Covert brain complexity in the intensive care unit.
Cortex 2026 Apr 17; 201:1-9. [Online ahead of print]

Abstract

Early detection of consciousness in critically ill patients with severe brain injuries can profoundly impact prognostication and clinical care decisions. Advanced multimodal protocols to detect signs of consciousness include standardized behavioral assessments, task-based functional magnetic resonance imaging (fMRI), and task-based electroencephalography (EEG). However, these approaches have limited diagnostic sensitivity because patients may lack auditory function, attention, language, or other cognitive capacities required to perform a task or process a sensory stimulus, even if they are conscious. Transcranial magnetic stimulation EEG (TMS-EEG) has the potential to overcome these limitations by directly engaging corticothalamic circuits to compute the perturbational complexity index (PCI), an emerging indicator of consciousness. To date, TMS-EEG studies have focused on patients in the subacute or chronic stage of recovery from severe brain injury. Here, we report the proof-of-concept application of TMS-EEG for a critically ill patient in the acute stage of brain injury, in which multimodal assessments suggested a vegetative state/unresponsive wakefulness syndrome. We demonstrate that TMS-EEG may detect signs of consciousness that elude current advanced evaluations, showing the feasibility of TMS-EEG as part of a multimodal protocol for assessing consciousness in the intensive care unit.

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Authors+Show Affiliations

Fecchio MCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. Electronic address: mfecchio@mgh.harvard.edu.
Schreier DRCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; The Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, MA, USA.
Cambareri MKCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Biomedical Engineering, Boston University, Boston, MA, USA.
Nisticò VCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; "Aldo Ravelli" Research Center for Neurotechnology and Experimental Brain Therapeutics, Department of Health Science, University of Milan, Milan, Italy; Department of Psychology, University of Milano-Bicocca, Milan, Italy.
Freeman HJCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Lawrence PKCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Bodien YGCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Department of Surgery, Department of Neurological Surgery, Department of Physical Medicine and Rehabilitation, Vanderbilt University Medical Center, Nashville, TN, USA.
Young MJCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
Wu OAthinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.
Edlow BLCenter for Neurotechnology and Neurorecovery, Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA; Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA.

Pub Type(s)

Case Reports
Journal Article

Language

eng

PubMed ID

42090748