Research topic
Models of neural responses whose predictions can be tested on held-out data.
Independent educational guide. Not affiliated with or endorsed by the universities, professors or laboratories described here. This collection reflects the material currently mapped on Socratic Learn.
Human Motor Control and Neuromodulation Laboratory: linking quantitative movement measurements with implanted subthalamic local field potentials and neuromodulation to understand Parkinson’s disease and develop personalized adaptive therapies.
5 lessons · ~27 minutes
Explore the labControlling, mapping and modeling neural circuits across cell types, space and behavior.
9 lessons · ~48 minutes
Explore the labBerkeley RAIL research studies robot learning from demonstrations, reward, prior datasets, and interaction: policies, reinforcement learning, manipulation, and generalization. The independent Levine primer also covers his co-founder work at Physical Intelligence, a separate company.
7 lessons · ~37 minutes
Explore the labHow retinal circuits transform visual information, adapt and compute; models that connect predictions to mechanisms.
6 lessons · ~45 minutes
Explore the labRecommended through the concepts linked to this topic. Each lesson belongs to an existing learning series.
Controlling, Mapping, and Modeling Neural Circuits
From cell types to brain-wide dynamics and behaviorDescribe distributed population activity using neural states and trajectories.
Supports: Neural network models
Neural Circuits, Vision, and Computation
From neural data to interpretable modelsDescribe a linear-nonlinear model r(t) = f(k * s(t)) and how it is evaluated on held-out data.
Supports: Neural network models
Decode Life: AI & Computational Biology
Train, validation and test setsTraining fits model parameters; validation guides choices; a held-out test estimates performance on unseen cases.
Supports: Neural network models
Decoding and Restoring Movement in Parkinson’s Disease
AI, gait, and the future of personalized neuromodulationInterpret neural and wearable gait biomarkers within their measurement limits.
Supports: Neural network models
How Robots Learn
From programming robots to teaching robotsExplain a policy and the closed perception-action loop.
Supports: Neural network models
How Robots Learn
Physical Intelligence: building a foundation model for robotsDistinguish a VLM from a VLA and a company goal from demonstrated capability.
Supports: Neural network models
No source-backed papers mapped here yet.