MIT News  November 2, 2022 The central claims of recent deep learning-based models of brain circuits are that they make novel predictions about neural phenomena or shed light on the fundamental functions being optimized. Through the case-study of grid cells in the entorhinal-hippocampal circuit, a team of researchers in the US (Stanford University, MIT) showed that one often gets neither. They reviewed the principles of grid cell mechanism and function obtained from analytical and first-principles modeling efforts and examined the claims of deep learning models of grid cells. Using large-scale hyperparameter sweeps and theory-driven experimentation, they demonstrated that the results […]