Neural bases of cognitive ERPs:: More than phase reset

Up to now, two conflicting theories have tried to explain the genesis of averaged event-related potentials (ERPs): Whereas one hypothesis claims that ERPs originate from an event-related activation of neural assemblies distinct from background dynamics, the other hypothesis states that ERPs are ground produced by phase resetting of ongoing oscillatory activity. So far, this question has only been addressed for early ERP components. Late ERP components, however, are generally thought to represent superimposed activities of several anatomically distinct brain areas. Thus, the question of which mechanism underlies the genesis of late ERP components cannot be easily answered based on scalp recordings. In contrast, two well-investigated late ERP components recorded invasively from within the human medial temporal lobe (MTL) in epilepsy patients, the so-called MTL-P300 and the anterior MTL-N400 (AMTL-N400), are based on single source activity. Hence, we investigated whether the MTL-P300 and the AMTL-N400 are based on an event-related activity increase, a phase reset of ongoing oscillatory activity or both. ERPs were recorded from the hippocampus and rhinal cortex in subjects performing a visual oddball paradigm and a visual word recognition paradigm. With wavelet techniques, stimulus-related phase-locking and power changes were analyzed in a frequency range covering 2 to 48 Hz. We found that the MTL-P300 is accompanied by both phase reset and power increase P300 and that both effects overlap partly in time. In contrast, the AMTL-N400 is initially associated with phase locking without power increase and only later during the course of the out AMTL-N400 we observed an additional power increase. In conclusion, both aspects, event-related activation of neural assemblies and phase resetting of ongoing activity seem to be involved in the generation of late ERP components as recorded in cognitive tasks. Therefore, separate analysis of event-related power and phase-locking changes might reveal specific related insights into the mechanisms underlying different cognitive functions.