been observed in functional imaging studies of categorization at different levels of specificity (Rogers et al., 2005).
One way of bypassing such problems is to assess semantic memory with words rather than pictorial stimuli. Words do not have the same visual confounds as images, and it is much easier to control for other confounding factors such as familiarity (which can be estimated by word‐frequency counts in large corpora) and specificity (since each word is intrinsically tied to a particular level of specificity). Although a few studies employing words as stimuli have indeed yielded results consistent with the many‐hubs view (e.g., Mahon et al., 2009), such evidence appears to be relatively rare. A meta‐analysis focusing exclusively on studies that used well‐controlled word stimuli found no significant differences contrasting animals and manmade objects (Binder et al., 2009). Other meta‐analyses have failed to find consistent evidence for category‐specific activation even when including studies that employed pictorial stimuli (Joseph, 2001). Given these null results and the many potential confounding factors in the existing literature, the importance of category‐specificity for theories about the gross architecture of the semantic network remains unclear.
pathology, and will be most likely to elicit strong anterior temporal activation in neuroimaging studies.
If this view is generally correct, we are left with two remaining issues. The first per- tains to questions about semantic access, retrieval, or control. To this point we have written as though processing of a word, image, or other stimulus automatically engages a broad network of associations across other stimulus modalities, with the item’s meaning inhering in the total operation of the full network. But this character- ization is certainly incorrect: in any given situation, only a restricted part of our full complement of knowledge is ever relevant to the task at hand, and indeed the task itself frequently constrains what information is relevant or important (Barsalou, 1982). Thus most people will generally agree that the ability to produce music is an important feature of a piano, but when helping a friend move, this property seems less salient than the piano’s weight. We have focused on the architecture of the cortical network that encodes knowledge about the associations among various kinds of sensory, motor, and linguistic representations, but have not discussed the systems involved in the interrogation of this knowledge base.
A full accounting of this interesting question would require its own review. Here we will briefly note that there is increasing evidence of a role for frontoparietal networks in the “control” of activation in the semantic network (for more discussion of con- trolled memory retrieval processes, see Chapter 7). Thompson‐Schill et al. (1997) have shown that the dorsolateral prefrontal cortex becomes more strongly engaged in semantic tasks that require the participant to resolve the competition amongst many potential responses. For instance, when asked to generate the action associated with an object, this region responds more strongly to items for which there are many correct responses (e.g., “computer”) than for items for which there is just one (e.g.,
“paintbrush”). Others have reported similar findings, and there is continuing debate regarding how such patterns are best interpreted (see, e.g., Badre and Wagner, 2002).
One hypothesis, in keeping with a broad literature on cognitive control more gener- ally (Cohen, Aston‐Jones, and Gilzenrat, 2004), is that representations in prefrontal cortex (and other parts of the executive system) serve to constrain or “guide” the flow of activation in the cortical semantic network, so that only those sensory‐motor rep- resentations relevant to the task at hand become activated. This view accords well with the early observations of Martin et al. (1995) that cortical regions associated with a particular property type (e.g., color, motion) activate more strongly when the partic- ipant must retrieve information about the corresponding property.
It also aligns with recent neuropsychological evidence from patients with semantic aphasia (SA) – a form of cross‐modal semantic impairment arising from cerebrovas- cular accidents in left hemisphere frontal and parietal regions (Jefferies and Lambon Ralph, 2006). Semantic impairments in SA differ qualitatively from those observed in SD, and in many cases the differences are consistent with the view that patients with SA are unable to select or resolve the competition amongst various alternative responses. For instance, patients with SA have a harder time understanding words whose meanings vary across linguistic contexts (Hoffman, Rogers, and Lambon Ralph, 2011), benefit from phonological cueing and from other contextual cues that constrain the range of possible responses (Jefferies, Patterson, and Lambon Ralph, 2008), and are less affected by the psycholinguistic factors that strongly influence performance in SD (Jefferies and Lambon Ralph, 2006). These deficits can be caused
by damage either to prefrontal or to parietal cortex in the left hemisphere, and the different loci appear to produce remarkably similar impairments, raising the possibility that both frontal and parietal regions operate together as part of a “semantic control”
system (Noonan et al., 2010).
