., Wise, R., Rascol, A., and Frackowiak, R. (1992). The anatomy of phonological and semantic processing in normal subjects. Brain, 115: 1753–68.CrossRefGoogle ScholarPubMed
Devlin, J. T., Russell, R. P., Davis, M. H., Price, C. J., Moss, H. E., Jalal Fadili, M., et al. (2002). Is there an anatomical basis for category-specificity? Semantic memory studies with PET and fMRI. Neuropsychologia, 40: 54–75.CrossRefGoogle ScholarPubMed
Emmorey, K., Grabowski, T., McCullough, S., Damasio, H., Ponto, L. L. B., Hichwa, R. D., and Bellugi, U. (2003). Neural systems underlying lexical retrieval for sign language. Neuropsychologia, 41: 85–95.CrossRefGoogle ScholarPubMed
Falkenstein, M., Hohnsbein, J., Hoormann, J., and Blanke, L. (1991). Effects of crossmodal divided attention on late ERP components: II. Error processing in choice reaction tasks. Electroencephalography and Clinical Neurophysiology, 78: 447–55.CrossRefGoogle ScholarPubMed
Farah, M. J. and McClelland, J. L. (1991). A computational model of semantic memory impairment: Modality specificity and emergent category specificity. Journal of Experimental Psychology General, 120: 339–57.CrossRefGoogle ScholarPubMed
Fiebach, C. J. and Friederici, A. D. (2003). Processing concrete words: fMRI evidence against a specific right-hemisphere involvement. Neuropsychologia, 42: 62–70.CrossRefGoogle Scholar
Fiez, J. A. (1997). Phonology, semantics and the role of the left inferior prefrontal cortex. Human Brain Mapping, 5: 79–83.3.0.CO;2-J>CrossRefGoogle ScholarPubMed
Franklin, S., Howard, D., and Patterson, K. (1995). Abstract word anomia. Cognitive Neuropsychology, 12: 549–66.CrossRefGoogle Scholar
Freud, S. (1891/1953). On Aphasia: A critical study. Madison, NY: International Universities Press.Google Scholar
Friederici, A. D., Opitz, B., and Cramon, D. Y. (2000). Segregating semantic and syntactic aspects of processing in the human brain: an fMRI investigation of different word types. Cerebral Cortex, 10: 698–705.CrossRefGoogle ScholarPubMed
Gehring, W. J., Goss, B., Coles, M. G. H., Meyer, D. E., and Donchin, E. (1993). A neural system for error detection and compensation. Psychological Science, 4: 385–90.CrossRefGoogle Scholar
Gelman, R. (1990). First principles organize attention to and learning about relevant data: number and the animate–inanimate distinction as examples. Cognitive Science, 14: 79–106.CrossRefGoogle Scholar
Gernsbacher, M. A. (1984). Resolving 20 years of inconsistent interactions between lexical familiarity and orthography, concreteness, and polysemy. Journal of Experimental Psychology: General, 113: 256–81.CrossRefGoogle ScholarPubMed
Geschwind, N. (1965). Disconnection syndromes in animals and man. Brain, 88: 237–94, 585–644.CrossRefGoogle Scholar
Gilhooly, K. J. and Logie, R. H. (1980). Age of acquisition, imagery, concreteness, familiarity and ambiguity measures for 1944 words. Behaviour Research Methods and Instrumentation, 12: 395–427.CrossRefGoogle Scholar
Gitelman, D. R., Nobre, A. C., Parrish, T. B., LaBar, K. S., Kim, Y. H., Meyer, J. R., and Mesulam, M. M. (1999). A large-scale distributed network for covert spatial attention: further anatomical delineation based on stringent behavioural and cognitive controls. Brain, 122: 1093–106.CrossRefGoogle ScholarPubMed
Glenberg, A. M. and Robertson, D. A. (2000). Symbol grounding and meaning: a comparison of high-dimensional and embodied theories of meaning. Journal of Memory and Language, 43: 379–401.CrossRefGoogle Scholar
