HypoSyncNet is a deep learning model intended to explore the relationship between different hypothalamic neuron types and their electrical activity, with all effects being anticipated outcomes based on predictive simulations. By integrating single-cell data, electrophysiological data, and existing knowledge of neural systems, HypoSyncNet aims to predict and simulate the hypothalamus's neural activity and its potential physiological functions. The project combines reductionist and systems approaches to advance a deeper understanding of hypothalamic neural mechanisms.
Currently, HypoSyncNet is in the conceptual stage, and many aspects of the project may evolve. Extensive research and data gathering are required to determine the specific research direction moving forward.
The project is scheduled to start on December 25, 2024. Stay tuned!
