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A unified model of human semantic knowledge and its disorders

Nature Human Behaviour volume 1, Article number: 0039 (2017) Cite this article

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Abstract

How is knowledge about the meanings of words and objects represented in the human brain? Current theories embrace two radically different proposals: either distinct cortical systems have evolved to represent different kinds of things, or knowledge for all kinds is encoded within a single domain-general network. Neither view explains the full scope of relevant evidence from neuroimaging and neuropsychology. Here we propose that graded category-specificity emerges in some components of the semantic network through joint effects of learning and network connectivity. We test the proposal by measuring connectivity amongst cortical regions implicated in semantic representation, then simulating healthy and disordered semantic processing in a deep neural network whose architecture mirrors this structure. The resulting neuro-computational model explains the full complement of neuroimaging and patient evidence adduced in support of both domain-specific and domain-general approaches, reconciling long-standing disputes about the nature and origins of this uniquely human cognitive faculty.

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Figure 1: ALE analysis showing regions that systematically respond more to animals than artifacts (orange), more to artifacts than animals (blue), or equally to both (green).
Figure 2: Tractography results.
Figure 3: Model architecture and functional magnetic resonance imaging (fMRI) data simulations.
Figure 4: Results of patient simulations.

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References

  1. Fernandino, L. et al. Predicting brain activation patterns associated with individual lexical concepts based on five sensory-motor attributes. Neuropsychologia 76, 17–26 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  2. Caramazza, A. & Shelton, J. R. Domain-specific knowledge systems in the brain: the animate–inanimate distinction. J. Cogn. Neurosci. 10, 1–34 (1998).

    Article  CAS  PubMed  Google Scholar 

  3. Caramazza, A. & Mahon, B. Z. The organization of conceptual knowledge: the evidence from category-specific semantic deficits. Trends Cogn. Sci. 7, 354–361 (2003).

    Article  PubMed  Google Scholar 

  4. Patterson, K., Nestor, P. J. & Rogers, T. T. Where do you know what you know? The representation of semantic knowledge in the human brain. Nat. Rev. Neurosci 8, 976–987 (2007).

    Article  CAS  PubMed  Google Scholar 

  5. Rogers, T. T. et al. The structure and deterioration of semantic memory: a computational and neuropsychological investigation. Psychol. Rev. 111, 205–235 (2004).

    Article  PubMed  Google Scholar 

  6. Tyler, L. K., Moss, H. E., Durrant-Peatfield, M. R. & Levy, J. P. Conceptual structure and the structure of concepts: a distributed account of category-specific deficits. Brain Lang. 75, 195–231 (2000).

    Article  CAS  PubMed  Google Scholar 

  7. Chen, L. & Rogers, T. T. Revisiting domain-general accounts of category specificity in mind and brain. Wiley Interdiscip. Rev. Cogn. Sci. 5, 327–44 (2014).

    Article  PubMed  Google Scholar 

  8. Plaut, D. C. Graded modality-specific specialisation in semantics: a computational account of optic aphasia. Cogn. Neuropsychol. 19, 603–639 (2002).

    Article  PubMed  Google Scholar 

  9. Mahon, B. Z., Anzellotti, S., Schwarzbach, J., Zampini, M. & Caramazza, A. Category-specific organization in the human brain does not require visual experience. Neuron 63, 397–405 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Warrington, E. K. & Shallice, T. Category specific semantic impairments. Brain 107, 829–854 (1984).

    Article  PubMed  Google Scholar 

  11. Cree, G. S. & McRae, K. Analyzing the factors underlying the structure and computation of the meaning of chipmunk, cherry, chisel, cheese, and cello (and many other such concrete nouns). J. Exp. Psychol. Gen. 132, 163–201 (2003).

    Article  PubMed  Google Scholar 

  12. Chen, L. & Rogers, T. T. A model of emergent category-specific activation in the posterior fusiform gyrus of sighted and congenitally blind populations. J. Cogn. Neurosci. 27, 1981–1999 (2015).