The second issue concerns a question hinted at in the introduction: What are we to make of words like “piety,” whose meanings are not clearly associated with sensory‐motor states? This is a pressing question for any grounded approach to meaning that we will not solve in this chapter. We will note, however, that the neu- roanatomical perspective in this review may provide a clue towards the beginnings of an answer. The clue lies in the existence of the ATL hub. Earlier we suggested that such a hub might be needed to represent the conceptual similarity structure that governs generalization, and that is not captured by sensory, motor, or linguistic rep- resentations taken independently. Computer simulations have shown that neural net- works can acquire knowledge of such structure through learning the associations among many different kinds of properties – but only when the network architecture is convergent: there must be a single region that contributes to the representation and processing of all kinds of information across all varieties of inputs and outputs (Rogers and McClelland, 2004). With such a region, the network is capable of detecting patterns of systematic high‐order covariation across various inputs and out- puts, and of constructing internal representations that efficiently exploit such struc- ture, including representations whose similarities differ substantially from those expressed in each input modality taken independently (Rogers et al., 2004a). Indeed, it has been shown that such an architecture is capable of learning completely abstract relationships – that is, the network can represent items as similar when they relate to other entities in similar ways, even if they share no properties at all in common (Rogers and McClelland, 2008). In contrast, if the same associations among the same properties are encoded across multiple different pathways, the network loses the ability to detect and exploit high‐order covariation, and thus fails to acquire rep- resentations that express abstract conceptual structure. Such simulations thus sug- gest that the single‐hub architecture may be necessary in order for people to learn abstract conceptual structure. Although this hypothesis provides a promising starting point, it is clear there is a long way to go before we resolve Euthyprho’s argument with Socrates.
References
Acosta‐Cabronero, J., Patterson, K., Fryer, T., et al. (2011). Atrophy, hypometabolism and white matter abnormalities in semantic dementia tell a coherent story. Brain, 134 (7), 2025–2035.
Adlam, A.‐L., Patterson, K., Rogers, T.T., et al. (2006). Semantic dementia and fluent primary progressive aphasia: two sides of the same coin? Brain, 129, 3066–3080.
Badre, D., and Wagner, A. (2002). Semantic retrieval, mnemonic control, and prefrontal cortex. Behavioral and Cognitive Neuroscience Reviews, 1 (3), 206–218.
Barsalou, L.W. (1982). Context‐independent and context‐dependent information in concepts.
Memory and Cognition, 10, 82–93.
Barsalou, L.W. (2008). Grounded cognition. Anuual Review of Psychology, 59, 617–645.
Barsalou, L.W., Simmons, W.K., Barbey, A., and Wilson, C.D. (2003). Grounding conceptual knowledge in modality‐specific systems. Trends in Cognitive Sciences, 7 (2), 84–91.
Binder, J.R., Desai, R.H., Graves, W.W., and Conant, L.L. (2009). Where is the semantic system? A critical review and meta‐analysis of 120 functional neuroimaging studies.
Cerebral Cortex, 19 (12), 2767–2796. doi: 10.1093/cercor/bhp055.
Binkofski, F., and Buxbaum, L.J. (2013). Two action systems in the human brain. Brain and Language, 127 (2), 222–229. doi: 10.1016/j.bandl.2012.07.007.
Binney, R.J., Embleton, K.V., Jefferies, E., et al. (2010). 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. Cerebral Cortex, 20 (11), 2728–2738. doi: 10.1093/cercor/bhq019.
Boronat, C.B., Buxbaum, L.J., Coslett, H.B., et al. (2005) Distinctions between manipulation and function knowledge of objects: evidence from functional magnetic resonance imaging.
Brain Research Cognitive Brain Research, 23 (2–3), 361–373. doi: 10.1016/j.cogbrainres.
