Paradox of slow frequencies - Are slow frequencies in upper cortical layers a neural predisposition of the level/state of consciousness (NPC)?

Consciousness research has much focused on faster frequencies like alpha or gamma while neglecting the slower ones in the infraslow (0.001-0.1 Hz) and slow (0.1-1 Hz) frequency range. These slower frequency ranges have a bad reputation though; their increase in power can observed during the loss of consciousness as in sleep, anesthesia, and vegetative state. However, at the same time, slower frequencies have been conceived instrumental for consciousness. The present paper aims to resolve this paradox which I describe as paradox of slow frequencies. I first show various data that suggest a central role of slower frequencies in integrating faster ones, i.e., temporo-spatial integration and nestedness. Such temporo-spatial integration and nestedness is disrupted during the loss of consciousness as in anesthesia and sleep leading to temporo-spatial fragmentation and isolation between slow and fast frequencies. Slow frequencies are supposedly mediated by neural activity in upper cortical layers in higher-order associative regions as distinguished from lower cortical layers that are related to faster frequencies. Taken together, slower and faster frequencies take on different roles for the level/state of consciousness. Faster frequencies by themselves are sufficient and thus a neural correlate of consciousness (NCC) while slower frequencies are a necessary non-sufficient condition of possible consciousness, e.g., a neural predisposition of the level/state of consciousness (NPC). This resolves the paradox of slow frequencies in that it assigns different roles to slower and faster frequencies in consciousness, i.e., NCC and NPC. Taken as NCC and NPC, fast and slow frequencies including their relation as in temporo-spatial integration and nestedness can be considered a first building bloc of a future temporo-spatial theory of consciousness (TTC) (Northoff, 2013; Northoff, 2014b; Northoff 82 Huang, 2017). (C) 2017 Elsevier Inc. All rights reserved.