Scientific Computing in Neuroscience

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Related lectures (32)

Page 3 of 4

Engineering Neurons: Optogenetics

Explores the engineering of neurons using light, chemicals, and sound to modulate neural activity and behavior.

In Silico Neuroscience: Network Simulation

Delves into simulating network dynamics in in silico neuroscience, covering spontaneous and evoked activity, in-vitro and in-vivo simulations, and sensitivity analysis.

Neural Signals and Signal Processing

Explores neuronal signals, brain organization, measurement techniques, and MRI principles.

Biophysical Understanding of Neuronal Behavior

Explores the biophysical understanding of neuronal behavior, focusing on action potentials, neuron modeling challenges, and dendritic inhibition.

Introduction to Systems Neuroscience: Memory Systems Overview

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

Attractor Networks and Spiking Neurons

Explores attractor networks, spiking neurons, memory data, and realistic networks in neural dynamics.

Neural Networks: Hierarchical Models and Odor Taxis

Covers neural function, hierarchical models, odor taxis behaviors, and disparate circuit parameters in 18 slides.

Blue Brain: Neocortical Microcircuitry

Covers the Blue Brain project's history, neocortical microcircuitry, neuron morphologies, and ion channel behavior.

Engineering Neurons: Light, Chemicals, Sound

Explores optogenetics, chemogenetics, and sonogenetics to engineer neural activity using light, chemicals, and sound.

Efficient Stochastic Numerical Methods

Explores efficient stochastic numerical methods for modeling and learning, covering topics like the Analytical Engine and kinase inhibitors.