Regional modulation of high resolution evoked potentials during verbal and non-verbal matching tasks

Abstract

Nine subjects performed a cued S1-S2 matching task in which two sequentially presented visual stimuli (either letter strings or non-verbal graphical patterns) were compared according to verbal (phonemic, semantic, syntactic) or non-verbal (graphic identity) criteria. The Laplacian derivation was used to spatially enhance the topography of averaged evoked potentials (EPs) recorded from 59 scalp electrodes. Several effects distinguished the non-verbal from the verbal conditions. For example, following S1 a P250 EP that reached maximum amplitude over the occipital area was larger for the non-verbal patterns, whereas word and word-like letter strings (but not unfamiliar characters) elicited an N470 in the left temporal region. In anticipation of S2, a CNV-like slow potential was enhanced over posterior regions for the non-verbal stimuli. During the matching interval following S2, a P475 peak was observed to be larger for non-verbal patterns than for letter strings over right frontal and temporal regions. Other effects distinguished the verbal conditions from one another. In particular, following S1 a left frontal P445 potential was enhanced to closed class versus open class words, and following S2 a P620 potential in the left temporal region was enhanced for phonological matching relative to semantic matching. These results suggest that processing of verbal and non-verbal stimuli depends on a network of subprocessors that are regionalized to functionally specialized cortical areas and that operate both sequentially and in parallel in order to extract and synthesize multiple forms of attribute-specific information. In contrast to neuropsychological approaches to the study of pattern recognition and reading, the fine-grain temporal resolution of EP measurements, in combination with the improved spatial resolution obtained through computation of Laplacian derivation wave forms from a large number of electrodes, permits characterization of both the regionalization of subprocesses and the subsecond dynamics of their engagement.