Abstract
The neural principles behind semantic category representation are still under debate. Dominant theories mostly focus on distinguishing concrete from abstract concepts but, in such theories, divisions into categories of concrete concepts are more developed than for their abstract counterparts. An encompassing theory on semantic category representation could be within reach when charting the semantic attributes that are capable of describing both concept types. A good candidate are the three semantic dimensions defined by Osgood (potency, valence, arousal). However, to show to what extent they affect semantic processing, specific neuroimaging tools are required. Electroencephalography (EEG) is on par with the temporal resolution of cognitive behavior and source reconstruction. Using high-density set-ups, it is able to yield a spatial resolution in the scale of millimeters, sufficient to identify anatomical brain parcellations that could differentially contribute to semantic category representation. Cognitive neuroscientists traditionally focus on scalp domain analysis and turn to source reconstruction when an effect in the scalp domain has been detected. Traditional methods will potentially miss out on the fine-grained effects of semantic features as they are possibly obscured by the mixing of source activity due to volume conduction. For this reason, we have developed a mass-univariate analysis in the source domain using a mixed linear effect model. Our analyses reveal distinct networks of sources for different semantic features that are active during different stages of lexico-semantic processing of single words. With our method we identified differences in the spatio-temporal activation patterns of abstract and concrete words, high and low potency words, high and low valence words, and high and low arousal words, and in this way shed light on how word categories are represented in the brain.
Highlights
Different cortical areas are involved in representing semantic categories and concepts, collectively known as the “semantic system” (Binder et al, 2009), and word representation (“semantic map”) has recently been mapped comprehensively with fMRI (Huth et al, 2016)
Our analyses reveal distinct networks of sources for different semantic features that are active during different stages of lexico-semantic processing of single words
We believe that the role of the right hemisphere in word processing should be more acknowledged since, in the current study, we found a number of brain areas, in particular in the right temporal cortex, that were largely involved in processing a number of semantic features
Summary
Different cortical areas are involved in representing semantic categories and concepts, collectively known as the “semantic system” (Binder et al, 2009), and word representation (“semantic map”) has recently been mapped comprehensively with fMRI (Huth et al, 2016). One of the most prominent theories of semantic word processing is the grounded cognition or embodied cognition model This model suggests that semantic knowledge resides in high-level perception and motor representation systems (Barsalou, 2008, 2010). An attempt to explain this along the lines of embodied cognition would need to resort to the most prevalent modality behind these categories, e.g. artifacts separated from animals and food as they call upon systems involved in manipulation or the action in response to experiencing the word, as evidenced by a larger activation in the left premotor cortex and the pre- and post-central gyrus (Hwang et al, 2009). The hub and spoke model is regarded as the middle ground between the embodied and disembodied hypotheses (Mahon and Caramazza, 2008; Lambon Ralph, 2013)
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