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Prerequisites and preparatory materials for NMA Computational Neuroscience
Neuro Video Series (W0D0)

Python Workshop 1 (W0D1)

Python Workshop 2 (W0D2)

Linear Algebra (W0D3)

Calculus (W0D4)

Statistics (W0D5)

Model Types (W1D1)

Modeling Practice (W2D1)

Model Fitting (W1D2)

Generalized Linear Models (W1D3)

Dimensionality Reduction (W1D4)

Deep Learning (W1D5)

Autoencoders (Bonus)

Machine Learning Wrap-Up

Linear Systems (W2D2)

Biological Neuron Models (W2D3)

Dynamic Networks (W2D4)

Dynamical Systems Wrap-Up

Bayesian Decisions (W3D1)

Hidden Dynamics (W3D2)

Optimal Control (W3D3)

Reinforcement Learning (W3D4)

Network Causality (W3D5)

Stochastic Processes Wrap-Up

Daily guide for projects

Modeling Step-by-Step Guide

Project Templates

Site Navigation

Schedule
Technical Help
Quick links and policies
Prerequisites and preparatory materials for NMA Computational Neuroscience
Neuro Video Series (W0D0)

Python Workshop 1 (W0D1)

Python Workshop 2 (W0D2)

Linear Algebra (W0D3)

Calculus (W0D4)

Statistics (W0D5)

Model Types (W1D1)

Modeling Practice (W2D1)

Model Fitting (W1D2)

Generalized Linear Models (W1D3)

Dimensionality Reduction (W1D4)

Deep Learning (W1D5)

Autoencoders (Bonus)

Machine Learning Wrap-Up

Linear Systems (W2D2)

Biological Neuron Models (W2D3)

Dynamic Networks (W2D4)

Dynamical Systems Wrap-Up

Bayesian Decisions (W3D1)

Hidden Dynamics (W3D2)

Optimal Control (W3D3)

Reinforcement Learning (W3D4)

Network Causality (W3D5)

Stochastic Processes Wrap-Up

Daily guide for projects

Modeling Step-by-Step Guide

Project Templates

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Introduction

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Technical Help
- Using jupyterbook
  - Using Google Colab
  - Using Kaggle
- Using discord

Quick links and policies

Prerequisites and preparatory materials for NMA Computational Neuroscience

Pre-reqs Refresher

Neuro Video Series (W0D0)
Python Workshop 1 (W0D1)
- Tutorial: LIF Neuron Part I
Python Workshop 2 (W0D2)
- Tutorial 1: LIF Neuron Part II
Linear Algebra (W0D3)
Calculus (W0D4)
Statistics (W0D5)

Intro to Modeling

Model Types (W1D1)
Modeling Practice (W2D1)

Machine Learning

Model Fitting (W1D2)
Generalized Linear Models (W1D3)
Dimensionality Reduction (W1D4)
Deep Learning (W1D5)
Autoencoders (Bonus)
Machine Learning Wrap-Up

Dynamical Systems

Linear Systems (W2D2)
Biological Neuron Models (W2D3)
Dynamic Networks (W2D4)
Dynamical Systems Wrap-Up

Stochastic Processes

Bayesian Decisions (W3D1)
Hidden Dynamics (W3D2)
Optimal Control (W3D3)
Reinforcement Learning (W3D4)
Network Causality (W3D5)
Stochastic Processes Wrap-Up

Project Booklet

Introduction
Daily guide for projects
Modeling Step-by-Step Guide
Datasets
- Neurons
  - Guide
  - Overview videos
- fMRI
  - Guide
  - Overview videos
- ECoG
  - Guide
  - Overview videos
- Behavior
  - Guide
  - Overview videos
- Theory
  - Guide
Project Templates
Projects 2020
- Neurons
- Theory
- Behavior
- fMRI
- EEG

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.ipynb

Overview videos

Contents

Video: Kay/Gallant dataset
Video: HCP dataset
Video: HCP dataset (2021 video)
Video: FSLcourse task fMRI
Video: HCP retinotopy
Video: Algonauts dataset
Video: Bonner dataset
Video: Cichy dataset

Overview videos#

Video: Kay/Gallant dataset#

Video: HCP dataset#

Video: HCP dataset (2021 video)#

Video: FSLcourse task fMRI#

Video: HCP retinotopy#

Video: Algonauts dataset#

Video: Bonner dataset#

Video: Cichy dataset#

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Guide to choosing an FMRI dataset

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ECoG

On this page

Video: Kay/Gallant dataset
Video: HCP dataset
Video: HCP dataset (2021 video)
Video: FSLcourse task fMRI
Video: HCP retinotopy
Video: Algonauts dataset
Video: Bonner dataset
Video: Cichy dataset

By Neuromatch

Last updated on None.

The contents of this repository are shared under the Creative Commons Attribution 4.0 International License. Software elements are additionally licensed under the BSD (3-Clause) License.