Simons Institute Courses

The Sparse Manifold Transform

Explore computational theories of the brain through the Sparse Manifold Transform, examining its applications in understanding neural processing and information representation in the visual system.

• YouTube
• 54 minutes
• Self-Paced
• Free Video

Networks of Spiking Neurons Learn to Learn and Remember

Explore how spiking neural networks acquire learning and memory capabilities, bridging computational neuroscience and artificial intelligence research.

• YouTube
• 55 minutes
• Self-Paced
• Free Video

An Algorithmic Theory of Brain Networks

Explore an algorithmic approach to understanding brain networks, examining computational theories and their implications for neuroscience and cognitive science.

• YouTube
• 49 minutes
• Self-Paced
• Free Video

The Brain as an Efficient, Robust Adaptive Learner

Explore how the brain functions as an efficient, robust, and adaptive learning system, drawing insights from computational theories and neuroscience research.

• YouTube
• 51 minutes
• Self-Paced
• Free Video

Predictive Coding Models of Perception

Explore cutting-edge theories on how the brain processes sensory information, focusing on predictive coding models and their implications for understanding perception.

• YouTube
• 52 minutes
• Self-Paced
• Free Video

Can the Brain's Structure Reveal its Function, Theoretically Speaking?

Explore the relationship between brain structure and function with Harvard's Jeff Lichtman, delving into cutting-edge neuroscience research and theoretical perspectives.

• YouTube
• 1 hour 18 minutes
• Self-Paced
• Free Video

The Deep Learning Revolution: What Does It Tell Us About Our Understanding of Intelligence?

Explore the implications of deep learning on our understanding of intelligence, examining its revolutionary impact and potential insights into cognitive processes.

• YouTube
• 51 minutes
• Self-Paced
• Free Video

Inferring Single-Trial Neural Population Dynamics Using Sequential Auto-Encoders

Explore cutting-edge techniques for analyzing neural population dynamics using sequential auto-encoders, with insights from Google researcher David Sussillo.

• YouTube
• 1 hour 36 minutes
• Self-Paced
• Free Video

Cortical Areas Interact through a Communication Subspace

Explore how cortical areas communicate through subspaces, examining neural population dynamics and inter-area interactions in visual processing using advanced data analysis techniques.

• YouTube
• 1 hour 13 minutes
• Self-Paced
• Free Video

Optimizing Robot Action Around and For People

Explore strategies for optimizing robot actions in human environments, focusing on prediction, interaction, and shared utility to enhance human-robot collaboration and safety.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

Basal Ganglia Architecture for Reinforcement Learning

Explore the neural circuitry of basal ganglia and its role in reinforcement learning, focusing on representation, coding, and computation in neural networks.

• YouTube
• 34 minutes
• Self-Paced
• Free Video

Continuous 8 Hz Alternation between Divergent Representations in the Hippocampus

Explore hippocampal theta sequences and their role in memory, planning, and decision-making. Discover how neural activity alternates between representations of current and future possibilities.

• YouTube
• 33 minutes
• Self-Paced
• Free Video

Place-Cell Sequences in the Hippocampus

Explore hippocampal place-cell sequences and their role in neural circuits, focusing on representation, coding, and computation in the brain's spatial navigation system.

• YouTube
• 43 minutes
• Self-Paced
• Free Video

Supernova Detection

Explore cutting-edge techniques for detecting supernovae in real-time, enhancing our understanding of cosmic explosions and their implications for astrophysics.

• YouTube
• 1 hour 14 minutes
• Self-Paced
• Free Video

Bayesian Theories of Perception and Cognition

Explore Bayesian theories in perception and cognition, examining how the brain processes information and makes decisions based on probabilistic models and prior knowledge.

• YouTube
• 1 hour 38 minutes
• Self-Paced
• Free Video