Neural representation of abstract and concrete concepts: A meta‐analysis of neuroimaging studies

Wang, Jing; Conder, Julie; Blitzer, David; Shinkareva, Svetlana V.

doi:10.1002/hbm.20950

Cited by 387 publications

(434 citation statements)

References 85 publications

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“…In contrast, our set of words included many abstract concepts, such as "justice" and "desire" (see Table S1 for full list). This suggestion is supported by a meta-analysis that contrasted regions involved in abstract versus concrete words, and that found clear evidence that the TP was more active in response to abstract words, whereas ventral temporal regions showed a preference for concrete words (20).…”

Section: Discussionmentioning

confidence: 73%

“…Computational models of semantic cognition propose that concepts are represented by a similarity-based code in an amodal "semantic hub," situated in the apex of the ventral processing stream in the temporal pole (TP) (17,18). Although other regions, such as the temporo-parietal cortex (19), have also been linked to the representation of abstract conceptual knowledge, the TP is most consistently implicated in both patient and neuroimaging studies (17,20,21).These computational models therefore make clear predictions about the expected neural basis of semantic false memory. Namely, the TP semantic hub should contain a similarity-based code, such that the neural representations of DRM words reflect the known semantic relatedness between those words.…”

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confidence: 99%

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Semantic representations in the temporal pole predict false memories

Chadwick

Anjum

Kumaran

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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Recent advances in neuroscience have given us unprecedented insight into the neural mechanisms of false memory, showing that artificial memories can be inserted into the memory cells of the hippocampus in a way that is indistinguishable from true memories. However, this alone is not enough to explain how false memories can arise naturally in the course of our daily lives. Cognitive psychology has demonstrated that many instances of false memory, both in the laboratory and the real world, can be attributed to semantic interference. Whereas previous studies have found that a diverse set of regions show some involvement in semantic false memory, none have revealed the nature of the semantic representations underpinning the phenomenon. Here we use fMRI with representational similarity analysis to search for a neural code consistent with semantic false memory. We find clear evidence that false memories emerge from a similarity-based neural code in the temporal pole, a region that has been called the "semantic hub" of the brain. We further show that each individual has a partially unique semantic code within the temporal pole, and this unique code can predict idiosyncratic patterns of memory errors. Finally, we show that the same neural code can also predict variation in true-memory performance, consistent with an adaptive perspective on false memory. Taken together, our findings reveal the underlying structure of neural representations of semantic knowledge, and how this semantic structure can both enhance and distort our memories.false memory | semantic | temporal pole | fMRI | pattern similarity E ach of us has a vast store of semantic knowledge that we apply to incoming sensory data to extract meaning from the world around us. Semantic representations are capable of capturing important structural features of the world at many different levels of abstraction, which allows for rapid and flexible responses to a diverse array of environmental challenges. This preexisting knowledge structure guides ongoing cognition, which usually aids performance, but under some circumstances can lead us into error (1-3). A striking example is the widely studied DRM (Deese, Roediger, and McDermott) false-memory illusion (4, 5). In a typical DRM task, subjects are asked to memorize a set of words such as "snow," "winter," "ice," and "warm." After a delay, subjects will typically falsely remember having seen the semantically related word "cold." It is widely agreed that this memory illusion is driven by the semantic relatedness between words contained in the encoding list (e.g., "snow") and falsely remembered words that were not actually presented (e.g., "cold"). As such, it is thought that each list item automatically, but weakly, activates the semantically related concept (Fig. 1A). This activation leads to memory confusion, either through a cumulative priming of the related lure (5, 6) or the encoding of the semantic overlap as a "gist" memory (3), resulting in a false memory unless the error is detected by some internal monitoring p...

