fMRI data for word-pair presentation

Published: 30 Jun 2015 | Version 2 | DOI: 10.17632/bnwvgpfvhf.2

Description of this data

There are two general views regarding the organization of object knowledge. The featurebased
view assumes that object knowledge is grounded in a widely distributed neural network in
terms of sensory/function features (e.g., Warrington & Shallice, 1984), while the category-based
view assumes in addition that object knowledge is organized by taxonomic and thematic
categories (e.g., Schwartz et al., 2011). Using an fMRI adaptation paradigm, we compare
predictions from the feature- and category-based views by examining the neural substrates
recruited as subjects read word pairs that are identical, taxonomically related, thematically
related or unrelated while controlling for the function features involved across the two
categories. The feature-based view predicts that adaptation in function regions (i.e., left posterior
middle temporal lobe, left premotor cortex) should be observed for related word pairs regardless
of the taxonomic/thematic categories. In contrast, the category-based view generates the
prediction that adaptation in the bilateral anterior temporal lobes should be observed for
taxonomically related word pairs and adaptation in the left temporo-parietal junction should be
observed for thematically related word pairs. By improving upon previous study designs and
employing the fMRI adaptation task, this study has the potential to clarify the role of semantic
categories and features in the organization of object knowledge.

Experiment data files

This data is associated with the following publication:

Distinct loci of lexical and semantic access deficits in aphasia: Evidence from voxel-based lesion-symptom mapping and diffusion tensor imaging

Published in: Cortex

Latest version

  • Version 2


    Published: 2015-06-30

    DOI: 10.17632/bnwvgpfvhf.2

    Cite this dataset

    Geng, Jingyi; Schnur, Tatiana (2015), “fMRI data for word-pair presentation”, Mendeley Data, v2


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The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.