    Article  PubMed  Google Scholar 

  13. Pobric, G., Jefferies, E. & Lambon Ralph, M. A. Category-specific versus category-general semantic impairment induced by transcranial magnetic stimulation. Curr. Biol. 20, 964–968 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Sadtler, P. T. et al. Neural constraints on learning. Nature 512, 423–426 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Gomez, J. et al. Functionally defined white matter reveals segregated pathways in human ventral temporal cortex associated with category-specific processing. Neuron 85, 216–227 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Mahon, B. Z. & Caramazza, A. What drives the organization of object knowledge in the brain? Trends Cogn. Sci. 15, 97–103 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  17. Plaut, D. C. & Behrmann, M. Complementary neural representations for faces and words: a computational exploration. Cogn. Neuropsychol. 28, 251–275 (2011).

    Article  PubMed  Google Scholar 

  18. Martin, A. & Chao, L. L. Semantic memory and the brain: structure and processes. Curr. Opin. Neurobiol. 11, 194–201 (2001).

    Article  CAS  PubMed  Google Scholar 

  19. Mahon, B. Z. et al. Action-related properties shape object representations in the ventral stream. Neuron 55, 507–520 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Hickok, G. & Poeppel, D. The cortical organization of speech processing. Nat. Rev. Neurosci. 8, 393–402 (2007).

    Article  CAS  PubMed  Google Scholar 

  21. Kellenbach, M. L., Brett, M. & Patterson, K. Actions speak louder than functions: the importance of manipulability and action in tool representation. J. Cogn. Neurosci. 15, 30–46 (2003).

    Article  PubMed  Google Scholar 

  22. Chouinard, P. A & Goodale, M. A. Category-specific neural processing for naming pictures of animals and naming pictures of tools: an ALE meta-analysis. Neuropsychologia 48, 409–418 (2010).

    Article  PubMed  Google Scholar 

  23. Pobric, G., Jefferies, E. & Lambon Ralph, M. A. Anterior temporal lobes mediate semantic representation: mimicking semantic dementia by using rTMS in normal participants. Proc. Natl Acad. Sci. USA 104, 20137–20141 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Acosta-Cabronero, J. et al. Atrophy, hypometabolism and white matter abnormalities in semantic dementia tell a coherent story. Brain 134, 2025–2035 (2011).

    Article  PubMed  Google Scholar 

  25. Chouinard, P. A. & Goodale, M. A. Category-specific neural processing for naming pictures of animals and naming pictures of tools: an ALE meta-analysis. Neuropsychologia 48, 409 (2010).

    Article  PubMed  Google Scholar 

  26. Hwang, K. et al. Category-specific activations during word generation reflect experiential sensorimotor modalities. Neuroimage 48, 717–725 (2009).

    Article  PubMed  Google Scholar 

  27. Smith, C. D. et al. Differences in functional magnetic resonance imaging activation by category in a visual confrontation naming task. J. Neuroimaging 11, 165–170 (2001).

    Article  CAS  PubMed  Google Scholar 

  28. Grossman, M. et al. The neural basis for category-specific knowledge: an fMRI study. Neuroimage 15, 936–948 (2002).

    Article  PubMed  Google Scholar 

  29. Martin, A., Haxby, J. V, Lalonde, F. M., Wiggs, C. L. & Ungerleider, L. G. Discrete cortical regions associated with knowledge of color and knowledge of action. Science 270, 102–105 (1995).

    Article  CAS  PubMed  Google Scholar 

  30. Tyler, L. K. et al. Do semantic categories activate distinct cortical regions? Evidence for a distributed neural semantic system. Cogn. Neuropsychol. 20, 541–559 (2003).

    Article  CAS  PubMed  Google Scholar 

  31. Damasio, H., Grabowski, T. J., Tranel, D., Hichwa, R. D. & Damasio, A. R. A neural basis for lexical retrieval. Nature 380, 499–505 (1996).

    Article  CAS  PubMed  Google Scholar 

  32. Cappa, S. F., Perani, D., Schnur, T., Tettamanti, M. & Fazio, F. The effects of semantic category and knowledge type on lexical-semantic access: a PET study. Neuroimage 8, 350–359 (1998).

    Article  CAS  PubMed  Google Scholar 

  33. Mechelli, A., Sartori, G., Orlandi, P. & Price, C. J. Semantic relevance explains category effects in medial fusiform gyri. Neuroimage 30, 992–1002 (2006).

    Article  PubMed  Google Scholar 

  34. Noppeney, U., Josephs, O., Kiebel, S., Friston, K. J. & Price, C. J. Action selectivity in parietal and temporal cortex. Brain Res. Cogn. Brain Res. 25, 641 (2005).

