Event-related electric microstates of the brain differ between words with visual and abstract meaning.
The present study shows that different neural activity during mental imagery and abstract mentation can be assigned to well-defined steps of the brain's information-processing. During randomized visual presentation of single, imagery-type and abstract-type words, 27 channel event-related potential (ERP) field maps were obtained from 25 subjects (sequence-divided into a first and second group for statistics). The brain field map series showed a sequence of typical map configurations that were quasi-stable for brief time periods (microstates). The microstates were concatenated by rapid map changes. As different map configurations must result from different spatial patterns of neural activity, each microstate represents different active neural networks. Accordingly, microstates are assumed to correspond to discrete steps of information-processing. Comparing microstate topographies (using centroids) between imagery- and abstract-type words, significantly different microstates were found in both subject groups at 286-354 ms where imagery-type words were more right-lateralized than abstract-type words, and at 550-606 ms and 606-666 ms where anterior-posterior differences occurred. We conclude that language-processing consists of several, well-defined steps and that the brain-states incorporating those steps are altered by the stimuli's capacities to generate mental imagery or abstract mentation in a state-dependent manner.
Koenig
T
T
The KEY Institute for Brain-Mind Research, University Hospital of Psychiatry, Zurich, Switzerland. tkoenig@key.unizh.ch
Kochi
K
K
Lehmann
D
D
D000328:Adult; D001921:Brain / Q000502:physiology*; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000706:statistics & numerical data*; D004585:Electrooculography; D005071:Evoked Potentials / Q000502:physiology; D005260:Female; D006801:Humans; D007802:Language; D008297:Male; D008606:Mental Processes / Q000502:physiology*; D016571:Neural Networks, Computer; D011932:Reading; D014796:Visual Perception / Q000502:physiology*