2004.11.001.
Bozeat, S., Lambon Ralph, M.A., Patterson, K., et al. (2000). Nonverbal semantic impairment in semantic dementia. Neuropsychologia, 38, 1207–1215.
Brambati, S.M., Myers, D., Wilson, A., et al. (2006). The anatomy of category‐specific object naming in neurodegenerative diseases. Journal of Cognitive Neuroscience, 18, 1644–53.
doi: 10.1162/jocn.2006.18.10.1644.
Buxbaum, L.J. (2001). Ideomotor apraxia: a call to action. Neurocase, 7(6), 445–458.
doi: 10.1093/neucas/7.6.445.
Buxbaum, L.J., and Saffran, E.M. (2002). Knowledge of object manipulation and object function: dissociations in apraxic and nonapraxic subjects. Brain and Language, 82 (2), 179–199.
Buxbaum, L.J., Veramontil, T., and Schwartz, M.F. (2000). Function and manipulation tool knowledge in apraxia: knowing ‘what for’ but not ‘how’. Neurocase, 6 (2), 83–97.
doi: 10.1080/13554790008402763.
Caine, D. (2004). Posterior cortical atrophy: a review of the literature. Neurocase, 10 (5), 382–385. doi: 10.1080/13554790490892239.
Campanella, F., D’Agostini, S., Skrap, M., and Shallice, T. (2010). Naming manipulable objects: anatomy of a category specific effect in left temporal tumours. Neuropsychologia, 48 (6), 1583–1597. doi: 10.1016/j.neuropsychologia.2010.02.002.
Chan, A.M., Baker, J.M. Eskandar, E., et al. (2011). First‐pass selectivity for semantic categories in human anteroventral temporal lobe. Journal of Neuroscience: the Official Journal of the Society for Neuroscience, 31 (49), 18119–18129. doi: 10.1523/JNEUROSCI.3122‐11.2011.
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 (10), 913–919.
Chao, L.L., and Martin, A. (1999). Cortical regions associated with perceiving, naming, and knowing about colors. Journal of Cognitive Neuroscience, 11 (1), 25–35.
Chouinard, P.A., and Goodale, M.A. (2010). Category‐specific neural processing for naming pictures of animals and naming pictures of tools: an ALE meta‐analysis. Neuropsychologia, 48 (2), 409–418. doi: 10.1016/j.neuropsychologia.2009.09.032.
Cohen, J.D., Aston‐Jones, G., and Gilzenrat, M.S. (2004). A systems‐level perspective on attention and cognitive control. In Cognitive Neuroscience of Attention (ed. M.I. Posner).
New York, NY: Guilford Press, pp. 71–90.
Coltheart, M. (2004). Are there lexicons? Quarterly Journal of Experimental Psychology, 57 (7), 1153–1171.
Coppens, P., and Frisinger, D. (2005). Category‐specific naming effect in non‐brain‐damaged individuals. Brain and Language, 94 (1), 61–71. doi: 10.1016/j.bandl.2004.11.008.
Damasio, A.R. (1989). The brain binds entities and events by multiregional activation from convergence zones. Neural Computation, 1, 123–132.
Damasio, H., Grabowski, T.J., Tranel, D., and Hichwa, R.D. (1996). A neural basis for lexical retrieval. Nature, 380 (6574), 499–505.
Eggert, G. H. (1977). Wernicke’s Works on Aphasia: A Sourcebook and Review. Vol. 1. The Hague: Mouton.
Farah, M. J. (1990). Visual Agnosia. Cambridge, MA: MIT Press.
Funnell, E., and Sheridan, J. (1992). Categories of knowledge? Unfamiliar aspects of living and nonliving things. Cognitive Neuropsychology, 9 (2), 135–153. doi: 10.1080/
02643299208252056.
Gainotti, G. (2000). What the locus of brain lesion tells us about the nature of the cognitive defect underlying category‐specific disorders: a review. Cortex, 36 (4), 539–559.
doi: 10.1016/S0010‐9452(08)70537‐9.