Goodglass, H., Hyde, M. R., and Blumstein, S. (1969). Frequency, picturability and availability of nouns in aphasia. Cortex, 5: 104–19.CrossRefGoogle ScholarPubMed
Grainger, J. and Jacobs, A. M. (1996). Orthographic processing in visual word recognition: a multiple read-out model. Psychological Review, 103: 518–65.CrossRefGoogle ScholarPubMed
Grossman, M., Koenig, P., DeVita, C., Glosser, G., Alsop, D., Detre, J., and Gee, J. (2002). The neural basis for category-specific knowledge: an fMRI study. Neuroimage, 15: 936–48.CrossRefGoogle ScholarPubMed
Harm, M. W. and Seidenberg, M. S. (2004). Computing the meanings of words in reading: cooperative division of labor between visual and phonological processes. Psychological Review, 111: 662–720.CrossRefGoogle ScholarPubMed
Holcomb, P. J., Kounios, J., Anderson, J. E., and West, W. C. (1999). Dual-coding, context availability, and concreteness effects in sentence comprehension: an electrophysiological investigation. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25: 721–42.Google ScholarPubMed
Honey, G. D., Bullmore, E. T., and Sharma, T. (2000). Prolonged reaction time to a verbal working memory task predicts increased power of posterior parietal cortical activation. NeuroImage, 12: 495–503.CrossRefGoogle ScholarPubMed
Howard, R. J., Ffytche, D. H., Barnes, J., McKeefry, D., Ha, Y., Woodruff, P. W., Bullmore, E. T., Simons, A., and Williams, S. C. R. (1998). The functional anatomy of imagined and perceived colour. Neuroreport, 9: 1019–23.CrossRefGoogle Scholar
Hume, D. (1739/1975). A Treatise of Human Nature. London: Oxford University Press.Google Scholar
Indefrey, P. and Levelt, W. J. M. (2000). The neural correlates of language production. In Gazzaniga, M. S. (ed.), The New Cognitive Neurosciences. Cambridge, MA: MIT Press, pp. 845–65.Google Scholar
Ischebeck, A., Indefrey, P., Usui, N., Nose, I., Hellwig, F., and Taira, M. (2004). Reading in a regular orthography: an fMRI study investigating the role of visual familiarity. Journal of Cognitive Neuroscience, 16: 727–41.CrossRefGoogle Scholar
Ishai, A., Ungerleider, L. G., and Haxby, J. V. (2000). Distributed neural systems for the generation of visual images. Neuron, 28: 979–90.CrossRefGoogle ScholarPubMed
James, C. T. (1975). The role of semantic information in lexical decisions. Journal of Experimental Psychology: Human Perception and Performance, 104: 130–6.Google Scholar
Jessen, F., Heun, R., Erb, M., Granath, D. O., Klose, U., Papassotiropoulos, A., and Grodd, W. (2000). The concreteness effect: Evidence for dual-coding and context availability. Brain and Language, 74: 103–12.CrossRefGoogle ScholarPubMed
Jones, G. V. (1985). Deep dyslexia, imageability, and ease of predication. Brain and Language, 24: 1–19.CrossRefGoogle ScholarPubMed
Jonides, J., Schumacher, E. H., Smith, E. E., Lauber, E., Awh, E., Minoshima, S., and Koeppe, R. A. (1997). The task-load of verbal working memory affects regional brain activation as measured by PET. Journal of Cognitive Neuroscience, 9: 462–75.CrossRefGoogle Scholar
Kan, I. P., Barsalou, L. W., Solomon, K. O., Minor, J. K., and Thompson-Schill, S. L. (2003). Role of mental imagery in a property verification task: fMRI evidence for perceptual representations of conceptual knowledge. Cognitive Neuropsychology, 20: 525–40.CrossRefGoogle Scholar
Kastner, S. and Ungerleider, L. G. (2000). Mechanisms of visual attention in the human cortex. Annual Review of Neuroscience, 23: 315–41.Google ScholarPubMed
