Multimodal meta-analysis of brain integrity in disorders of consciousness

Disorders of consciousness represent severe neurological conditions that occur following acquired brain injury, with highly variable outcomes ranging from full recovery to prolonged unconsciousness and death. Understanding the precise brain mechanisms underlying this heterogenous group of disorders remains a scientific and medical challenge, impeding progress in the development of treatment or actionable clinical plans. Here, we sought to map the precise spatiotemporal pattern of brain alterations in these patients by performing a multimodal meta-analysis comprising 90 electroencephalography, magnetic resonance imaging and positron emission tomography studies (3,535 observations from rare patients with a prolonged disorder of consciousness and 1,372 from healthy controls). To generate hypotheses about potential underlying biological mechanisms, we quantified the spatial correspondence between brain circuits robustly associated with disorders of consciousness and openly available atlases of normative features of human brain biology, including maps on neurotransmission, which could inform new receptor-based mechanistic models of disease. By assessing 49 electrophysiological features of global brain integrity, we show that, in patients, neural electrical activity is consistently and globally stronger (i.e., spectral power and connectivity) in the delta band and weaker in the alpha band, while broadband entropy and alpha-SD of the participation coefficient best discriminate among patient groups. Using coordinate-based techniques, we identify convergent loss of structure, function and metabolism in specific cortical hubs of the default mode network and in subcortical “cognitive integration zones”
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of the mediodorsal thalamus and of the executive caudate nucleus, at the interface between default mode and executive, salience and ventral-attention networks
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. This convergent pattern aligns with specific receptor distributions (mGluR5, GABA-A, µ-opioid, CB1) and with the noradrenergic transporter topography, identifying putative receptor-level candidates for therapeutic trials. Altogether, our findings provide a robust foundation for refining current mechanistic models of disorders of consciousness, identifying promising clinical diagnostic biomarkers within the heterogenous literature and patient profiles, and selecting targets for therapeutic development.