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Neuromatch Academy: Computational Neuroscience (Experimental)

Introduction

Schedule

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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Contents

Video: Steinmetz dataset
Video: Stringer dataset
Video: Allen Institute dataset

Overview videos

Contents

Video: Steinmetz dataset
Video: Stringer dataset
Video: Allen Institute dataset

Overview videos¶

Video: Steinmetz dataset¶

Video: Stringer dataset¶

Video: Allen Institute dataset¶

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Guide to choosing a Neurons dataset

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fMRI

By Neuromatch

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.