Katz, R. B. and Goodglass, H. (1990). Deep dysphasia: Analysis of a rare form of repetition disorder. Brain and Language, 39: 153–85.CrossRefGoogle ScholarPubMed
Kellenbach, M. L., Brett, M., and Patterson, K. (2001). Large, colourful or noisy? Attribute- and modality-specific activations during retrieval of perceptual attribute knowledge. Cognitive, Affective, and Behavioral Neuroscience, 1: 207–21.CrossRefGoogle ScholarPubMed
Kiehl, K. A., Liddle, P. F., Smith, A. M., Mendrek, A., Forster, B. B., and Hare, R. D. (1999). Neural pathways involved in the processing of concrete and abstract words. Human Brain Mapping, 7: 225–33.3.0.CO;2-P>CrossRefGoogle ScholarPubMed
Kosslyn, S. M. and Thompson, W. L. (2000). Shared mechanisms in visual imagery and visual perception: insights from cognitive neuroscience. In Gazzaniga, M. S. (ed.), The New Cognitive Neurosciences, 2nd edn. Cambridge, MA: MIT Press, pp. 975–85.Google Scholar
Kounios, J. and Holcomb, P. J. (1994). Concreteness effects in semantic processing: ERP evidence supporting dual-encoding theory. Journal of Experimental Psychology: Learning, Memory and Cognition, 20: 804–23.Google Scholar
Kounios, J. and Holcomb, P. J. (2000). Concreteness effects in semantic processing: ERP evidence supporting dual-coding theory. Journal of Experimental Psychology: Language, Memory and Cognition, 20: 804–23.Google Scholar
Kroll, J. F. and Merves, J. S. (1986). Lexical access for concrete and abstract words. Journal of Experimental Psychology: Learning, Memory and Cognition, 12: 92–107.Google Scholar
LaBar, K. S., Gitelman, D. R., Parrish, T. B., and Mesulam, M. M. (1999). Neuroanatomic overlap of working memory and spatial attention networks: a functional MRI comparison within subjects. Neuroimage, 10: 695–704.CrossRefGoogle ScholarPubMed
Locke, J. (1690/1959). An Essay Concerning Human Understanding. New York: Dover.Google Scholar
Mandler, J. M. (1992). How to build a baby: II. Conceptual primitives. Psychological Review, 99: 587–604.CrossRefGoogle ScholarPubMed
Mareschal, D. (2000). Infant object knowledge: current trends and controversies. Trends in Cognitive Science, 4: 408–16.CrossRefGoogle Scholar
Marshall, J., Pring, T., Robson, J., and Chiat, S. (1998). When ottoman is easier than chair: an inverse frequency effect in jargon aphasia. Brain and Language, 65: 78–81.Google Scholar
Marshall, J. C. and Newcombe, F. (1973). Patterns of paralexia: a psycholinguistic approach. Journal of Psycholinguist Research, 2: 175–99.CrossRefGoogle ScholarPubMed
Martin, A. and Chao, L. L. (2001). Semantic memory in the brain: Structure and processes. Current Opinion in Neurobiology, 11: 194–201.CrossRefGoogle ScholarPubMed
Martin, A., Haxby, J. V., Lalonde, F. M., Wiggs, C. L., and Ungerleider, L. G. (1995). Discrete cortical regions associated with knowledge of color and knowledge of action. Science, 270: 102–5.CrossRefGoogle Scholar
Martin, A., Wiggs, C. L., Ungerleider, L. G., and Haxby, J. V. (1996). Neural correlates of category-specific knowledge. Nature, 379: 649–52.CrossRefGoogle ScholarPubMed
Martin, A., Ungerleider, L. G., and Haxby, J. V. (2000). Category-specificity and the brain: The sensory-motor model of semantic representations of objects. In Gazzaniga, M. S. (ed.), The New Cognitive Neurosciences, 2nd edn. Cambridge, MA: MIT Press, pp. 1023–36.Google Scholar
Mellet, E., Tzourio, N., Denis, M., and Mazoyer, B. (1998). Cortical anatomy of mental imagery of concrete nouns based on their dictionary definition. Neuroreport, 9: 803–8.CrossRefGoogle ScholarPubMed
