The Neurobiology of Semantic Memory

By Jeffrey R. Binder, Rutvik H. Desai. Trends in Cognitive Sciences, 2011

1,897 citations recorded by the source corpus.

Semantic memory includes all acquired knowledge about the world and is the basis for nearly all human activity, yet its neurobiological foundation is only now becoming clear. Recent neuroimaging studies demonstrate two striking results: the participation of modality-specific sensory, motor, and emotion systems in language comprehension, and the existence of large brain regions that participate in comprehension tasks but are not modality-specific. These latter regions, which include the inferior parietal lobe and much of the temporal lobe, lie at convergences of multiple perceptual processing streams. These convergences enable increasingly abstract, supramodal representations of perceptual experience that support a variety of conceptual functions including object recognition, social cognition, language, and the remarkable human capacity to remember the past and imagine the future.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology, Social Psychology

View Paper: https://www.semanticscholar.org/paper/15de5528b04bf3d9cf741122677588140c25ebff

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Citations in the corpus

Understanding Grounded Language Learning Agents (2017, background): “Neuroscientiﬁc theories of memory, representation and learning have been developed to account for these effects (Rogers & McClelland, 2004; Binder & Desai, 2011).”
The Goldilocks Principle: Reading Children's Books with Explicit Memory Representations (2015, background): “The context in which words and sentences are understood, whether a conversation, book chapter or road sign, plays an important role in human comprehension (Altmann & Steedman, 1988; Binder & Desai, 2011).”
The theory of constructed emotion: an active inference account of interoception and categorization (2017, positive): “This hypothesis is partially consistent with the hypothesis that the default mode network represents semantic concepts (Binder et al., 2009; Binder and Desai, 2011) (see Figure 4B).”
Semantic reconstruction of continuous language from non-invasive brain recordings (2022, background): “…we partitioned brain data into three macro-scale cortical regions previously shown to be active during language processing—the speech network 29 , the parietal-temporal-occipital association region 23 and the prefrontal region 5 —and separately decoded from each region in each hemisphere (Fig.”
Contributions of episodic retrieval and mentalizing to autobiographical thought: evidence from functional neuroimaging, resting-state connectivity, and fMRI meta-analyses (2014, background): “Regions throughout the dorsal medial subsystem also become engaged during conceptual processing and semantic retrieval, as well as when individuals read complex narratives (Andrews-Hanna et al., in press; Binder and Desai, 2011; Binder et al., 2009; Mar, 2011; Olson et al., 2013; Patterson et al., 2”
Neural changes underlying successful second language word learning: An fMRI study (2015, background): “Increasing evidence indicates that the posterior middle temporal gyrus and angular gyrus are involved in semantic processing across a range of input modalities (e.g., Binder & Desai, 2011; Price, 2000; Rodd, Davis, & Johnsrude, 2005).”
MUC (Memory, Unification, Control) and beyond (2013, background): “Despite its impact until this very day, the classical model is wrong (cf. Poeppel et al., 2012).”
The Default Network and Social Cognition (2015, background): “Inferior frontal and lateral temporal regions, extending anteriorly into the temporal poles, are also activated during many social tasks and likely contribute to semantic/ conceptual aspects of mentalizing (Binder & Desai, 2011; Binder, Desai, Graves, & Conant, 2009; Seghier, 2012).”
A review and synthesis of the first 20 years of PET and fMRI studies of heard speech, spoken language and reading (2012, background): “For more comprehensive reviews of the semantic system, see Binder et al. (2009) and Binder and Desai (2011).”
The Impact of Generative AI on Critical Thinking: Self-Reported Reductions in Cognitive Effort and Confidence Effects From a Survey of Knowledge Workers (2025, positive): “Cognitive science shows that effective learning requires “grounding” information through multiple perspectives and examples [10, 11, 68], and GenAI can offer personalised analogies to aid this process [77, 90].”
Describing Sensory Experience: The Genre of Wine Reviews (2013, positive): “Recent neurobiological research indicate that conceptual representations consist of multiple levels of abstraction from sensory, motor and affective input, and activation of these modalities is influenced by factors such as contextual demands, frequency and familiarity (Binder & Desai 2011).”