Gainotti, G., Silveri, M.C., Daniele, A., and Giustoli, L. (1995). Neuroanatomical correlates of category‐specific semantic disorders: a critical survey. Memory, 3 (3/4), 247–264.
Gauthier, I., Anderson, A.W. Tarr, M.J., et al. (1997). Levels of categorization in visual recog- nition studied with functional MRI. Current Biology, 7, 645–651.
Glenberg, A.M. (2010). Embodiment as a unifying perspective for psychology. Wiley Interdisciplinary Reviews: Cognitive Science, 1 (4), 586–596. doi: 10.1002/wcs.55.
Glenberg, A.M., and Kaschak, M.P. (2002). Grounding language in action. Psychonomic Bulletin and Review, 9 (3), 558–565. doi: 10.3758/BF03196313.
Goodale, M.A., and Milner, A.D. (1992). Separate visual pathways for perception and action.
Trends in Neurosciences, 15 (1), 20–25. doi: 10.1016/0166‐2236(92)90344‐8.
Gorno‐Tempini, M., and Price, C. (2001). Identification of famous faces and buildings: a functional neuroimaging study of semantically unique items. Brain, 124 (10), 2087–2097.
Gorno‐Tempini, M., Price, C., Rudge, P., and Cipolotti, L. (2001). Identification without naming: a functional neuroimaging study of an anomic patient. Journal of Neurology, Neurosurgery and Psychiatry, 70 (3), 397–400.
Grabowski, T.J., Damasio, H., Tranel, D., et al. (2001). A role for left temporal pole in the retrieval of words for unique entities. Human Brain Mapping, 13 (4), 199–212.
Hauk, O., Johnsrude, I., and Pulvermüller, F. (2004). Somatotopic representation of action words in human motor and premotor cortex. Neuron, 41 (2), 301–307. doi: 10.1016/
S0896‐6273(03)00838‐9.
Hodges, J.R., Bozeat, S., Patterson, K., and Spatt, J. (2000). The role of conceptual knowledge in object use evidence from semantic dementia. Brain 123, 1913–1925.
Hodges, J.R., Garrard, P., Perry, R., et al. (1999). The differentiation of semantic dementia and frontal lobe dementia from early Alzheimer’s disease: a comparative neuropsychological study. Neuropsychology, 13, 31–40.
Hodges, J.R., Graham, N., and Patterson, K. (1995). Charting the progression in semantic dementia: implications for the organisation of semantic memory. Memory, 3, 463–495.
Hoffman, P., Rogers, T.T., and Lambon Ralph, M.A. (2011). Semantic diversity accounts for the ‘missing’ word frequency effect in stroke aphasia: insights using a novel method to quantify contextual variability in meaning. Journal of Cognitive Neuroscience, 23 (9), 2432–2446. doi: 10.1162/jocn.2011.21614.
Humphreys, G.W., and Forde, E.M. (2001). Hierarchies, similarity, and interactivity in object‐
recognition: on the multiplicity of `category‐specific’ deficits in neuropsychological popu- lations. Behavioral and Brain Sciences, 24 (3), 453–509.
Jefferies, E., and Lambon Ralph, M.A. (2006). Semantic impairment in stroke aphasia versus semantic dementia: a case‐series comparison. Brain 129, 2132–2147.
Jefferies, E., Patterson, K., and Lambon Ralph, M.A. (2008). Deficits of knowledge versus executive control in semantic cognition: insights from cued naming. Neuropsychologia, 46 (2), 649–658. doi: 10.1016/j.neuropsychologia.2007.09.007.
Joseph, J.E. (2001). Functional neuroimaging studies of category specificity in object recogni- tion: a critical review and meta‐analysis. Cognitive, Affective and Behavioral Neuroscience, 1 (2), 119–136.
