Events

Title:A multimodal sleep foundation model for disease prediction Abstract: Sleep is a fundamental biological process with broad implications for physical and mental health, yet its complex relationship with disease remains poorly understood. Polysomnography (PSG)—the gold standard for sleep analysis—captures rich physiological signals but is underutilized due to challenges in standardization, generalizability and multimodal integration. To…

Herbert Zheng Wu Title: Neural Basis of Leader–Follower Dynamics in Cooperative Behavior Abstract: Cooperation allows social species to achieve outcomes that individuals cannot accomplish alone. Even in simple groups, cooperative behavior often depends on complementary social roles such as leaders and followers, yet the neural computations supporting these dynamic relationships are not well understood. Our lab investigates…

1) Charlotte onboarded vision and audio MNIST dataloaders. She's focusing on predictive coding for sequential tasks (e.g., audio data/moving MNIST). 2) Todd built a multi-modal predictive coding baselines showing that unsupervised representation learning is possible here. 3) Eivinas proposed a backprop based autoencoder and Hebbian based autoencoder (maybe Exponentiated Gradients?). 4) Nihal offered to onboard…