Menon, V., Adleman, N. E., White, C. D., Glover, G. H., and Reiss, A. L. (2001). Error-related brain activation during a Go/NoGo response inhibition task. Human Brain Mapping, 12: 131–43.3.0.CO;2-C>CrossRefGoogle ScholarPubMed
Meyer, D. E., Schvaneveldt, R. W., and Ruddy, M. G. (1974). Functions of graphemic and phonemic codes in visual word recognition. Memory and Cognition, 2: 309–21.CrossRefGoogle ScholarPubMed
Monaghan, J. and Ellis, A. W. (2002). What exactly interacts with spelling–sound consistency in word naming?Journal of Experimental Psychology: Learning, Memory, and Cognition, 28: 183–206.Google ScholarPubMed
Moore, C. J. and Price, C. J. (1999). A functional neuroimaging study of the variables that generate category specific object processing differences. Brain, 122: 943–62.CrossRefGoogle ScholarPubMed
Morton, J. and Patterson, K. (1980). A new attempt at an interpretation, or, an attempt at a new interpretation. In Coltheart, M., Patterson, K., and Marshall, J. C. (eds.), Deep Dyslexia. London: Routledge & Kegan Paul, pp. 91–118.Google Scholar
Mummery, C. J., Patterson, K., Hodges, J. R., and Wise, R. J. S. (1996). Generating “tiger” as an animal name or a word beginning with T: differences in brain activation. Proceedings of the Royal Society of London B, 263: 989–95.CrossRefGoogle ScholarPubMed
Mummery, C. J., Patterson, K., Hodges, J. R., and Price, C. J. (1998). Functional neuroanatomy of the semantic system: divisible by what?Journal of Cognitive Neuroscience, 10: 766–77.CrossRefGoogle Scholar
Nittono, H., Suehiro, M., and Hori, T. (2002). Word imageability and N400 in an incidental memory paradigm. International Journal of Psychophysiology, 44: 219–29.CrossRefGoogle Scholar
Noppeney, U. and Price, C. J. (2004). Retrieval of abstract semantics. Neuroimage, 22: 164–70.CrossRefGoogle ScholarPubMed
O'Craven, K. M. and Kanwisher, N. (2000). Mental imagery of faces and places activates corresponding stimulus-specific brain regions. Journal of Cognitive Neuroscience, 12: 1013–23.CrossRefGoogle Scholar
Paivio, A. (1971). Imagery and Verbal Processes. New York: Holt, Rinehart & Winston.Google Scholar
Paivio, A. (1986). Mental Representations: A dual-coding approach. New York: Oxford University Press.Google Scholar
Paivio, A., Yuille, J. C., and Madigan, S. A. (1968). Concreteness, imagery, and meaningfulness values for 925 nouns. Journal of Experimental Psychology Monograph Supplement, 76: 1–25.CrossRefGoogle ScholarPubMed
Paulesu, E., Frith, C. D., and Frackowiak, R. S. J. (1993). The neural correlates of the verbal component of working memory. Nature, 362: 342–5.CrossRefGoogle ScholarPubMed
Perani, D., Cappa, S. F., Bettinardi, V., Bressi, S., Gorno-Tempini, M., Matarrese, M., and Fazio, F. (1995). Different neural systems for the recognition of animals and man-made tools. Neuroreport, 6: 1637–41.CrossRefGoogle ScholarPubMed
Perani, D., Schnur, T., Tettamanti, M., Gorno-Tempini, M., Cappa, S. F., and Fazio, F. (1999a). Word and picture matching: a PET study of semantic category effects. Neuropsychologia, 37: 293–306.CrossRefGoogle Scholar
Perani, D., Cappa, S. F., Schnur, T., Tettamanti, M., Collina, S., Rosa, M. M., and Fazio, F. (1999b). The neural correlates of verb and noun processing. A PET study. Brain, 122: 2337–44.CrossRefGoogle Scholar
Plaut, D. C. and Shallice, T. (1993). Deep dyslexia: a case study of connectionist neuropsychology. Cognitive Neuropsychology, 10: 377–500.CrossRefGoogle Scholar
