4 papers
Measuring and Controlling Solution Degeneracy across Task-Trained Recurrent Neural Networks
Ann Huang, Satpreet H. Singh, Flavio Martinelli +1
Task-trained recurrent neural networks (RNNs) are widely used in neuroscience and machine learning to model dynamical computations. To gain mechanistic insight into how neural syst…
Active Electrosensing and Communication in MARL-trained Weakly Electric Fish Collectives
Satpreet H. Singh, Sonja Johnson-Yu, Zhouyang Lu +7
How complex collective behavior emerges from individual interactions is a fundamental scientific question, but experimental cost and difficulty of simultaneous multi-brain recordin…
InputDSA: Demixing then Comparing Recurrent and Externally Driven Dynamics
Ann Huang, Mitchell Ostrow, Satpreet H. Singh +3
In control problems and basic scientific modeling, it is important to compare observations with dynamical simulations. For example, comparing two neural systems can shed light on t…
Dissecting Larval Zebrafish Hunting using Deep Reinforcement Learning Trained RNN Agents
Raaghav Malik, Satpreet H. Singh, Sonja Johnson-Yu +4
Larval zebrafish hunting provides a tractable setting to study how ecological and energetic constraints shape adaptive behavior in both biological brains and artificial agents. Her…