Time:
Wednesday, November 26, 2025, 10:00 AM

Venue:
Conference Room 1, 3rd Floor, Intelligence Building

Host:
Shan Yu — Researcher, Institute of Automation, Chinese Academy of Sciences

Speaker:
Zhewei Zhang — Postdoctoral Fellow, National Institutes of Health (NIH), USA

Abstract

Cognitive maps are central to flexible learning and decision-making in complex environments, allowing animals to infer hidden structures and predict outcomes. The hippocampus (HC) and orbitofrontal cortex (OFC) are key regions involved in constructing cognitive maps, but their functional distinctions remain unclear.
This study combines electrophysiology and reinforcement learning models to explore dopaminergic firing patterns following HC or OFC lesions. Results indicate that HC lesions mainly disrupt representations of abstract, high-level states, whereas OFC lesions impair detailed, low-level states. Simultaneous recordings from both regions validate this division of labor.
These findings reveal complementary roles of HC and OFC in hierarchical cognitive mapping, deepening our understanding of neural mechanisms underlying flexible behavior and offering new insights into constructing hierarchical cognitive maps and reinforcement learning models in artificial intelligence.

Speaker Biography

Dr. Zhewei Zhang obtained his Ph.D. from the Institute of Neuroscience, Chinese Academy of Sciences (Center for Brain Science and Brain-Inspired Intelligence Technology). He is currently a Postdoctoral Fellow at the National Institutes of Health (NIH), working with Professor Geoffrey Schoenbaum. His research focuses on the neural mechanisms of reward-based learning and decision-making, particularly using electrophysiology and computational modeling.
Dr. Zhang has published first-author papers in Nature Communications and Current Biology, providing critical insights into the computational and neural principles of human cognition and decision-making.