Information Sharing in the Brain Indexes Consciousness in Noncommunicative Patients

Abstract

Neuronal theories of conscious access tentatively relate conscious perception to the integration and global broadcasting of information across distant cortical and thalamic areas. Experiments contrasting visible and invisible stimuli support this view and suggest that global neuronal communication may be detectable using scalp electroencephalography (EEG). However, whether global information sharing across brain areas also provides a specific signature of conscious state in awake but noncommunicating patients remains an active topic of research. We designed a novel measure termed "weighted symbolic mutual information" (wSMI) and applied it to 181 high-density EEG recordings of awake patients recovering from coma and diagnosed in various states of consciousness. The results demonstrate that this measure of information sharing systematically increases with consciousness state, particularly across distant sites. This effect sharply distinguishes patients in vegetative state (VS), minimally conscious state (MCS), and conscious state (CS) and is observed regardless of etiology and delay since insult. The present findings support distributed theories of conscious processing and open up the possibility of an automatic detection of conscious states, which may be particularly important for the diagnosis of awake but noncommunicating patients.

Signature of consciousness in the dynamics of resting-state brain activity

“…Our results are also in agreement with several theories of consciousness (22,24) and earlier observations in sleep, anesthesia, and VS (18,(40)(41)(42)(43). Several theories of consciousness posit that distributed functional networks support conscious states and that loss of consciousness is indexed by alterations of these network patterns (22,24,42).…”

Brain networks predict metabolism, diagnosis and prognosis at the bedside in disorders of consciousness

“…Our finding is also consistent with previous literature that analysed EEG data with complementary methods based on clinical expertise (Forgacs et al, 2014) and information theory (King et al, 2013). This engenders confidence in the reliability of EEG as a valuable tool, as it suggests that different analytical methods could be used to deliver similarly capable diagnostic capabilities.…”

“…This engenders confidence in the reliability of EEG as a valuable tool, as it suggests that different analytical methods could be used to deliver similarly capable diagnostic capabilities. Further, the strength of the relationship between the best brain network metrics we use here and the CRS-R based diagnosis is comparable to that reported in previous literature that has employed EEG-based analysis (King et al, 2013;Sitt et al, 2014). PET (Stender et al, 2016) and TMS-EEG (Casarotto et al, 2016) have been shown to perform better, but both require much more complex technology that is either impossible or difficult to deploy at the patient's bedside.…”

“…To help address the diagnostic and prognostic challenge in disorders of consciousness, a range of neuroimaging technologies have been proposed for assessing ongoing brain activity with sophisticated analytical techniques. These include MRI (Demertzi et al, 2015), PET (Thibaut et al, 2012;Stender et al, 2014) and high density EEG (Lehembre et al, 2012;King et al, 2013;Lechinger et al, 2013;Chennu et al, 2014;Sitt et al, 2014). EEG in particular is an attractive option in this context as it is portable, cost-effective, and relatively feasible to deploy at the patient's bedside.…”

Probing consciousness in a sensory-disconnected paralyzed patient

“…We then analyzed in detail the univariate markers that are usually more contributive to the multivariate classifier by comparing the topographies from the previously recorded and diagnosed patients with this patient. Detailed analysis further revealed that patterns of spectral power of EEG (in delta and alpha band), complexity markers (spectral entropy, permutation entropy and Komolgorov-Chaitin complexity), and functional connectivity (weighted Symbolic Mutual Information, wSMI [12] ) were strongly supportive of a conscious state, rather than of a VS/UWS or even MCS ( Figure 2). As expected, univariate markers of auditory event-related potentials were not contributive given patient's deafness.…”