    Article  CAS  PubMed  Google Scholar 

  35. Phillips, J. A., Noppeney, U., Humphreys, G. W. & Price, C. J. Can segregation within the semantic system account for category-specific deficits? Brain 125, 2067–2080 (2002).

    Article  PubMed  Google Scholar 

  36. Kroliczak, G. & Frey, S. H. A common network in the left cerebral hemisphere represents planning of tool use pantomimes and familiar intransitive gestures at the hand-independent level. Cereb. Cortex 19, 2396–2410 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  37. Grossman, M. et al. Category-specific semantic memory: converging evidence from bold fMRI and Alzheimer’s disease. Neuroimage 68, 263–274 (2013).

    Article  PubMed  Google Scholar 

  38. Laine, M., Rinne, J. O., Hiltunen, J., Kaasinen, V. & Sipilä, H. Different brain activation patterns during production of animals versus artefacts: a PET activation study on category-specific processing. Cogn. Brain Res. 13, 95–99 (2002).

    Article  Google Scholar 

  39. Boronat, C. B. et al. Distinctions between manipulation and function knowledge of objects: evidence from functional magnetic resonance imaging. Cogn. Brain Res. 23, 361–373 (2005).

    Article  Google Scholar 

  40. Gorno-Tempini, M.-L. Category differences in brain activation studies: where do they come from? Proc. R. Soc. Lond. B 267, 1253–1258 (2000).

    Article  CAS  Google Scholar 

  41. Gerlach, C., Law, I. & Paulson, O. B. When action turns into words. Activation of motor-based knowledge during categorization of manipulable objects. J. Cogn. Neurosci. 14, 1230–1239 (2002).

    Article  PubMed  Google Scholar 

  42. Rogers, T. T., Hocking, J., Mechelli, A., Patterson, K. & Price, C. Fusiform activation to animals is driven by the process, not the stimulus. J. Cogn. Neurosci. 17, 434–445 (2005).

    Article  PubMed  Google Scholar 

  43. Lewis, J. W., Brefczynski, J. A., Phinney, R. E., Janik, J. J. & DeYoe, E. A. Distinct cortical pathways for processing tool versus animal sounds. J. Neurosci. 25, 5148–5158 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Canessa, N. et al. The different neural correlates of action and functional knowledge in semantic memory: an fMRI study. Cereb. Cortex 18, 740–751 (2008).

    Article  PubMed  Google Scholar 

  45. Joseph, J. E., Gathers, A. D. & Piper, G. A. Shared and dissociated cortical regions for object and letter processing. Cogn. Brain Res. 17, 56–67 (2003).

    Article  Google Scholar 

  46. Gerlach, C. et al. Brain activity related to integrative processes in visual object recognition: bottom-up integration and the modulatory influence of stored knowledge. Neuropsychologia 40, 1254–1267 (2002).

    Article  CAS  PubMed  Google Scholar 

  47. Gerlach, C., Law, I., Gade, A. & Paulson, O. B. Categorization and category effects in normal object recognition: a PET study. Neuropsychologia 38, 1693–1703 (2000).

    Article  CAS  PubMed  Google Scholar 

  48. Devlin, J. T., Rushworth, M. F. S. & Matthews, P. M. Category-related activation for written words in the posterior fusiform is task specific. Neuropsychologia 43, 69–74 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  49. Noppeney, U., Price, C. J., Penny, W. D. & Friston, K. J. Two distinct neural mechanisms for category-selective responses. Cereb. Cortex 16, 437–445 (2006).

    Article  PubMed  Google Scholar 

  50. Whatmough, C., Chertkow, H., Murtha, S. & Hanratty, K. Dissociable brain regions process object meaning and object structure during picture naming. Neuropsychologia 40, 174–186 (2002).

    Article  CAS  PubMed  Google Scholar 

  51. Grafton, S. T., Fadiga, L., Arbib, M. A. & Rizzolatti, G. Premotor cortex activation during observation and naming of familiar tools. Neuroimage 6, 231–236 (1997).

    Article  CAS  PubMed  Google Scholar 

  52. Chao, L. L., Haxby, J. V. & Martin, A. Attribute-based neural substrates in temporal cortex for perceiving and knowing about objects. Nat. Neurosci. 2, 913–919 (1999).

