Speaker: Hemali Angne

Bio

Location : CoRE 301

Committee: 

Assistant Professor Qiong Zhang

Professor Amélie Marian

Professor Jacob Feldman

Associate Professor Yongfeng Zhang

Event Type: Qualifying Exam

Abstract: To understand how humans encode and retrieve information, memory research traditionally uses well-controlled laboratory experiments. For example, studying and recalling a list of discrete items. Although useful in uncovering fundamental memory mechanisms, lab experiments do not fully capture the range of dynamics and behaviors shown in real-world scenarios. In our work, we extend well-established theories from lab experiments to account for this broader range of behaviors revealed in naturalistic settings.The first naturalistic setting we considered was people remembering information with others in a group. To model group recall, we extended a cognitive model that captures how individuals recall a list of items alone. This model encodes studied items in a latent space, and recalls are made by searching for memories in this space. Our extended model captures and explains group memory behaviors, including collaborative inhibition: the counterintuitive finding that a group of people recalling information together remembers less than the same number of individuals recalling alone. Collaborative inhibition is captured through a model mechanism in which group members are influenced by each other's recalls. This influence synchronizes their memory search trajectories in the latent space, negatively affecting group performance.We next studied how people summarize stories and news articles. To understand the cognitive processes involved in summarization, we analyzed large datasets of human summaries for behavioral patterns studied in memory literature. Our work demonstrates that summarization is closely related to recall: the process of summarizing is constrained by mechanisms of memory recall, displaying behaviors that align with well-known memory effects of primacy, recency, and temporal contiguity. By additionally analyzing a dataset of story recall, we showed that naturalistic recall also takes the form of summarization, showing higher memorability for central information from a story. In more realistic settings, since recall is constrained by limited time and cognitive resources, it is rational to prioritize central information, maximizing informativeness while minimizing effort.Our ongoing work studies why the human memory system segments continuous experiences into discrete events at multiple levels of abstraction. To examine whether this event segmentation serves an adaptive purpose, we draw parallels between the outputs of neural network models, which are optimized solely for task performance, and human memory behaviors.

Organization: 

Contact  Assistant Professor Qiong Zhang

Zoom Link: https://rutgers.zoom.us/j/2577236013?pwd=YzF2VnpSRURlMDNGSkxhc0IrY2psZz09&omn=99528593216