Oscillatory Dynamics Supporting Semantic Cognition: MEG Evidence for the Contribution of the Anterior Temporal Lobe Hub and Modality-Specific Spokes

The "hub and spoke model" of semantic representation suggests that the multimodal features of objects are drawn together by an anterior temporal lobe (ATL) "hub", while modality-specific "spokes" capture perceptual/action features. However, relatively little is known ab...

Full description

Saved in:
Bibliographic Details
Published inPloS one Vol. 12; no. 1; p. e0169269
Main Authors Mollo, Giovanna, Cornelissen, Piers L, Millman, Rebecca E, Ellis, Andrew W, Jefferies, Elizabeth
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 11.01.2017
Public Library of Science (PLoS)
Subjects
Online AccessGet full text

Cover

Loading…
More Information
Summary:The "hub and spoke model" of semantic representation suggests that the multimodal features of objects are drawn together by an anterior temporal lobe (ATL) "hub", while modality-specific "spokes" capture perceptual/action features. However, relatively little is known about how these components are recruited through time to support object identification. We used magnetoencephalography to measure neural oscillations within left ATL, lateral fusiform cortex (FC) and central sulcus (CS) during word-picture matching at different levels of specificity (employing superordinate vs. specific labels) for different categories (manmade vs. animal). This allowed us to determine (i) when each site was sensitive to semantic category and (ii) whether this was modulated by task demands. In ATL, there were two phases of response: from around 100 ms post-stimulus there were phasic bursts of low gamma activity resulting in reductions in oscillatory power, relative to a baseline period, that were modulated by both category and specificity; this was followed by more sustained power decreases across frequency bands from 250 ms onwards. In the spokes, initial power increases were not stronger for specific identification, while later power decreases were stronger for specific-level identification in FC for animals and in CS for manmade objects (from around 150 ms and 200 ms, respectively). These data are inconsistent with a temporal sequence in which early sensory-motor activity is followed by later retrieval in ATL. Instead, knowledge emerges from the rapid recruitment of both hub and spokes, with early specificity and category effects in the ATL hub. The balance between these components depends on semantic category and task, with visual cortex playing a greater role in the fine-grained identification of animals and motor cortex contributing to the identification of tools.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
Competing Interests: The authors have declared that no competing interests exist.
Conceptualization: EJ GM PLC AWE.Data curation: GM PLC REM.Formal analysis: GM PLC.Funding acquisition: EJ PLC AWE.Investigation: GM REM.Methodology: GM PLC EJ.Project administration: GM EJ.Resources: GM REM PLC.Software: GM PLC.Supervision: EJ GM PLC.Validation: GM PLC.Visualization: GM.Writing – original draft: GM PLC EJ.Writing – review & editing: GM PLC EJ.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0169269