Search Results for author:
Found 5 papers, 4 papers with code
Neural Foundations of Mental Simulation: Future Prediction of Latent Representations on Dynamic Scenes
In particular, we find that neural responses are currently best predicted by models trained to predict the future state of their environment in the latent space of pretrained foundation models optimized for dynamic scenes in a self-supervised manner.
Modeling Human Eye Movements with Neural Networks in a Maze-Solving Task
This not only provides a generative model of eye movements in this task but also suggests a computational theory for how humans solve the task, namely that humans use mental simulation.
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity
We curate four datasets of neural spiking activity from cognitive, sensory, and motor areas to promote models that apply to the wide variety of activity seen across these areas.
Interpreting neural computations by examining intrinsic and embedding dimensionality of neural activity
The ongoing exponential rise in recording capacity calls for new approaches for analysing and interpreting neural data.
Modular Object-Oriented Games: A Task Framework for Reinforcement Learning, Psychology, and Neuroscience
In recent years, trends towards studying simulated games have gained momentum in the fields of artificial intelligence, cognitive science, psychology, and neuroscience.
