Characterizing Brain Functional Patterns Associated With Disorders Of Consciousness

The biological basis of consciousness continues to be an important but unsolved science issue.Severe acquired brain injury results in the disorders of consciousness(DOC),providing a natural model from which key insights about consciousness may be drawn.DOC can be divided into minimally conscious state and vegetative state.Clinical evaluation of the state of consciousness is mainly based on behavioral observation.However,the misdiagnosis rate is worryingly high and reaches up to 41% if it is based exclusively on observable behavior.Our current study is based on the financial support of the Beijing science and technology commission and national institutes of health(NIH)in Amarica.The aim of our study is to characterize the brain functional patterns based on functional MRI technique and provide objective classification features for accurate diagnosis and prognosis in patients with severely impaired consciousness.Method: Study participants included 88 patients in disorders of consciousness and 20 age-matched healthy control subjects.Classification of patients on referral was made based on the CRS-R scores.CRSR score and resting-state structural and functional MRI data were acquired for each participant.Date processing methods included the functional connectivity analysis,general linear model,clustering analysis and principal component analysis.Specifically,we introduced the methods below to our study:(1)Brain network feature extraction: increased connectivity index [ICI] and decreased connectivity index [DCI];(2)A new approach to identify well-labeled patients based on unsupervised clustering algorithm;(3)Entropy assessment of brain regions.Results:(1)Reorganization of the clinically assessed patients can highly improve the classification accuracy of a SVM classifier.Thirty-one out of 58 VS patients and 23 out of 30 MCS patients were selected based on our novel selection approach,with an average classification accuracy of 90.2% in differentiating between the two groups at the single subject level.Furthermore,decreased DMN functional connectivity strengthin representative VS and MCS patients revealed a positive correlation with the severity of consciousness impairment,while comparisons involving excluded patients did not.(2)A positive correlation between entropy reduction and symptoms worsening of DOC patients We showed that,as the symptoms of DOC deepen from MCS to VS,regional information content also was significantly reduced in that order in the sensory and memory systems of the brain.In contrast,with few exceptions,regional information content in high-order cognitive systems such as the DMN,executive control network,and silence network,remained statistically at a level similar to those in healthy individuals in MCS patients and only showed a significant reduction in VS patients.(3)Disrupted connection between arousal system and internal and external cortical awareness networks in MCS and VS patients We showed that functional connectivity from the PTA and caudal midbrain area to the corticalawareness-supporting networks were significantly reduced in MCS and VS patients;Moreover,as the clinical symptoms of consciousness disorders deepen from MCS to VS,functional connectivity strength became significantly reduced,changing from presenting no significant connections in MCS to widespread negative connections in VS.Additionally,we observed increased connectivity from the PTA and caudal midbrain area to limbic structures,the brainstem areas,and the cerebellum in MCS and VS patients,consistent with prior studies.Conclusions:(1)We proposed a novel and objective approach to reorganize the clinically labeled DOC patients based on the combination of brain connection features extraction and clinical assessment scale,which can complement the clinical assessment by improving the diagnosis and prognosis of patients with disorders of consciousness.(2)We provided,in the theoretical context of consciousness,novel evidence for a reduction of regional information content as a potential systems-level mechanism of consciousness disorder in MCS and VS,which can be used as a useful biomarker to differentiate MCS from VS.(3)Our findings offered important insights into the neural mechanisms underlying the longobserved arousal-awareness dissociation in DOC patients.