Brain Networks in Disorders of Consciousness

A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Clinical Neurology".

Deadline for manuscript submissions: closed (31 March 2020) | Viewed by 17927

Special Issue Editors


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Guest Editor
Brain Investigation & Neuromodulation Lab (Si-BIN Lab) at the Department of Medicine, Surgery and Neuroscience, Neurology and Clinical Neurophysiology Unit, University of Siena, 53100 Siena, Italy
Interests: neuromodulation; parkinson’s disease; movement disorders; noninvasive brain stimulation techniques; neurophysiology; transcranial magnetic stimulation; eeg; cognitive neuroscience; robotic devices
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Professor of Physiology, Department of Biomedical and Clinical Sciences “L. Sacco”, Laboratory for the Analysis of Bioelectrical Signals (LASEB), University of Milan, Milan, Italy
Interests: neurophysiology of the cerebral cortex in wakefulness and sleep; neurophysiology of disorders of consciousness and other pathological conditions

Special Issue Information

Dear Colleagues,

Disorders of consciousness (DOC) represent a big and multi-perspective challenge of contemporary clinical neuroscience. First, measuring consciousness and identifying the mechanisms of unconsciousness are still open issues that neuroimaging and neurophysiology are trying to answer with different and complementary approaches. Second, the identification of the level of gravity of a patient with DOC still has some margins of uncertainty; this implies that even prognostic methods are still not optimal. Third, conventional medical interventions and therapies often do not have a substantial impact on the clinical course in these patients. New interventions based on invasive or non-invasive neuromodulatory approaches are emerging, but are still investigational. Nevertheless, DOC represent an increasing burden for the different health care systems worldwide. The concept of this Special Issue is to look at DOC from a brain network perspective; this is now possible thanks to the impressive advancements that have occurred in neuroimaging and neurophysiological investigations in recent years. An integrated network-based approach will hopefully help to better understand the neural mechanisms underlying consciousness (the most complex—and still unsolved—brain construct) and its dysfunctions, for which there is room for rehabilitative and therapeutic interventions currently and in the future.  

Prof. Dr. Simone Rossi
Prof. Dr. Mario Rosanova
Guest Editors

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Keywords

  • Disorders of consciousness
  • Neuroimaging
  • Brain networks
  • Neurophysiology
  • Neuromodulation
  • Electroencephalography
  • Transcranial magnetic stimulation
  • Functional magnetic resonance Imaging
  • Deep brain stimulation

Published Papers (4 papers)

