Electronic Thesis and Dissertation Repository

Thesis Format

Integrated Article

Degree

Doctor of Philosophy

Program

Neuroscience

Supervisor

Owen, Adrian M.

2nd Supervisor

Gofton, Teneille E.

Co-Supervisor

Abstract

Detecting signs of preserved awareness and predicting recovery after severe acute brain injury in the intensive care unit (ICU) is clinically and scientifically challenging. Treatment decisions are often based on unreliable behavioural responses rather than objective and quantifiable measures. This dissertation examines the utility of using advanced neuroimaging methods to improve diagnosis and prognosis after severe brain injury. In Chapter 2, a series of functional MRI (fMRI) studies were employed to assess preserved brain activity in a patient with severe traumatic brain injury (TBI) and at 9-months post injury. Preserved sound and speech perception were demonstrated acutely, and an increased response to higher-order cognitive tasks with greater functional connectivity was observed at recovery. In Chapter 3, we performed a series of multimodal, longitudinal investigations in 33 patients with acute severe TBI that integrated results from resting-state and stimulus-based fMRI, diffusion tractography, and behavioural assessments to identify biomarkers of recovery. Neuroimaging measures predicted good functional recovery at 6 months with 87.5% accuracy and outperformed clinical and demographic predictors. In Chapter 4, we evaluated the use of functional near-infrared spectroscopy (fNIRS) to detect biomarkers of conscious processing. We demonstrate that fNIRS can capture somatosensory perception, auditory processing, and command-driven brain activity with adequate sensitivity at the single-subject level in healthy participants. We then used fNIRS to detect covert brain activity in one acutely brain-injured patient in the ICU and found a greater level of cognitive processing than what bedside behavioural measures demonstrated. In Chapter 5, we test for preserved covert conscious awareness in 14 critically ill unresponsive patients using fNIRS. We found that 4 patients were able to willfully modulate their brain activity when asked to complete a motor imagery task, suggesting a level of awareness that was entirely inconsistent with their behavioural examination. Collectively, these studies demonstrate that advanced neuroimaging techniques can improve the detection of consciousness in the ICU and accurately predict functional recovery. These tests may inform discussions regarding the trajectory of care and drive efforts to develop interventions that facilitate recovery and improve quality of life.

Summary for Lay Audience

Each year, millions of people worldwide sustain a severe brain injury and are treated in the intensive care unit (ICU) for life-saving care. Currently, there are no tools that can accurately detect preserved consciousness and predict which patients will fully recover. This makes decisions about continuing or withdrawing lifesaving therapies challenging for doctors and families. Recently, brain imaging techniques have been developed to address this critical problem. This dissertation explores the use of these methods in patients with acute severe brain injury in the ICU. In Chapter 2, functional MRI (fMRI) was used to examine brain activity in an unresponsive patient with severe traumatic brain injury (TBI) while in ICU and again at 9 months post injury. FMRI results revealed that the patient’s brain was responding to auditory stimuli while in ICU and that markers for high level cognition recovered by 9 months post injury. In Chapter 3, a combination of brain imaging methods was used to predict recovery from severe brain injury in the ICU with 87.5% accuracy, which was significantly higher than current prediction tools. The brain function of most patients fully recovered by 6 months. In Chapter 4, a portable neuroimaging method called functional near-infrared spectroscopy (fNIRS) was used to detect markers of conscious processing in healthy individuals using stimuli that examines sensory processing and command following abilities. We show that fNIRS has variable reliability for capturing brain activity. We then tested fNIRS to test one patient in the ICU and found that the patient had a higher level of cognitive processing then what behavioural measures showed. In Chapter 5, we used fNIRS to detect preserved consciousness in 14 patients in the ICU. We found that 4 patients were able to imagine playing a game of tennis, when instructed to do so, despite not following commands at the bedside. Collectively, these studies demonstrate advanced imaging techniques can provide objective information about brain function for patients with severe brain injury, improve the detection of consciousness, and predict recovery. This research may have significant impacts on the assessment and care of patients in the ICU, inform discussions about life-saving therapy, and drive efforts to develop interventions to promote recovery.

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Available for download on Wednesday, May 27, 2026

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