Ihalainen, R. | bioRxiv Science

bioRxiv2023

Lateral frontoparietal effective connectivity differentiates and predicts state of consciousness in traumatic disorders of consciousness

Neuroimaging studies have suggested an important role for the default mode network (DMN) in disorders of consciousness (DoC). However, the extent to which DMN connectivity can discriminate DoC states - unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS) - is less evident. Particularly, it is unclear whether effective DMN connectivity, as measured indirectly with dynamic causal modelling (DCM) of resting EEG can disentangle UWS from healthy controls and from patients considered conscious (MCS+). Crucially, this extends to UWS patients with potentially "covert" awareness (minimally conscious star, MCS*) indexed by voluntary brain activity in conjunction with partially preserved frontoparietal metabolism as measured with positron emission tomography (PET+ diagnosis; in contrast to PET-diagnosis with complete frontoparietal hypometabolism). Here, we address this gap by using DCM of EEG data acquired from patients with traumatic brain injury in 11 UWS (6 PET- and 5 PET+) and in 12 MCS+ (11 PET+ and 1 PET-), alongside with 11 healthy controls. We provide evidence for a key difference in left frontoparietal connectivity when contrasting UWS PET- with MCS+ patients and healthy controls. Next, in a leave-one-subject-out cross-validation, we tested the classification performance of the DCM models demonstrating that connectivity between medial prefrontal and left parietal sources reliably discriminates UWS PET- from MCS+ patients and controls. Finally, we illustrate that these models generalize to an unseen dataset: models trained to discriminate UWS PET- from MCS+ and controls, classify MCS* patients as conscious subjects with high posterior probability (pp > .92). These results identify specific alterations in the DMN after severe brain injury and highlight the clinical utility of EEG- based effective connectivity for identifying patients with potential covert awareness. Author SummaryOur study investigates the role of the Default Mode Network (DMN) in individuals with disorders of consciousness (DoC), such as unresponsive wakefulness syndrome (UWS) and minimally conscious state (MCS). Previous neuroimaging studies have suggested a role for the DMN in DoC, but its ability to differentiate between UWS and MCS remain unclear. Using advance brain imaging and modelling techniques, we analyzed data from DoC patients with traumatic brain injury and healthy controls. Our findings reveal a key difference in left frontoparietal connectivity when comparing UWS to MCS patients and healthy individuals. To validate our results, we employed a robust cross-validation approach, which demonstrated that the connectivity between frontal and left parietal brain regions reliably discriminates UWS patients from MCS patients and controls. Furthermore, we extended our analysis to include patients with potential covert awareness, showcasing the clinical utility of our findings. We successfully classified these patients as conscious with high accuracy. This research significantly contributes to our understanding of the DMN in DoC and highlights the potential use of electroencephalography-based connectivity analysis in clinical settings. By identifying specific alterations in the DMN after severe brain injury, our study may aid in the accurate diagnosis and management of individuals with disorders of consciousness, potentially improving their overall outcomes.

neuroscience↗

bioRxiv2020

How hot is the hot zone? Computational modelling clarifies the role of parietal and frontoparietal connectivity during anaesthetic-induced loss of consciousness

In recent years, specific cortical networks have been proposed to be crucial for sustaining consciousness, including the posterior hot zone and frontoparietal resting state networks (RSN). Here, we computationally evaluate the relative contributions of three RSNs - the default mode network (DMN), the salience network (SAL), and the central executive network (CEN) - to consciousness and its loss during propofol anaesthesia. Specifically, we use dynamic causal modelling (DCM) of 10 minutes of high-density EEG recordings (N = 10, 4 males) obtained during behavioural responsiveness, unconsciousness and post-anaesthetic recovery to characterise differences in effective connectivity within frontal areas, the posterior "hot zone", frontoparietal connections, and between-RSN connections. We estimate - for the first time - a large DCM model (LAR) of resting EEG, combining the three RSNs into a rich club of interconnectivity. Consistent with the hot zone theory, our findings demonstrate reductions in inter-RSN connectivity in the parietal cortex. Within the DMN itself, the strongest reductions are in feed-forward frontoparietal and parietal connections at the precuneus node. Within the SAL and CEN, loss of consciousness generates small increases in bidirectional connectivity. Using novel DCM leave-one-out cross-validation, we show that the most consistent out-of-sample predictions of the state of consciousness come from a key set of frontoparietal connections. This finding also generalises to unseen data collected during post-anaesthetic recovery. Our findings provide new, computational evidence for the importance of the posterior hot zone in explaining the loss of consciousness, highlighting also the distinct role of frontoparietal connectivity in underpinning conscious responsiveness, and consequently, suggest a dissociation between the mechanisms most prominently associated with explaining the contrast between conscious awareness and unconsciousness, and those maintaining consciousness. HighlightsO_LIModelling shows that connectivity within hot zone tracks change of conscious state C_LIO_LISeparately, frontoparietal connections support maintenance of conscious state C_LIO_LIStrength of frontoparietal connections predicts conscious state in unseen data C_LIO_LIBoth parietal hot zone and frontoparietal connectivity important for consciousness C_LI FundingThis work was supported by the UK Engineering and Physical Sciences Research Council (EP/P033199/1), Belgian National Funds for Scientific Research (FRS-FNRS), the University and University Hospital of Liege, the Fund Generet, the King Baudouin Foundation, the AstraZeneca Foundation, the European Unions Horizon 2020 Framework Programme for Research and Innovation under the Specific Grant Agreement No. 945539 (Human Brain Project SGA3), DOCMA project (EU-H2020-MSCA-RISE-778234), the BIAL Foundation, the European Space Agency (ESA) and the Belgian Federal Science Policy Office (BELSPO) in the framework of the PRODEX Programme, the Center-TBI project (FP7-HEALTH-602150), the Public Utility Foundation Universite Europeenne du Travail, "Fondazione Europea di Ricerca Biomedica", the Mind Science Foundation, the European Commission, and the Special Research Fund of Ghent University. O.G. is research associate and S.L. is research director at the F.R.S-FNRS. Declaration of interestNone. Significance StatementVarious connectivity studies have suggested multiple network-level mechanisms driving changes in the state of consciousness, such as the posterior hot zone, frontal-, and large-scale frontoparietal networks. Here, we computationally evaluate evidence for these mechanisms using dynamic causal modeling for resting EEG recorded before and during propofol-anaesthesia, and demonstrate that, particularly, connectivity in the posterior hot zone is impaired during propofol-induced unconsciousness. With a robust cross-validation paradigm, we show that connectivity in the large-scale frontoparietal networks can consistently predict the state of consciousness and further generalise these findings to an unseen state of recovery. These results suggest a dissociation between the mechanisms most prominently associated with explaining the contrast between conscious awareness and unconsciousness, and those maintaining consciousness.

neuroscience↗