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 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.
Highlights
Advances in life-saving medical technology have dramatically increased survival rates for comatose patients after severe brain injury
The prolonged disorder of consciousness (pDoC) fall into three sub-categories: (1) the vegetative state/unresponsive wakefulness syndrome (VS/UWS), in which a patient is wakeful but unaware; (2) the minimally conscious state minus (MCS−), in which patients show reproducible minimal evidence of awareness, such as visual pursuit or fixation, orientation to noxious stimuli, and vocalizations or contingent motor and affective responses, their presence is inconsistent; and (3) the MCS plus (MCS+), in which patients show more complex volitional responses [3,4]
We excluded from the study patients with: (i) severe pathologies independent from the brain injury; (ii) mixed etiology; (iii) non-stabilized and severe general clinical conditions; (iv) contra-indication for magnetic resonance imaging (MRI); (v) large brain damage (>50% of total brain volume), as stated by a certified neuroradiologist on computed tomography (CT) or MRI scan performed before the positron emission tomography (PET)/functional magnetic resonance imaging (fMRI) acquisition; and (vi) motion parameters >3 mm in translation and 3 mm in rotation
Summary
Advances in life-saving medical technology have dramatically increased survival rates for comatose patients after severe brain injury Many of these patients will be diagnosed with a prolonged disorder of consciousness (pDoC) [1,2], a state in which they show disruption to their awareness of themselves and/or their environment. The patient is classified as emergence from minimally conscious state (EMCS) when he/she is able to communicate or show proper functional object use [4] In each of these conditions, the clinical assessment of awareness through behavioural tools can be extremely challenging and sometimes inconsistent between assessments, even when a standardized scale such as the Coma Recovery Scale [5] is administered [6]. In those patients that remain on life support, approximately half go on to recover some degree of awareness [15]
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