Kalénine, S., Buxbaum, L.J., and Coslett, H.B. (2010). Critical brain regions for action recog- nition: lesion symptom mapping in left hemisphere stroke. Brain, 133 (11), 3269–3280.
doi: 10.1093/brain/awq210.
Kellenbach, M., Brett, M., and Patterson, K. (2001). Large, colorful or noisy? Attribute‐ and modality‐specific activations during retrieval of perceptual attribute knowledge. Cognitive, Affective and Behavioral Neuroscience, 1 (3), 207–221.
Lambon Ralph, M.A., Lowe, C., and Rogers, T.T. (2007). Neural basis of category‐specific semantic deficits for living things: evidence from semantic dementia, HSVE and a neural network model. Brain, 130, 1127–1137.
Lambon Ralph, M.A., McClelland, J.L. Patterson, K., et al. (2001). No right to speak? The relationship between object naming and semantic impairment: neuropsychological evi- dence and a computational model. Journal of Cognitive Neuroscience, 13, 341–356.
Laurence, S., and Margolis, E. (1999). Concepts and cognitive science. In Concepts: Core Readings (ed. E. Margolis and S. Laurence). Boston, MA: MIT Press, pp. 3–81.
Luzzi, S., Snowden, J.S., Neary, D., et al. (2007). Distinct patterns of olfactory impairment in Alzheimer’s disease, semantic dementia, frontotemporal dementia, and corticobasal degeneration. Neuropsychologia, 45 (8), 1823–1831. doi: 10.1016/j.neuropsychologia.
2006.12.008.
Mahon, B.Z., Anzellotti, S., Schwarzbach, J., et al. (2009). Category‐specific organization in the human brain does not require visual experience. Neuron, 63 (3), 397–405.
doi: 10.1016/j.neuron.2009.07.012.
Mahon, B.Z., Schwarzbach, J., and Caramazza, A. (2010). The representation of tools in left parietal cortex is independent of visual experience. Psychological Science, 21 (6), 764–771.
doi: 10.1177/0956797610370754.
Martin, A., and Chao, L.L. (2001). Semantic memory in the brain: structure and processes.
Current Opinion in Neurobiology, 11, 194–201.
Martin, A., Haxby, J.V., Lalonde, F.M., et al. (1995). Discrete cortical regions associated with knowledge of color and knowledge of action. Science, 270, 102–105.
Martin, A., Wiggs, C., Ungerleider, L., and Haxby, J.V. (1996). Neural correlates of category‐
specific knowledge. Nature, 379, 649–652.
McCarthy, R., and Warrington, E.K. (1986). Visual associative agnosia: a clinico‐anatomical study of a single case. Journal of Neurology, Neurosurgery and Psychiatry, 49, 1233–1240.
Mesulam, M.M. (2001). Primary progressive aphasia. Annals of Neurology, 49 (4), 425–432.
doi: 10.1002/ana.91.
Mesulam, M.M., Grossman, M., Hillis, A., et al. (2003). The core and halo of primary progres- sive aphasia and semantic dementia. Annals of Neurology, 54 (suppl. 5), S11–S14.
Mesulam, M.M., Wieneke, C., Hurley, R., et al. (2013). Words and objects at the tip of the left temporal lobe in primary progressive aphasia. Brain, 136 (2), 601–618. doi: 10.1093/
brain/aws336.
Mion, M., Patterson, K., Acosta‐Cabronero, J., et al. (2010). What the left and right fusiform gyri tell us about semantic memory. Brain 133, 3256–3268.
Moss, H.E., Rodd, J.M., Stamatakis, E.A., et al. (2005). Anteromedial temporal cortex sup- ports fine grained differentiation among objects. Cerebral Cortex, 15, 626–627.
Mummery, C.J., Patterson, K., Price, C.J., et al. (2000). A voxel‐based morphometry study of semantic dementia: relationship between temporal lobe atrophy and semantic memory.
Annals of Neurology, 47 (1), 36–45.
Nestor, P.J., Fryer, T.D., and Hodges, J.R. (2006). Declarative memory impairments in Alzheimer’s disease and semantic dementia. NeuroImage, 30, 1010–1020.
