Doctoral Defense
Detecting Early Signs of Recovery of Consciousness and a Computational Model on Working Memory
Xi Cheng
December 5, 2024
2:00 PM
Light Engineering, Room 250
Advisor: Sima Mofakham
Recovery of consciousness after acute brain injury is difficult to detect, leading to significant challenges for care and prognosis. Some patients may even recover consciousness “covertly,” meaning they are aware, but clinicians cannot detect voluntary movement. We hypothesized that low-amplitude movements precede larger-amplitude voluntary movements detectable by clinicians after acute brain injury. To test this hypothesis, we developed and evaluated a novel computer vision-based tool called “SeeMe” that captures and quantifies the evoked response to spoken commands with a high spatiotemporal resolution. The prefrontal cortex (PFC) is vital for flexible behavior or cognitive control, but how task-relevant PFC dynamics emerge and evolve remains elusive. In this study, we built a data-grounded layer-specific PFC-basal ganglia (BG)-thalamus model to investigate neural bases of rule selection and working memory enabling cognitive control. This model replicated the recent experimental observation in non-human primates that the relevant abstract task rule in a working memory task initially emerged in thalamic and then transferred to the cortex.