Distinguishing Different Levels of Consciousness using a Novel Network Causal Activity Measure

Abstract

Characterizing consciousness, the inner subjective feeling that is present in every experience, is a hard problem in neuroscience, but has important clinical implications. A leading neuro-scientific approach to understanding consciousness is to measure the complex causal neural interactions in the brain. Elucidating the complex causal interplay between cortical neural interactions and the subsequent network computations is very challenging. In this study, we propose a novel quantitative measure of consciousness - Network Causal Activity - using a recently proposed Compression-Complexity Causality measure to analyze electrocorticographic signals from the lateral cortex of four monkeys during two states of consciousness (awake and anaesthesia). Our results suggest that Network Causal Activity is consistently higher in the awake state as compared with anaesthesia state for all the monkeys.