    Article  CAS  PubMed  Google Scholar 

  53. Chao, L. L. & Martin, A. Representation of manipulable man-made objects in the dorsal stream. Neuroimage 12, 478–484 (2000).

    Article  CAS  PubMed  Google Scholar 

  54. Goldberg, R. F., Perfetti, C. A. & Schneider, W. Perceptual knowledge retrieval activates sensory brain regions. J. Neurosci. 26, 4917–4921 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Bai, H. M. et al. Functional MRI mapping of category-specific sites associated with naming of famous faces, animals and man-made objects. Neurosci. Bull. 27, 307–318 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  56. Folstein, J. R., Palmeri, T. J. & Gauthier, I. Category learning increases discriminability of relevant object dimensions in visual cortex. Cereb. Cortex 23, 814–823 (2013).

    Article  PubMed  Google Scholar 

  57. Martin, A, Wiggs, C. L., Ungerleider, L. G. & Haxby, J. V. Neural correlates of category-specific knowledge. Nature 379, 649–652 (1996).

    Article  CAS  PubMed  Google Scholar 

  58. Perani, D. et al. Word and picture matching: a PET study of semantic category effects. Neuropsychologia 37, 293–306 (1999).

    Article  CAS  PubMed  Google Scholar 

  59. Handy, T. C., Grafton, S. T., Shroff, N. M., Ketay, S. & Gazzaniga, M. S. Graspable objects grab attention when the potential for action is recognized. Nat. Neurosci. 6, 421–427 (2003).

    Article  CAS  PubMed  Google Scholar 

  60. Gerlach, C., Law, I. & Paulson, O. B. Structural similarity and category-specificity: a refined account. Neuropsychologia 42, 1543–1553 (2004).

    Article  PubMed  Google Scholar 

  61. Wadsworth, H. M. & Kana, R. K. Brain mechanisms of perceiving tools and imagining tool use acts: a functional MRI study. Neuropsychologia 49, 1863–1869 (2011).

    Article  PubMed  Google Scholar 

  62. Okada, T. et al. Naming of animals and tools: a functional magnetic resonance imaging study of categorical differences in the human brain areas commonly used for naming visually presented objects. Neurosci. Lett. 296, 33 (2000).

    Article  CAS  PubMed  Google Scholar 

  63. Mahon, B. Z., Schwarzbach, J. & Caramazza, A. The representation of tools in left parietal cortex is independent of visual experience. Psychol. Sci. 21, 764–771 (2010).

    Article  PubMed  Google Scholar 

  64. Creem-Regehr, S. H. & Lee, J. N. Neural representations of graspable objects: are tools special? Cogn. Brain Res. 22, 457–469 (2005).

    Article  Google Scholar 

  65. Mruczek, R. E. B., von Loga, I. S. & Kastner, S. The representation of tool and non-tool object information in the human intraparietal sulcus. J. Neurophysiol. 109, 2883–2896 (2013).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Zannino, G. D. et al. Visual and semantic processing of living things and artifacts: an fMRI study. J. Cogn. Neurosci. 22, 554–570 (2010).

    Article  PubMed  Google Scholar 

  67. Chao, L. L., Weisberg, J. & Martin, A. Experience-dependent modulation of category-related cortical activity. Cereb. Cortex 12, 545–551 (2002).

    Article  PubMed  Google Scholar 

  68. Anzellotti, S., Mahon, B. Z., Schwarzbach, J. & Caramazza, A. Differential activity for animals and manipulable objects in the anterior temporal lobes. J. Cogn. Neurosci. 23, 2059–2067 (2011).

    Article  PubMed  Google Scholar 

  69. Moore, C. J. & Price, C. J. A functional neuroimaging study of the variables that generate category-specific object processing differences. Brain 122, 943–962 (1999).

    Article  PubMed  Google Scholar 

  70. Tranel, D., Martin, C., Damasio, H., Grabowski, T. J. & Hichwa, R. Effects of noun–verb homonymy on the neural correlates of naming concrete entities and actions. Brain Lang. 92, 288–299 (2005).

    Article  PubMed  Google Scholar 

  71. Grabowski, T. J., Damasio, H. & Damasio, A. R. Premotor and prefrontal correlates of category-related lexical retrieval. Neuroimage 7, 232–243 (1998).

