Semantic processing in older adults is associated with distributed neural activation which varies by association and abstractness of words

Paivio A. Mental representations: a dual coding approach. New York: Oxford University Press; 1985.

Google Scholar 

Doboli A, Umbarkar A, Doboli S, Betz J. Modeling semantic knowledge structures for creative problem solving: studies on expressing concepts, categories, associations, goals and context. Knowl-Based Syst. 2015;78:34–50.

Article  Google Scholar 

Nelson DL, McEvoy CL, Schreiber TA. The University of South Florida free association, rhyme, and word fragment norms. Behav Res Methods Instrum Comput. 2004;36(3):402–7.

Article  PubMed  Google Scholar 

Troche J, Crutch S, Reilly J. Clustering, hierarchical organization, and the topography of abstract and concrete nouns. Front Psychol. 2014;5:360.

Article  PubMed  PubMed Central  Google Scholar 

Yap MJ, Tan SE, Pexman PM, Hargreaves IS. Is more always better? Effects of semantic richness on lexical decision, speeded pronunciation, and semantic classification. Psychon Bull Rev. 2011;18(4):742–50.

Article  PubMed  Google Scholar 

Cieutat. Association indices for 446 randomly selected English monosyllables, bisyllables, and trisyllables. J Verbal Learn Verbal Behav. 1963;2(2):176–85.

Crutch SJ. Qualitatively different semantic representations for abstract and concrete words: further evidence from the semantic reading errors of deep dyslexic patients. Neurocase. 2006;12(2):91–7.

Article  PubMed  Google Scholar 

Crutch SJ, Connell S, Warrington EK. The different representational frameworks underpinning abstract and concrete knowledge: evidence from odd-one-out judgements. Q J Exp Psychol (Hove). 2009;62(7):1377-88–1388.

PubMed  Google Scholar 

Crutch SJ, Warrington EK. Gradients of semantic relatedness and their contrasting explanations in refractory access and storage semantic impairments. Cogn Neuropsychol. 2005;22(7):851–76.

Article  PubMed  Google Scholar 

Crutch SJ, Warrington EK. Abstract and concrete concepts have structurally different representational frameworks. Brain. 2005;128(Pt 3):615–27.

Article  PubMed  Google Scholar 

Crutch SJ, Warrington EK. The differential dependence of abstract and concrete words upon associative and similarity-based information: complementary semantic interference and facilitation effects. Cogn Neuropsychol. 2010;27(1):46–71.

Article  PubMed  Google Scholar 

Montefinese M. Semantic representation of abstract and concrete words: a minireview of neural evidence. J Neurophysiol. 2019;121(5):1585–7.

Article  PubMed  Google Scholar 

Meteyard L, Cuadrado SR, Bahrami B, Vigliocco G. Coming of age: a review of embodiment and the neuroscience of semantics. Cortex. 2012;48(7):788–804.

Article  PubMed  Google Scholar 

McClelland JL, Rumelhart DE. Explorations in parallel distributed processing: a handbook of models, programs, and exercises. Cambridge, Mass.: MIT Press; 1989. ix, pp. 355.

Rumelhart DE, McClelland JL, University of California San Diego. PDP Research Group. Parallel distributed processing: explorations in the microstructure of cognition. Cambridge, Mass.: MIT Press; 1986.

Hillis AE, Caramazza A. Cognitive and neural mechanisms underlying visual and semantic processing: implications from “optic aphasia.” J Cogn Neurosci. 1995;7(4):457–78.

Article  PubMed  CAS  Google Scholar 

Hillis AE, Caramzza A. The compositionality of lexical semantic representations: clues from semantic errors in object naming. Memory. 1995;3(3–4):333–58.

Article  PubMed  CAS  Google Scholar 

Cloutman L, Gottesman R, Chaudhry P, Davis C, Kleinman JT, Pawlak M, et al. Where (in the brain) do semantic errors come from? Cortex. 2009;45(5):641–9.

Article  PubMed  Google Scholar 

Patterson K, Nestor PJ, Rogers TT. Where do you know what you know? The representation of semantic knowledge in the human brain. Nat Rev Neurosci. 2007;8(12):976–87.

