Graduate Student Seminar Series – Mohammad Rezaei

Presentation Title: Cognitive State Inference and the Impact of Deep Brain Stimulation on Decision-Making in Parkinson’s Disease

Abstract: Human cognition arises from the intricate interplay of neural and behavioral signals, shaped by dynamic interactions across distributed brain networks. Understanding these hidden cognitive states is particularly important in neurological disorders like Parkinson’s disease (PD), which impair cognitive functions and disrupt normal brain activity. This thesis focuses on developing computational models to infer cognitive states from high-dimensional neural and behavioral data and to evaluate the impact of deep brain stimulation (DBS) on cognitive abilities during decision-making processes. Specifically, it explores the temporal effects of DBS on PD patients’ cognitive abilities in high-conflict and no-conflict decision-making situations, introducing the Cognet model. This model, which simulates the dynamic interactions between the subthalamic nucleus (STN) and the medial prefrontal cortex (mPFC), provides insights into the optimal timing and modulation strategies for DBS to enhance cognitive function. The proposed models open new pathways for understanding the generation of neural and behavioral signals and the effects of neuromodulation on cognitive processes, contributing to the advancement of cognitive state inference and therapeutic interventions in neuroscience.

Supervisor Name: Milos Popovic

Year of Study: 5

Program of Study: PhD