Literature DB >> 32935833

Visual and Semantic Representations Predict Subsequent Memory in Perceptual and Conceptual Memory Tests.

Simon W Davis1,2, Benjamin R Geib1, Erik A Wing1, Wei-Chun Wang1, Mariam Hovhannisyan2, Zachary A Monge1, Roberto Cabeza1.   

Abstract

It is generally assumed that the encoding of a single event generates multiple memory representations, which contribute differently to subsequent episodic memory. We used functional magnetic resonance imaging (fMRI) and representational similarity analysis to examine how visual and semantic representations predicted subsequent memory for single item encoding (e.g., seeing an orange). Three levels of visual representations corresponding to early, middle, and late visual processing stages were based on a deep neural network. Three levels of semantic representations were based on normative observed ("is round"), taxonomic ("is a fruit"), and encyclopedic features ("is sweet"). We identified brain regions where each representation type predicted later perceptual memory, conceptual memory, or both (general memory). Participants encoded objects during fMRI, and then completed both a word-based conceptual and picture-based perceptual memory test. Visual representations predicted subsequent perceptual memory in visual cortices, but also facilitated conceptual and general memory in more anterior regions. Semantic representations, in turn, predicted perceptual memory in visual cortex, conceptual memory in the perirhinal and inferior prefrontal cortex, and general memory in the angular gyrus. These results suggest that the contribution of visual and semantic representations to subsequent memory effects depends on a complex interaction between representation, test type, and storage location.
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Entities:  

Keywords:  DNNs; episodic memory; object representation; representational similarity analysis; semantic memory

Mesh:

Year:  2021        PMID: 32935833      PMCID: PMC8485078          DOI: 10.1093/cercor/bhaa269

Source DB:  PubMed          Journal:  Cereb Cortex        ISSN: 1047-3211            Impact factor:   5.357


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