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Section: Discussionmentioning

confidence: 73%

mentioning

confidence: 99%

Semantic representations in the temporal pole predict false memories

Chadwick

Anjum

Kumaran

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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“…Lieberman, 2012a,b;Spunt and Adolphs, 2014). These regions partially overlap with several meta-analytically defined functional networks, including: (i) the so-called 'theory-of-mind' or 'mentalizing' network associated with tasks of mental-state reasoning (Gallagher and Frith, 2003;Amodio and Frith, 2006;Saxe, 2006;Carrington and Bailey, 2009;Van Overwalle and Baetens, 2009;Schurz et al, 2014); (ii) the default mode network (DMN), especially its dorsomedial PFC component (Raichle et al, 2001;Buckner et al, 2008;Andrews-Hanna et al, 2010; (iii) the network associated with mentally simulating episodes both past and future (Hassabis and Maguire, 2007;Spreng et al, 2009;Schacter et al, 2012); (iv) the network associated with comprehending narrative discourse (Ferstl and von Cramon, 2001;Ferstl et al, 2008;Mar, 2011;Nijhof and Willems, 2015); (v) the network associated with transmodal semantic processing (Binder et al, 2009;Binder and Desai, 2011) and (vi) the network associated with comprehending abstract compared to concrete words (Binder et al, 2009;Wang et al, 2010;Binder and Desai, 2011). Decreasing LOAs were associated with the majority of the left hemisphere regions reliably associated with the How > Why contrast in previous work.…”

Section: Brain Regions For Conceptualizing An Action At Different Loasmentioning

confidence: 99%

The neural basis of conceptualizing the same action at different levels of abstraction

Spunt

Kemmerer

Adolphs

2015

Soc Cogn Affect Neurosci

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People can conceptualize the same action (e.g. 'riding a bike') at different levels of abstraction (LOA), where higher LOAs specify the abstract motives that explain why the action is performed (e.g. 'getting exercise'), while lower LOAs specify the concrete steps that indicate how the action is performed (e.g. 'gripping handlebars'). Prior neuroimaging studies have shown that why and how questions about actions differentially activate two cortical networks associated with mental-state reasoning and action representation, respectively; however, it remains unknown whether this is due to the differential demands of the questions per se or to the shifts in LOA those questions produce. We conducted functional magnetic resonance imaging while participants judged pairs of action phrases that varied in LOA and that could be framed either as a why question (Why ride a bike? Get exercise.) or a how question (How to get exercise? Ride a bike.). Question framing (why vs how) had no effect on activity in regions of the two networks. Instead, these regions uniquely tracked parametric variation in LOA, both across and within trials. This suggests that the human capacity to understand actions at different LOA is based in the relative activity of two cortical networks.

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“…However, these regions of the semantic network are recruited differently depending of the type of stimuli that are processed. For instance, differences of activation in ATL and IPC have been reported between concrete and abstract words in neuroimaging studies, using functional magnetic resonance imaging or positron emission topography (Hoffman, Binney, & Lambon Ralph, 2014;Sabsevitz, Medler, Seidenberg, & Binder, 2005;Wang, Conder, Blitzer, & Shinkareva, 2010). Studies on clinical patients, with lesions in regions of the semantic network also showed differences in performance during semantic processing of abstract and concrete words (Loiselle, et al, 2012).…”

Section: Introductionmentioning

confidence: 98%

Neural changes associated with semantic processing in healthy aging despite intact behavioral performance

et al. 2015

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Semantic memory recruits an extensive neural network including the left inferior prefrontal cortex (IPC) and the left temporoparietal region, which are involved in semantic control processes, as well as the anterior temporal lobe region (ATL) which is considered to be involved in processing semantic information at a central level. However, little is known about the underlying neuronal integrity of the semantic network in normal aging. Young and older healthy adults carried out a semantic judgment task while their cortical activity was recorded using magnetoencephalography (MEG). Despite equivalent behavioral performance, young adults activated the left IPC to a greater extent than older adults, while the latter group recruited the temporoparietal region bilaterally and the left ATL to a greater extent than younger adults. Results indicate that significant neuronal changes occur in normal aging, mainly in regions underlying semantic control processes, despite an apparent stability in performance at the behavioral level.

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Neural representation of abstract and concrete concepts: A meta‐analysis of neuroimaging studies

Cited by 387 publications

References 85 publications

Semantic representations in the temporal pole predict false memories

Semantic representations in the temporal pole predict false memories

The neural basis of conceptualizing the same action at different levels of abstraction

Neural changes associated with semantic processing in healthy aging despite intact behavioral performance

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