Coursework
Fundamentals of Neuroscience
Course Link: Fundamentals of Neuroscience
Summary
This course will introduce learners to the fundamentals of neuroscience and the workings of individual neurons. Through interactive simulations, learners will build a neuron step by step and explore how neurons transmit information using electricity. In addition, learners will have the opportunity to visit a neuroscience lab at Harvard and gain practical knowledge on conducting DIY neuroscience experiments.
Documentation
Computational Neuroscience
Summary
The tutorials begin with an introduction to modeling in Neuroscience. It explores the various types of questions models can address, focusing on what happens, how it happens, and why it happens in the brain. The course delves into Machine Learning, teaching its applications in Neuroscience. Key concepts like model fitting, generalized linear models, dimensionality reduction, and deep learning are covered.
The Dynamical Systems module introduces the use of dynamical systems to create biologically plausible neuron and neuron network models. It covers linear systems, biological neuron models, and dynamic networks. The course then shifts to Stochastic Processes, dicussing Bayesian inference, hidden dynamics, and optimal control. These concepts are used to explore the brain’s computational mechanisms, aiming to answer why the brain operates in certain ways.
Documentation