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Research

18 pages, 5643 KiB  
Article
Consciousness and the Dimensionality of DOC Patients via the Generalized Ising Model
by Pubuditha M. Abeyasinghe, Marco Aiello, Emily S. Nichols, Carlo Cavaliere, Salvatore Fiorenza, Orsola Masotta, Pasquale Borrelli, Adrian M. Owen, Anna Estraneo and Andrea Soddu
J. Clin. Med. 2020, 9(5), 1342; https://doi.org/10.3390/jcm9051342 - 04 May 2020
Cited by 13 | Viewed by 3650
Abstract
The data from patients with severe brain injuries show complex brain functions. Due to the difficulties associated with these complex data, computational modeling is an especially useful tool to examine the structure–function relationship in these populations. By using computational modeling for patients with [...] Read more.
The data from patients with severe brain injuries show complex brain functions. Due to the difficulties associated with these complex data, computational modeling is an especially useful tool to examine the structure–function relationship in these populations. By using computational modeling for patients with a disorder of consciousness (DoC), not only we can understand the changes of information transfer, but we also can test changes to different states of consciousness by hypothetically changing the anatomical structure. The generalized Ising model (GIM), which specializes in using structural connectivity to simulate functional connectivity, has been proven to effectively capture the relationship between anatomical structures and the spontaneous fluctuations of healthy controls (HCs). In the present study we implemented the GIM in 25 HCs as well as in 13 DoC patients diagnosed at three different states of consciousness. Simulated data were analyzed and the criticality and dimensionality were calculated for both groups; together, those values capture the level of information transfer in the brain. Ratifying previous studies, criticality was observed in simulations of HCs. We were also able to observe criticality for DoC patients, concluding that the GIM is generalizable for DoC patients. Furthermore, dimensionality increased for the DoC group as compared to healthy controls, and could distinguish different diagnostic groups of DoC patients. Full article
(This article belongs to the Special Issue Brain Networks in Disorders of Consciousness)
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29 pages, 5855 KiB  
Article
Network Mapping of Connectivity Alterations in Disorder of Consciousness: Towards Targeted Neuromodulation
by Lucia Mencarelli, Maria Chiara Biagi, Ricardo Salvador, Sara Romanella, Giulio Ruffini, Simone Rossi and Emiliano Santarnecchi
J. Clin. Med. 2020, 9(3), 828; https://doi.org/10.3390/jcm9030828 - 18 Mar 2020
Cited by 14 | Viewed by 5234
Abstract
Disorder of consciousness (DoC) refers to a group of clinical conditions that may emerge after brain injury, characterized by a varying decrease in the level of consciousness that can last from days to years. An understanding of its neural correlates is crucial for [...] Read more.
Disorder of consciousness (DoC) refers to a group of clinical conditions that may emerge after brain injury, characterized by a varying decrease in the level of consciousness that can last from days to years. An understanding of its neural correlates is crucial for the conceptualization and application of effective therapeutic interventions. Here we propose a quantitative meta-analysis of the neural substrate of DoC emerging from functional magnetic resonance (fMRI) and positron emission tomography (PET) studies. We also map the relevant networks of resulting areas to highlight similarities with Resting State Networks (RSNs) and hypothesize potential therapeutic solutions leveraging network-targeted noninvasive brain stimulation. Available literature was reviewed and analyzed through the activation likelihood estimate (ALE) statistical framework to describe resting-state or task-dependent brain activation patterns in DoC patients. Results show that task-related activity is limited to temporal regions resembling the auditory cortex, whereas resting-state fMRI data reveal a diffuse decreased activation affecting two subgroups of cortical (angular gyrus, middle frontal gyrus) and subcortical (thalamus, cingulate cortex, caudate nucleus) regions. Clustering of their cortical functional connectivity projections identify two main altered functional networks, related to decreased activity of (i) the default mode and frontoparietal networks, as well as (ii) the anterior salience and visual/auditory networks. Based on the strength and topography of their connectivity profile, biophysical modeling of potential brain stimulation solutions suggests the first network as the most feasible target for tES, tDCS neuromodulation in DoC patients. Full article
(This article belongs to the Special Issue Brain Networks in Disorders of Consciousness)
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20 pages, 886 KiB  
Article
Neuroimaging Studies on Disorders of Consciousness: A Meta-Analytic Evaluation
by Manuela Berlingeri, Francesca Giulia Magnani, Gerardo Salvato, Mario Rosanova and Gabriella Bottini
J. Clin. Med. 2019, 8(4), 516; https://doi.org/10.3390/jcm8040516 - 16 Apr 2019
Cited by 16 | Viewed by 3435
Abstract
Neuroimaging tools could open a window on residual neurofunctional activity in the absence of detectable behavioural responses in patients with disorders of consciousness (DOC). Nevertheless, the literature on this topic is characterised by a large heterogeneity of paradigms and methodological approaches that can [...] Read more.
Neuroimaging tools could open a window on residual neurofunctional activity in the absence of detectable behavioural responses in patients with disorders of consciousness (DOC). Nevertheless, the literature on this topic is characterised by a large heterogeneity of paradigms and methodological approaches that can undermine the reproducibility of the results. To explicitly test whether task-related functional magnetic resonance imaging (fMRI) can be used to systematically detect neurofunctional differences between different classes of DOC, and whether these differences are related with a specific category of cognitive tasks (either active or passive), we meta-analyzed 22 neuroimaging studies published between 2005 and 2017 using the Activation Likelihood Estimate method. The results showed that: (1) active and passive tasks rely on well-segregated patterns of activations; (2) both unresponsive wakeful syndrome and patients in minimally conscious state activated a large portion of the dorsal-attentional network; (3) shared activations between patients fell mainly in the passive activation map (7492 voxels), while only 48 voxels fell in a subcortical region of the active-map. Our results suggest that DOCs can be described along a continuum—rather than as separated clinical categories—and characterised by a widespread dysfunction of brain networks rather than by the impairment of a well functionally anatomically defined one. Full article
(This article belongs to the Special Issue Brain Networks in Disorders of Consciousness)
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22 pages, 2283 KiB  
Article
Functional Brain Network Topology Discriminates between Patients with Minimally Conscious State and Unresponsive Wakefulness Syndrome
by Alberto Cacciola, Antonino Naro, Demetrio Milardi, Alessia Bramanti, Leonardo Malatacca, Maurizio Spitaleri, Antonino Leo, Alessandro Muscoloni, Carlo Vittorio Cannistraci, Placido Bramanti, Rocco Salvatore Calabrò and Giuseppe Pio Anastasi
J. Clin. Med. 2019, 8(3), 306; https://doi.org/10.3390/jcm8030306 - 05 Mar 2019
Cited by 37 | Viewed by 4668
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Brain Networks in Disorders of Consciousness)
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