Plaut, D. C., McClelland, J. L., Seidenberg, M. S., and Patterson, K. (1996). Understanding normal and impaired word reading: computational principles in quasi-regular domains. Psychological Review, 103: 45–115.CrossRefGoogle ScholarPubMed
Price, C. J. and Friston, K. J. (2002). Functional imaging studies of category specificity. In Forde, E. M. E. and Humphreys, G. (eds.), Category Specificity in Brain and Mind. Hove, UK: Psychology Press, pp. 427–48.Google Scholar
Price, C. J., Moore, C. J., Humphreys, G. W., and Wise, R. J. S. (1997). Segregating semantic from phonological processes during reading. Journal of Cognitive Neuroscience, 9: 727–33.CrossRefGoogle ScholarPubMed
Pulvermüller, F. (1999). Words in the brain's language. Behavioral Brain Science, 22: 253–336.CrossRefGoogle ScholarPubMed
Rissman, J., Eliassen, J. C., and Blumstein, S. E. (2003). An event-related fMRI investigation of implicit semantic priming. Journal of Cognitive Neuroscience, 15: 1160–75.CrossRefGoogle ScholarPubMed
Roeltgen, D. P., Sevush, S., and Heilman, K. M. (1983). Phonological agraphia: Writing by the lexical–semantic route. Neurology, 33: 755–65.CrossRefGoogle ScholarPubMed
Rosch, E., Mervis, C. B., Gray, W. D., Johnson, D. M., and Boyes-Braem, D. (1976). Basic objects in natural categories. Cognitive Psychology, 8: 382–439.CrossRefGoogle Scholar
Roskies, A. L., Fiez, J. A., Balota, D. A., Raichle, M. E., and Petersen, S. E. (2001). Task-dependent modulation of regions in the left inferior frontal cortex during semantic processing. Journal of Cognitive Neuroscience, 13: 829–43.CrossRefGoogle ScholarPubMed
Sabsevitz, D. S., Medler, D. A., Seidenberg, M., and Binder, J. R. (2005). Modulation of the semantic system by word imageability. Neuroimage, 27: 188–200.CrossRefGoogle ScholarPubMed
Schwanenflugel, P. (1991). Why are abstract concepts hard to understand? In Schwanenflugel, P. (ed.), The Psychology of Word Meanings. Hillsdale, NJ: Erlbaum, pp. 223–50.Google Scholar
Scott, S. K., Leff, A. P., and Wise, R. J. S. (2003). Going beyond the information given: a neural system supporting semantic interpretation. Neuroimage, 19: 870–6.CrossRefGoogle ScholarPubMed
Seidenberg, M. S. and McClelland, J. L. (1989). A distributed, developmental model of word recognition and naming. Psychological Review, 96: 523–68.CrossRefGoogle ScholarPubMed
Shibahara, N., Zorzi, M., Hill, M. P., Wydell, T., and Butterworth, B. (2003). Semantic effects in word naming: evidence from English and Japanese Kanji. Quarterly Journal of Experimental Psychology, 56A: 263–86.CrossRefGoogle Scholar
Smith, E. E., Jonides, J., Marshuetz, C., and Koeppe, R. A. (1998). Components of verbal working memory: Evidence from neuroimaging. Proceedings of the National Academy of Sciences USA, 95: 876–82.CrossRefGoogle ScholarPubMed
Stone, G. O. and Orden, G. C. (1993). Strategic control of processing in word recognition. Journal of Experimental Psychology: Human Perception and Performance, 19: 744–74.Google ScholarPubMed
Strain, E., Patterson, K., and Seidenberg, M. S. (1995). Semantic effects in single-word naming. Journal of Experimental Psychology: Learning, Memory, and Cognition, 21: 1140–54.Google ScholarPubMed
Strain, E., Patterson, K., and Seidenberg, M. S. (2002). Theories of word naming interact with spelling–sound consistency. Journal of Experimental Psychology: Learning, Memory, and Cognition, 28: 207–14.Google ScholarPubMed
Sturm, W. and Willmes, K. (2001). On the functional neuroanatomy of intrinsic and phasic alertness. Neuroimage, 14: S76–84.CrossRefGoogle ScholarPubMed
