Content-State Dimensions Characterize Different Types of Neural Correlates of Consciousness

Abstract

Identifying the neural correlates of consciousness (NCCs) is key to support the different scientific theories of consciousness. NCCs can be defined to reflect either the brain signatures underlying specific conscious content or those supporting different states of consciousness, two aspects traditionally studied separately. In this paper, we introduce a framework to characterize NCCs according to their dynamics in both the 'state' and 'content' dimensions. The two-dimensional space is defined by the NCCs' capacity to distinguish the conscious states from non-conscious states, (x-axis) and the content (perceived versus unperceived, y-axis). According to the sign of the x and y-axis, NCCs are separated into four quadrants in terms of how they distinguish the state and content dimensions. We implement the framework using three types of EEG NCCs: markers of connectivity, markers of complexity, and spectral summaries. The NCC-state is represented by the level of consciousness in 1) patients with disorders of consciousness; 2) healthy participants’ during a nap. On the other hand NCC-content by the conscious content in healthy participants' perception tasks: 1) auditory local-global paradigm and 2) visual awareness paradigm. In both cases, we see separate clusters of NCCs with correlated and anti-correlated dynamics, shedding light on the complex relationship between the state and content of consciousness and emphasizing the importance of considering them simultaneously. This work presents an innovative framework for studying consciousness by examining NCC in a two-dimensional space, providing a valuable resource for future research, with potential applications using diverse experimental paradigms, neural recording techniques, and modeling investigations.