Ayham Alkhachroum, M.D., MSc

Primary Investigator of the Hacking Consciousness Lab. Co-Director of Master of Science in Clinical and Translational Investigation.

Understanding Consciousness, Communication, and Recovery After Acute Brain Injury

My research focuses on understanding, detecting, and restoring brain function in patients with severe acute brain injury who appear behaviorally unresponsive. A major challenge in neurocritical care is that clinical examination alone often fails to detect preserved cognition, intention, or capacity for recovery. This limitation can lead to inaccurate prognostication, premature withdrawal of life-sustaining therapies, and lost opportunities for recovery and communication.

The central premise of my work is that consciousness and cognitive processing can persist despite the absence of overt behavior, and that these latent brain functions can be detected, quantified, and leveraged using advanced neurophysiologic and computational tools. My laboratory integrates clinical neuroscience, electrophysiology, imaging, and artificial intelligence to identify covert brain function, improve prognostication, and develop communication pathways for patients with disorders of consciousness following traumatic brain injury, hypoxic-ischemic injury, stroke, and other critical neurologic illnesses.

To address this complex and clinically urgent problem, my research program is organized around three complementary strategies:

1. Multimodal neurophysiologic probing of residual brain function

We use EEG-based paradigms involving music, language, and sensory stimulation to probe hierarchical auditory, semantic, and attentional processing in unresponsive patients. These paradigms are designed to detect preserved neural pathways even in the absence of motor output, allowing us to identify covert consciousness and stratify patients along biologically meaningful recovery trajectories. By integrating traditional evoked potentials with more sophisticated encoding and decoding approaches, we aim to move beyond binary “present/absent” markers toward continuous, mechanistically informed biomarkers of brain function.

2. AI-driven prognostication and state classification

A core focus of my work is the development of machine-learning models that integrate electrophysiology, imaging, and clinical data to predict meaningful neurological outcomes. We apply explainable AI approaches to classify patients into distinct brain-response states, estimate individualized probabilities of recovery, and quantify uncertainty in prognostic predictions. These models are explicitly designed to complement clinical judgment, providing ICU teams and families with transparent, data-driven guidance during high-stakes decision-making.

3. Bedside communication and brain–computer interface development

Building on our ability to detect preserved cognition, we are developing scalable bedside tools that allow patients to communicate their basic needs. These platforms are designed to adapt to the patient’s residual abilities and serve as a foundation for future brain–computer interface–based communication in this vulnerable population. The overarching goal is to restore agency, dignity, and participation in care for patients who are otherwise unable to express themselves.

Using these approaches, my group has demonstrated that meaningful cognitive processing can be detected in a substantial subset of unresponsive patients and that these signals carry prognostic value beyond standard clinical assessments. Our ongoing work aims to translate these discoveries into routine ICU practice, shifting the field from population-level prognostication toward individualized, biology-informed care.

More broadly, my research is motivated by a translational mission: to change how coma and severe brain injury are understood, evaluated, and treated, while also advancing fundamental knowledge about the neural basis of consciousness through the study of disorders of consciousness. By leveraging these conditions as a window into how awareness, cognition, and intentional behavior are disrupted and preserved after brain injury, we aim to refine both clinical care and neuroscientific theory. By revealing hidden brain function and building pathways for recovery and communication, our work seeks to improve outcomes for patients and provide clarity, hope, and ethical grounding for families and care teams navigating some of the most difficult decisions in medicine.