    Article  CAS  PubMed  Google Scholar 

  72. Eickhoff, S. B., Bzdok, D., Laird, A. R., Kurth, F. & Fox, P. T. Activation likelihood estimation meta-analysis revisited. Neuroimage 59, 2349–2361 (2012).

    Article  PubMed  Google Scholar 

  73. Martin, A. The representation of object concepts in the brain. Annu. Rev. Psychol. 58, 25–45 (2007).

    Article  PubMed  Google Scholar 

  74. Ueno, T., Saito, S., Rogers, T. T. & Lambon Ralph, M. A. Lichtheim 2: synthesizing aphasia and the neural basis of language in a neurocomputational model of the dual dorsal-ventral language pathways. Neuron 72, 385–96 (2011).

    Article  CAS  PubMed  Google Scholar 

  75. Visser, M., Jefferies, E. & Lambon Ralph, M. A. Semantic processing in the anterior temporal lobes: a meta-analysis of the functional neuroimaging literature. J. Cogn. Neurosci. 22, 1083–1094 (2010).

    Article  CAS  PubMed  Google Scholar 

  76. Adlam, A. L. R. et al. Semantic dementia and fluent primary progressive aphasia: two sides of the same coin? Brain 129, 3066–3080 (2006).

    Article  PubMed  Google Scholar 

  77. Shimotake, A. et al. Direct exploration of the role of the ventral anterior temporal lobe in semantic memory: cortical stimulation and local field potential evidence from subdural grid electrodes. Cereb. Cortex 25, 3802–3817 (2015).

    Article  PubMed  Google Scholar 

  78. Lambon Ralph, M. A., Lowe, C. & Rogers, T. T. Neural basis of category-specific semantic deficits for living things: evidence from semantic dementia, HSVE and a neural network model. Brain 130, 1127–1137 (2007).

    Article  PubMed  Google Scholar 

  79. Binkofski, F. & Buxbaum, L. J. Two action systems in the human brain. Brain Lang. 127, 222–229 (2013).

    Article  PubMed  Google Scholar 

  80. Humphreys, G. W. & Riddoch, M. J. Features, objects, action: the cognitive neuropsychology of visual object processing, 1984–2004. Cogn. Neuropsychol. 23, 156–183 (2006).

    Article  PubMed  Google Scholar 

  81. Humphreys, G. F. & Lambon Ralph, M. A. Fusion and fission of cognitive functions in the human parietal cortex. Cereb. Cortex 25, 3547–3560 (2015).

    Article  PubMed  Google Scholar 

  82. Jung, J., Cloutman, L. L., Binney, R. J. & Ralph, M. A. L. The structural connectivity of higher order association cortices reflects human functional brain networks. Cortex http://dx.doi.org/10.1016/j.cortex.2016.08.011 (2016).

  83. Embleton, K. V., Haroon, H. A., Morris, D. M., Lambon Ralph, M. A. & Parker, G. J. M. Distortion correction for diffusion-weighted MRI tractography and fMRI in the temporal lobes. Hum. Brain Mapp. 31, 1570–1587 (2010).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Binney, R. J., Embleton, K. V, Jefferies, E., Parker, G. J. M. & Lambon Ralph, M. A. The ventral and inferolateral aspects of the anterior temporal lobe are crucial in semantic memory: evidence from a novel direct comparison of distortion-corrected fMRI, rTMS, and semantic dementia. Cereb. Cortex 20, 2728–2738 (2010).

    Article  PubMed  Google Scholar 

  85. Kravitz, D. J., Saleem, K. S., Baker, C. I., Ungerleider, L. G. & Mishkin, M. The ventral visual pathway: an expanded neural framework for the processing of object quality. Trends Cogn. Sci. 17, 26–49 (2013).

    Article  PubMed  Google Scholar 

  86. Binney, R. J., Parker, G. J. M. & Lambon Ralph, M. A. Convergent connectivity and graded specialization in the rostral human temporal lobe as revealed by diffusion-weighted imaging probabilistic tractography. J. Cogn. Neurosci. 24, 1998–2014 (2012).

    Article  PubMed  Google Scholar 

  87. Schmahmann, J. D. & Pandya, D. Fiber Pathways of the Brain (Oxford Univ. Press, 2009).

    Google Scholar 

  88. Bajada, C. J., Lambon Ralph, M. A. & Cloutman, L. L. Transport for language south of the Sylvian fissure: the routes and history of the main tracts and stations in the ventral language network. Cortex 69, 141–151 (2015).

