Dynamical modeling, decoding, and control of multiscale brain network activity

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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.

Introduction to Systems Neuroscience: Memory Systems Overview

Introduces systems neuroscience, focusing on neural circuits, memory systems, and course logistics.

Brain Intelligence: Continual Learning of Representational Models

Delves into the continual learning of representational models after deployment, highlighting the limitations of current artificial neural networks.

The Microcircuits of Striatum in Silico

Explores the reconstruction of a full-scale mouse striatal cellular level model to integrate and interpret striatal data.

Brain-Computer Interfaces: Advancements in Systems Neuroscience

Covers brain-computer interfaces and their impact on systems neuroscience and neuroprosthetics.

Neuroscience and Machine Learning: Understanding Visual Intelligence

Explores the relationship between neuroscience and machine learning in visual intelligence.

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.

Scientific Computing in Neuroscience

Explores the history and tools of scientific computing in neuroscience, emphasizing the simulation of neurons and networks.

Optimization of Neuroprosthetic Systems

Explores the optimization of neuroprosthetic systems, including sensory feedback restoration and neural stimulation strategies.

Miniaturized CMOS Interfaces

Explores miniaturized CMOS interfaces for neural signals processing and neurostimulation.