Project Summary/ Abstract The researcher's central career goal is to become an independent researcher investigating disorders of consciousness (DoC), with a specific emphasis on using non-invasive neurostimulation to restore accurate conscious perception. Despite ongoing research efforts, gaps persist in the understanding of consciousness, and recent findings suggest promising avenues for neurostimulation therapies. Aim 1 of the dissertation research project involves utilizing functional magnetic resonance imaging (fMRI) to map brain networks associated with auditory perception without explicit reporting. The thesis work establishes a paradigm and machine learning model that eliminates the need for explicit reporting, mitigating confounding signals related to reporting. Preliminary data indicate success in inducing threshold-level perception, identifying eye metrics specific to auditory conscious perception, and a successful machine learning model to predict auditory perception based on eye tracking. Aim 1.2 will identify the neuronal activity associated with this more purified measure of perception. Auditory conscious perception is hypothesized to involve three major brain networks independent of task report: 1. Detection/arousal/salience networks, 2. Task-positive attention networks, and 3. Default mode network. This work will improve our capacity to identify auditory perception in those who may not be able to report their experiences and holds promise to help identify targets for neuromodulation to improve disorders of consciousness. Aim 2, the postdoctoral research direction, advances neuromodulation strategies for DoC. Current approaches like transcranial direct current stimulation (tDCS) and deep brain stimulation (DBS) have limitations, and the researcher proposes exploring transcranial, low-intensity, low-frequency focused ultrasound (tFUS) as a potential solution. tFUS offers spatially precise neuromodulation of deep brain structures without surgery, demonstrating safety and neuroactivity in animal models and healthy human volunteers. The plan is to contribute to the broader field of neuromodulation research by advancing understanding of tFUS's modulatory effects on neural networks associated with consciousness. Essential skills to be acquired include a comprehensive understanding and practical skills related to tFUS technology and gaining clinical insight into DoC and working with clinical populations. The training in both aims will significantly enhance the researcher's proficiency in neuroimaging, machine learning, and neuromodulation approaches, laying a solid foundation for future academic pursuits.