Lecture
Dynamical modeling, decoding, and control of multiscale brain network activity
Related lectures (238)
Data-Driven Modeling in Neuroscience: Meenakshi Khosla
By Meenakshi Khosla explores data-driven modeling in large-scale naturalistic neuroscience, focusing on brain activity representation and computational models.
Optimization of Neuroprosthetic Systems
Explores the optimization of neuroprosthetic systems, including sensory feedback restoration and neural stimulation strategies.
Theinfluenceoftheeegonthebrain
This study aimed to investigate the influence of the brain on the brain behavior.
Neural Signals and Signal Processing
Explores neural signal modeling, nervous system structure, and fiber classification for understanding neural phenomena.
Neural Signals and Signal Processing: Modeling and Simulation
Covers the fundamentals of neural signals and signal processing, focusing on modeling and simulation of neural systems.
Motor Neuroprosthetics: Brain-Machine Interfaces
Explores Brain-Machine Interfaces for motor control and communication using neural signals.
Neuromorphic Computing: Concepts and Hardware Implementations
Covers neuromorphic computing, challenges in ternary and binary computing, hardware simulations of the brain, and new materials for artificial brain cells.
Network Simulation and Activity Dynamics
Explores neural network simulation, activity dynamics, and validation processes to ensure accurate predictions.
Integrative Benchmarking: Advancing System Models of Human Intelligence
Explores advancing system models of human intelligence through integrative benchmarking and the importance of Brain-Score for fair model comparisons.
The Microcircuits of Striatum in Silico
Explores the reconstruction of a full-scale mouse striatal cellular level model to integrate and interpret striatal data.