    Article  PubMed  Google Scholar 

  89. Bedny, M., Caramazza, A., Pascual-Leone, A. & Saxe, R. Typical neural representations of action verbs develop without vision. Cereb. Cortex 22, 286–293 (2012).

    Article  CAS  PubMed  Google Scholar 

  90. Warrington, E. K. & McCarthy, R. Category specific access dysphasia. Brain 106, 859–878 (1983).

    Article  PubMed  Google Scholar 

  91. Gotts, S. & Plaut, D. C. The impact of synaptic depression following brain damage: a connectionist account of ‘access/refractory’ and ‘degraded-store’ semantic impairments. Cogn. Affect. Behav. Neurosci. 2, 187–213 (2002).

    Article  PubMed  Google Scholar 

  92. Noppeney, U. et al. Temporal lobe lesions and semantic impairment: a comparison of herpes simplex virus encephalitis and semantic dementia. Brain 130, 1138–1147 (2007).

    Article  PubMed  Google Scholar 

  93. Campanella, F., D’Agostini, S., Skrap, M. & Shallice, T. Naming manipulable objects: anatomy of a category specific effect in left temporal tumours. Neuropsychologia 48, 1583–1597 (2010).

    Article  PubMed  Google Scholar 

  94. Roberts, D. Exploring the Link Between Visual Impairment and Pure Alexia. PhD thesis, Univ. Manchester (2009).

    Google Scholar 

  95. Humphreys, G. W. & Forde, E. M. E. Category specificity in mind and brain? Behav. Brain Sci. 24, 497–509 (2001).

    Article  Google Scholar 

  96. Laiacona, M., Capitani, E. & Barbarotto, R. Semantic category dissociations: a longitudinal study of two cases. Cortex 33, 441–461 (1997).

    Article  CAS  PubMed  Google Scholar 

  97. Pietrini, V. et al. Recovery from herpes simplex encephalitis: selective impairment of specific semantic categories with neuroradiological correlation. J. Neurol. Neurosurg. Psychiatry 51, 1284–1293 (1988).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  98. Damasio, H., Tranel, D., Grabowski, T., Adolphs, R. & Damasio, A. Neural systems behind word and concept retrieval. Cognition 92, 179–229 (2004).

    Article  CAS  PubMed  Google Scholar 

  99. Plaut, D. C. & Behrmann, M. Complementary neural representations for faces and words: a computational exploration. Cogn. Neuropsychol. 28, 251–275 (2011).

    Article  PubMed  Google Scholar 

  100. Farah, M. J. & McClelland, J. L. A computational model of semantic memory impairment: modality-specificity and emergent category-specificity. J. Exp. Psychol. Gen. 120, 339–357 (1991).

    Article  CAS  PubMed  Google Scholar 

  101. Badre, D. & Wagner, A. Semantic retrieval, mnemonic control, and prefrontal cortex. Behav. Cogn. Neurosci. Rev. 1, 206–218 (2002).

    Article  PubMed  Google Scholar 

  102. LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436–444 (2015).

    Article  CAS  PubMed  Google Scholar 

  103. McClelland, J. L., Rumelhart, D. E. & Hinton, G. E. in Parallel Distributed Processing: Explorations in the Microstructure of Cognition Vol. 1 (eds Rumelhart, D. E., McClelland, J. L. & the PDP Research Group ) 3–44 (MIT Press, 1986).

    Google Scholar 

  104. Price, C. J., Devlin, J. T., Moore, C. J., Morton, C. & Laird, A. R. Meta-analyses of object naming: effect of baseline. Hum. Brain Mapp. 25, 70–82 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  105. Turkeltaub, P. E. et al. Minimizing within-experiment and within-group effects in activation likelihood estimation meta-analyses. Hum. Brain Mapp. 33, 1–13 (2012).

    Article  PubMed  Google Scholar 

  106. Oldfield, R. C. The assessment and analysis of handedness: the Edinburgh inventory. Neuropsychologia 9, 97–113 (1971).

    Article  CAS  PubMed  Google Scholar 

  107. Eickhoff, S. B. et al. Coordinate-based activation likelihood estimation meta-analysis of neuroimaging data: a random-effects approach based on empirical estimates of spatial uncertainty. Hum. Brain Mapp. 30, 2907–2926 (2009).