Article  PubMed  CAS  Google Scholar 

Jackson RL, Bajada CJ, Rice GE, Cloutman LL, Lambon Ralph MA. An emergent functional parcellation of the temporal cortex. Neuroimage. 2018;170:385–99.

Article  PubMed  Google Scholar 

Jefferies E. The neural basis of semantic cognition: converging evidence from neuropsychology, neuroimaging and TMS. Cortex. 2013;49(3):611–25.

Article  PubMed  Google Scholar 

Ralph MA, Jefferies E, Patterson K, Rogers TT. The neural and computational bases of semantic cognition. Nat Rev Neurosci. 2017;18(1):42–55.

Article  PubMed  CAS  Google Scholar 

Mineroff Z, Blank IA, Mahowald K, Fedorenko E. A robust dissociation among the language, multiple demand, and default mode networks: evidence from inter-region correlations in effect size. Neuropsychologia. 2018;119:501–11.

Article  PubMed  PubMed Central  Google Scholar 

Smith V, Duncan J, Mitchell DJ. Roles of the default mode and multiple-demand networks in naturalistic versus symbolic decisions. J Neurosci. 2021;41(10):2214–28.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Wang X, Gao Z, Smallwood J, Jefferies E. Both default and multiple-demand regions represent semantic goal information. J Neurosci. 2021;41(16):3679–91.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Hodgson VJ, Lambon Ralph MA, Jackson RL. Multiple dimensions underlying the functional organization of the language network. Neuroimage. 2021;241:118444.

Article  PubMed  Google Scholar 

Shallice T, Cooper RP. Is there a semantic system for abstract words? Front Hum Neurosci. 2013;7:175.

Article  PubMed  PubMed Central  Google Scholar 

Binder JR, Westbury CF, McKiernan KA, Possing ET, Medler DA. Distinct brain systems for processing concrete and abstract concepts. J Cogn Neurosci. 2005;17(6):905–17.

Article  PubMed  CAS  Google Scholar 

Noppeney U, Price CJ. Retrieval of abstract semantics. Neuroimage. 2004;22(1):164–70.

Article  PubMed  Google Scholar 

Sabsevitz DS, Medler DA, Seidenberg M, Binder JR. Modulation of the semantic system by word imageability. Neuroimage. 2005;27(1):188–200.

Article  PubMed  CAS  Google Scholar 

Pexman PM, Hargreaves IS, Edwards JD, Henry LC, Goodyear BG. Neural correlates of concreteness in semantic categorization. J Cogn Neurosci. 2007;19(8):1407–19.

Article  PubMed  Google Scholar 

Badre D, Poldrack RA, Pare-Blagoev EJ, Insler RZ, Wagner AD. Dissociable controlled retrieval and generalized selection mechanisms in ventrolateral prefrontal cortex. Neuron. 2005;47(6):907–18.

Article  PubMed  CAS  Google Scholar 

Noonan KA, Jefferies E, Visser M, Lambon Ralph MA. Going beyond inferior prefrontal involvement in semantic control: evidence for the additional contribution of dorsal angular gyrus and posterior middle temporal cortex. J Cogn Neurosci. 2013;25(11):1824–50.

Article  PubMed  Google Scholar 

Thompson-Schill SL, D’Esposito M, Aguirre GK, Farah MJ. Role of left inferior prefrontal cortex in retrieval of semantic knowledge: a reevaluation. Proc Natl Acad Sci U S A. 1997;94(26):14792–7.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Wang L, Metzak PD, Honer WG, Woodward TS. Impaired efficiency of functional networks underlying episodic memory-for-context in schizophrenia. J Neurosci. 2010;30(39):13171–9.

Article  PubMed  PubMed Central  CAS  Google Scholar 

Whitney C, Kirk M, O’Sullivan J, Lambon Ralph MA, Jefferies E. Executive semantic processing is underpinned by a large-scale neural network: revealing the contribution of left prefrontal, posterior temporal, and parietal cortex to controlled retrieval and selection using TMS. J Cogn Neurosci. 2012;24(1):133–47.

Article  PubMed  Google Scholar 

Binder JR, Desai RH, Graves WW, Conant LL. Where is the semantic system? A critical review and meta-analysis of 120 functional neuroimaging studies. Cereb Cortex. 2009;19(12):2767–96.

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