Functional Brain Network Topology Discriminates between Patients with Minimally Conscious State and Unresponsive Wakefulness Syndrome.

Alberto Cacciola,Placido Bramanti,Leonardo Malatacca,Demetrio Milardi,Maurizio Spitaleri,Antonino Naro,Giuseppe Anastasi,Alessia Bramanti,Rocco Calabrò,Carlo Cannistraci,Alessandro Muscoloni,Antonino Leo

doi:10.3390/jcm8030306

Abstract

Consciousness arises from the functional interaction of multiple brain structures and their ability to integrate different complex patterns of internal communication. Although several studies demonstrated that the fronto-parietal and functional default mode networks play a key role in conscious processes, it is still not clear which topological network measures (that quantifies different features of whole-brain functional network organization) are altered in patients with disorders of consciousness. Herein, we investigate the functional connectivity of unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) patients from a topological network perspective, by using resting-state EEG recording. Network-based statistical analysis reveals a subnetwork of decreased functional connectivity in UWS compared to in the MCS patients, mainly involving the interhemispheric fronto-parietal connectivity patterns. Network topological analysis reveals increased values of local-community-paradigm correlation, as well as higher clustering coefficient and local efficiency in UWS patients compared to in MCS patients. At the nodal level, the UWS patients showed altered functional topology in several limbic and temporo-parieto-occipital regions. Taken together, our results highlight (i) the involvement of the interhemispheric fronto-parietal functional connectivity in the pathophysiology of consciousness disorders and (ii) an aberrant connectome organization both at the network topology level and at the nodal level in UWS patients compared to in the MCS patients.

Highlights

The human connectome is a comprehensive description of neural elements and their reciprocal connections reflecting the complex organization of the brain [1]
Since we looked at the performance of whole-brain topological network measures in separating unresponsive wakefulness syndrome (UWS) from minimally conscious state (MCS) patients, we have computed the area under the ROC curve (AUC) and area under the precision-recall curve (AUPR)
At a network topology level, we found that the patients with UWS showed higher values of Local Community Paradigm (LCP)-corr, clustering coefficient, and local efficiency than those with MCS

Summary

Introduction

The human connectome is a comprehensive description of neural elements and their reciprocal connections reflecting the complex organization of the brain [1]. Several magnetic resonance imaging (MRI) and neurophysiological studies have demonstrated that the brain networks present an intrinsic small-world (SW) architecture, functionally segregated (local clustering) and integrated (global efficiency), which is organized into modules with high clustering and short characteristic path length [5,6,7]. This enables information to travel quickly and efficiently even between far brain structures, as well as to prevent the uncontrolled spread of information across the whole network [8]. According to the information integration theory, consciousness is the product of functional interaction of multiple brain structures and depends on the brain’s ability to integrate different complex patterns of internal communication [9]

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