Spatiotemporal dynamics of abstract and concrete semantic representations.

Dual Coding Theories (DCT) suggest that meaning is represented in the brain by a double code: a language-derived code in the Anterior Temporal Lobe (ATL) and a sensory-derived code in perceptual and motor regions. Concrete concepts should activate both codes, while abstract ones rely solely on the linguistic code. To test these hypotheses, the present magnetoencephalography (MEG) experiment had participants judge whether visually presented words relate to the senses while we recorded brain responses to abstract and concrete semantic components obtained from 65 independently rated semantic features.

Access to meaning from visual input: Object and word frequency effects in categorization behavior.

Object and word recognition are both cognitive processes that transform visual input into meaning. When reading words, the frequency of their occurrence ("word frequency," WF) strongly modulates access to their meaning, as seen in recognition performance. Does the frequency of objects in our world also affect access to their meaning? With object labels available in real-world image datasets, one can now estimate the frequency of occurrence of objects in scenes ("object frequency," OF).

Hierarchical organization of objects in scenes is reflected in mental representations of objects.

The arrangement of objects in scenes follows certain rules ("Scene Grammar"), which we exploit to perceive and interact efficiently with our environment. We have proposed that Scene Grammar is hierarchically organized: scenes are divided into clusters of objects ("phrases", e.g.

A neural mechanism for contextualizing fragmented inputs during naturalistic vision.

With every glimpse of our eyes, we sample only a small and incomplete fragment of the visual world, which needs to be contextualized and integrated into a coherent scene representation. Here we show that the visual system achieves this contextualization by exploiting spatial schemata, that is our knowledge about the composition of natural scenes. We measured fMRI and EEG responses to incomplete scene fragments and used representational similarity analysis to reconstruct their cortical representations in space and time.