    Article  PubMed  PubMed Central  Google Scholar 

  108. Cloutman, L. L., Binney, R. J., Drakesmith, M., Parker, G. J. M. & Lambon Ralph, M. A. The variation of function across the human insula mirrors its patterns of structural connectivity: evidence from in vivo probabilistic tractography. Neuroimage 59, 3514–3521 (2012).

    Article  PubMed  Google Scholar 

  109. Visser, M. & Lambon Ralph, M. A. Differential contributions of bilateral ventral anterior temporal lobe and left anterior superior temporal gyrus to semantic processes. J. Cogn. Neurosci. 23, 3121–3131 (2011).

    Article  CAS  PubMed  Google Scholar 

  110. Pobric, G., Jefferies, E. & Lambon Ralph, M. A. Category-specific versus category-general semantic impairment induced by transcranial magnetic stimulation. Curr. Biol. 20, 964–968 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  111. Parker, G. J. M. & Alexander, D. C. Probabilistic anatomical connectivity derived from the microscopic persistent angular structure of cerebral tissue. Phil. Trans. R. Soc. B 360, 893–902 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  112. Rohde, D. L. T. LENS: The Light, Efficient Network Simulator. Technical Report CMU-CS-99-164 (Carnegie Mellon Univ., 1999).

  113. Rumelhart, D. E., Hinton, G. E. & Williams, R. J. Learning Representations by Back-Propagating Errors (MIT Press, 1988).

    Google Scholar 

  114. Garrard, P. & Carroll, E. Lost in semantic space: a multi-modal, non-verbal assessment of feature knowledge in semantic dementia. Brain 129, 1152–1163 (2006).

    Article  PubMed  Google Scholar 

  115. Dixon, M. J., Bub, D. N. & Arguin, M. The interaction of object form and object meaning in the identification performance of a patient with category-specific visual agnosia. Cogn. Neuropsychol. 14, 1085–1130 (1997).

    Article  Google Scholar 

  116. Dixon, M. J., Bub, D. N., Chertkow, H. & Arguin, M. Object identification deficits in dementia of the Alzheimer type: combined effects of semantic and visual proximity. J. Int. Neuropsychol. Soc. 5, 330–345 (1999).

    Article  CAS  PubMed  Google Scholar 

  117. Zevin, J. D. & Seidenberg, M. S. Simulating consistency effects and individual differences in nonword naming: a comparison of current models. J. Mem. Lang. 54, 145–160 (2006).

    Article  Google Scholar 

Download references

Acknowledgements

This research was supported by a programme grant from the Medical Research Council (MRC, UK, MR/J004146/1) to M.A.L.R. and by a University Fellowship from UW-Madison to L.C. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank L. Cloutman for assisting with the tractography analysis and R. Ishibashi for assisting with the ALE analysis.

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Authors and Affiliations

  1. Department of Psychology, University of Wisconsin-Madison, 1202 West Johnson Street, Madison, Wisconsin 53705, USA

    Lang Chen & Timothy T. Rogers

  2. Stanford Cognitive and Systems Neuroscience Laboratory, 1070 Arastradero Road Suite 220, Palo Alto, California 94304, USA

    Lang Chen

  3. Division of Neuroscience and Experimental Psychology, Neuroscience and Aphasia Research Unit (NARU), School of Biological Sciences, University of Manchester, M13 9PL, UK

    Matthew A. Lambon Ralph

Authors
  1. Lang Chen
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  2. Matthew A. Lambon Ralph
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  3. Timothy T. Rogers
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Contributions

All authors contributed to the entire process of this project, including project planning, experiment work, data analysis and writing the paper.

Corresponding authors

Correspondence to Lang Chen, Matthew A. Lambon Ralph or Timothy T. Rogers.

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Competing interests

The authors declare no competing interests.

Supplementary information

Supplementary Information

Supplementary Figures 1–8, Supplementary tables 1–7, Supplementary Discussion, Supplementary Methods, Supplementary References (PDF 3425 kb)

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Chen, L., Lambon Ralph, M. & Rogers, T. A unified model of human semantic knowledge and its disorders. Nat Hum Behav 1, 0039 (2017). https://doi.org/10.1038/s41562-016-0039

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