Taylor, S. F., Kornblum, S., Minoshima, S., Oliver, L. M., and Koeppe, R. A. (1994). Changes in medial cortical blood flow with a stimulus–response compatibility task. Neuropsychologia, 32: 249–55.CrossRefGoogle ScholarPubMed
Thompson-Schill, S. L. (2003). Neuroimaging studies of semantic memory: inferring “how” from “where”. Neuropsychologia, 41: 280–92.CrossRefGoogle Scholar
Thompson-Schill, S. L., D'Esposito, M., and Kan, I. P. (1999a). Effects of repetition and competition on activity in left prefrontal cortex during word generation. Neuron, 23: 513–22.CrossRefGoogle Scholar
Thompson-Schill, S. L., Aguirre, G. K., D'Esposito, M., and Farah, M. J. (1999b). A neural basis for category and modality specificity of semantic knowledge. Neuropsychologia, 37: 671–6.CrossRefGoogle Scholar
Tyler, L. K., Russell, R., Fadili, J., and Moss, H. E. (2001). The neural representation of nouns and verbs: PET studies. Brain, 124: 1619–34.CrossRefGoogle ScholarPubMed
Ullsperger, M. and Cramon, D. Y. (2001). Subprocesses of performance monitoring: a dissociation of error processing and response competition revealed by event-related fMRI and ERPs. Neuroimage, 14: 1387–401.CrossRefGoogle ScholarPubMed
Order, G. C., Pennington, B. F., and Stone, G. O. (1990). Word identification in reading and the promise of subsymbolic psycholinguistics. Psychological Review, 97: 488–522.Google Scholar
Veen, V. and Carter, C. S. (2002). The anterior cingulate as a conflict monitor: fMRI and ERP studies. Physiology and Behavior, 77: 477–82.CrossRefGoogle ScholarPubMed
Wager, T. D. and Smith, E. E. (2003). Neuroimaging studies of working memory: a meta-analysis. Cognitive, Affective, and Behavioral Neuroscience, 3: 255–74.CrossRefGoogle ScholarPubMed
Warrington, E. K. (1975). The selective impairment of semantic memory. Quarterly Journal of Experimental Psychology, 27: 635–57.CrossRefGoogle ScholarPubMed
Warrington, E. K. (1981). Concrete word dyslexia. British Journal of Psychology, 72: 175–96.CrossRefGoogle ScholarPubMed
Warrington, E. K. and Shallice, T. (1984). Category specific semantic impairments. Brain, 107: 829–54.CrossRefGoogle ScholarPubMed
Warrington, E. K. and McCarthy, R. A. (1987). Categories of knowledge. Further fractionations and an attempted integration. Brain, 110: 1273–96.CrossRefGoogle ScholarPubMed
Waters, G. S. and Seidenberg, M. S. (1985). Spelling–sound effects in reading: time course and decision criteria. Memory and Cognition, 13: 557–72.CrossRefGoogle ScholarPubMed
Wernicke, C. (1874). Der aphasische Symptomenkomplex. Breslau: Cohn & Weigert.
Whatmough, C., Verret, L., Fung, D., and Chertkow, H. (2004). Common and contrasting areas of activation for abstract and concrete concepts: an H2 15O PET study. Journal of Cognitive Neuroscience, 16: 1211–26.CrossRefGoogle ScholarPubMed
Wise, R. J. S., Howard, D., Mummery, C. J., Fletcher, P., Leff, A., Büchel, C., and Scott, S. K. (2000). Noun imageability and the temporal lobes. Neuropsychologia, 38: 985–94.CrossRefGoogle ScholarPubMed
Zaidel, E. (1978). Auditory language comprehension in the right hemisphere following commissurotomy and hemispherectomy: a comparison with child language and aphasia. In Caramazza, A. and Zurif, E. B. (eds.), Language Acquisition and Language Breakdown: Parallels and divergences. Baltimore, MD: The Johns Hopkins University Press, pp. 229–75.Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure coreplatform@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×