Noonan, K.A., Jefferies, E., Corbett, F., and Lambon Ralph, M.A. (2010). Elucidating the nature of deregulated semantic cognition in semantic aphasia: evidence for the roles of prefrontal and temporo‐parietal cortices. Journal of Cognitive Neuroscience, 22 (7), 1597–1613.
Noppeney, U., Nagaraja, S.S., Tyler, L.K., et al. (2007). Temporal lobe lesions and semantic impairment: a comparison of herpes simplex virus encephalitis and semantic dementia.
Brain, 130 (4), 1138–1147.
Ochipa, C., Rothi, L.J. and Heilman, K.M. (1989). Ideational apraxia: a deficit in tool selection and use. Annals of Neurology, 25 (2), 190–193. doi: 10.1002/ana.410250214.
Oliveri, M., Finocchiaro, C., Shapiro, K., et al. (2004). All talk and no action: a transcranial magnetic stimulation study of motor cortex activation during action word produc- tion. Journal of Cognitive Neuroscience, 16 (3), 374–381. doi: 10.1162/
089892904322926719.
Patterson, K., Nestor, P. J., and Rogers, T.T. (2007). Where do you know what you know? The representation of semantic knowledge in the human brain. Nature Reviews Neuroscience, 8, 976–987.
Plaut, D.C. (2002). Graded modality‐specific specialisation in semantics: a computational account of optic aphasia. Cognitive Neuropsychology, 19 (7), 603–639.
Pobric, G., Jefferies, E., and Lambon Ralph, M.A. (2007). Anterior temporal lobes mediate semantic representation: mimicking semantic dementia by using rTMS in normal partici- pants. Proceedings of the National Academy of Sciences of the USA, 104 (50), 20137–20141.
doi: 10.1073/pnas.0707383104.
Pobric, G., Jefferies, E., and Lambon Ralph, M.A. (2010). Category‐specific versus category‐
general semantic impairment induced by transcranial magnetic stimulation. Current Biology, 20 (10), 964–968. doi: 10.1016/j.cub.2010.03.070.
Rogers, T.T., Hocking, J., Mechelli, A., et al. (2005). Fusiform activation to animals is driven by the process, not the stimulus. Journal of Cognitive Neuroscience (173), 434–445.
Rogers, T.T., Ivanoiu, A., Patterson, K., and Hodges, J.R. (2006). Semantic memory in Alzheimer’s disease and the fronto‐temporal dementias: a longitudinal study of 236 patients. Neuropsychology, 20 (3), 319–335.
Rogers, T.T., Lambon Ralph, M.A., Garrard, P., et al. (2004a). The structure and deterioration of semantic memory: a computational and neuropsychological investigation. Psychological Review, 111 (1), 205–235.
Rogers, T.T., Lambon Ralph, M.A., Hodges, J.R., and Patterson, K. (2003). Object recogni- tion under semantic impairment: the effects of conceptual regularities on perceptual decisions. Language and Cognitive Processes, 18 (5/6), 625–662.
Rogers, T.T., Lambon Ralph, M.A., Hodges, J.R., and Patterson, K. (2004b). Natural selec- tion: the impact of semantic impairment on lexical and object decision. Cognitive Neuropsychology, 21 (2–4), 331–352.
Rogers, T.T., and McClelland, J.L. (2004). Semantic Cognition: A Parallel Distributed Processing Approach. Cambridge, MA: MIT Press.
Rogers, T.T., and McClelland, J.L. (2008). A Simple model from a powerful framework that spans levels of analysis. Behavioral and Brain Sciences, 31, 729–749.
Rogers, T.T., and Patterson, K. (2007). Object categorization: reversals and explanations of the basic‐level advantage. Journal of Experimental Psychology: General, 136 (3), 451–469.
Rogers, T.T., Patterson, K., and Graham, K. (2007). Colour knowledge in semantic dementia:
it’s not all black and white. Neuropsychologia, 45, 3285–3298.
Rudrauf, D., Mehta, S., Bruss, J., et al. (2008). Thresholding lesion overlap difference maps:
application to category‐related naming and recognition deficits. NeuroImage, 41 (3), 970–984.
Schapiro, A.C., McClelland, J.L., Welbourne, S.R., et al. (2013). Why bilateral damage is worse than unilateral damage to the brain. Journal of Cognitive Neuroscience, 25 (12), 2107–2123.
Schwartz, M.F., Montgomery, M.W., Buxbaum, L.J., et al. (1998). Naturalistic action impair- ment in closed head injury. Neuropsychology, 12 (1), 13–28.
Stewart, F., Parkin, A.J., and Hunkin, N.M. (1992). Naming impairments following recovery from herpes simplex encephalitis: category‐specific? Quarterly Journal of Experimental Psychology Section A, 44 (2), 261–284. doi: 10.1080/02724989243000037.
Thompson Schill, S.L., D’Esposito, M., Aguirre, G.K., and Farah, M.J. (1997). Role of left inferior prefrontal cortex in retrieval of semantic knowledge: a reevaluation. Proceedings of the National Academy of Sciences of the USA, 94, 14792–14797.
Tranel, D., Damasio, H. and Damasio, A.R. (1997). A neural basis for the retrieval of conceptual knowledge. Neuropsychologia, 35 (10), 1319–1327.
Visser, M., Jefferies, E., and Lambon Ralph, M.A. (2010). Semantic processing in the anterior temporal lobes: a meta‐analysis of the functional neuroimaging literature. Journal of Cognitive Neuroscience, 22 (6), 1083–1094.
Warrington, E.K., and Shallice, T. (1984). Category specific semantic impairments. Brain, 107, 829–854.
The Wiley Handbook on the Cognitive Neuroscience of Memory, First Edition.
Edited by Donna Rose Addis, Morgan Barense, and Audrey Duarte.
© 2015 John Wiley & Sons, Ltd. Published 2015 by John Wiley & Sons, Ltd.
Encoding and Retrieval in Episodic Memory
Insights from fMRI
Michael D. Rugg, Jeffrey D. Johnson, and Melina R. Uncapher
5
Introduction
In this chapter we review evidence from functional magnetic resonance imaging (fMRI) studies relevant to the question of how episodic memories are encoded and retrieved, and how encoding and retrieval are related. We outline a theoretical frame- work that has guided much of the research conducted in these areas in the past few years and provide a selective review of relevant studies, focusing largely on findings pertaining to the cerebral cortex outside the medial temporal lobe (MTL). More exhaustive reviews of this literature can be found in the meta‐analyses of Kim (2010, 2011). Detailed discussion of the specific functional roles of the hippocampus and adjacent MTL regions in episodic memory is beyond the scope of the present chapter (see, for example, Davachi, 2006; Diana, Yonelinas, and Ranganath, 2007; Montaldi et al., 2006; Squire, Wixted, and Clark, 2007; see also Chapter 6).
Our use of the term episodic memory refers to memories for unique events, that is, events that are individuated by their contexts, such as where you parked your car today rather than yesterday (Tulving, 1983). A key feature of episodic memories is their associational nature, such that different elements of an event are bound together in memory; in the example above, remembering where your car is currently parked depends on retrieval of associations between the act of parking the car, the location of the act, and when it occurred (see Chapter 18). Episodic memory can be contrasted with two other kinds of explicit (conscious) memory in which contextual associations play little or no role. Semantic memory supports general knowledge that is acquired through repeated exposure to the same information in a variety of different contexts, such that the information becomes largely decontextualized (see Chapter 4). Similarly, a sense of familiarity can support simple judgments of recognition memory, but provides no access to contextual or other qualitative information about the prior event (e.g., Yonelinas, 2002).
Before outlining the theoretical framework that links encoding and retrieval, we briefly define what we mean by these terms. Encoding refers to the processes that are