/awesome-computational-neuroscience

An awesome list of computational neuroscience and computational cognitive science.

GNU General Public License v3.0GPL-3.0

Awesome Computational Neuroscience

An awesome list of computational neuroscience and computational cognitive science. I build this list only for my own use. I used to use bookmarks. But it is a bad way to organize things, I can hardly find what I want.

Other useful Computational neuroscience resources.

"DISCLAIMER: The contents of this list reflect my own personal interests and should not be taken as a recommendation or endorsement of any kind. Use of any information or resources provided in this list is at your own risk."

Table of contents generated with markdown-toc

Course

Computational Neuroscience

Computational Cognitive Science

Neuroscience

Psychology

Package

Computational Neuroscience

  • BrainPy - A flexible, efficient, and extensible framework for computational neuroscience and brain-inspired computation based on the JIT compilation.
  • Nengo - The Nengo Brain Maker is a Python package for building, testing, and deploying neural networks.
  • NeuroGym - NeuroGym is a curated collection of neuroscience tasks with a common interface. The goal is to facilitate training of neural network models on neuroscience tasks.

Computational Cognitive Science

  • HDDM - A python toolbox for hierarchical Bayesian parameter estimation of the Drift Diffusion Model (via PyMC).
  • Computational and Behavioral Modeling - CBM provides tools for hierarchical Bayesian inference
  • rlssm - A Python package for fitting reinforcement learning models, sequential sampling models, and combinations of the two, using Bayesian parameter estimation.
  • RL_DDM - Reinforcement learning + drift-diffusion model repository.
  • Bandits - Python library for Multi-Armed Bandits implements the following algorithms: Epsilon-Greedy, UCB1, Softmax, Thompson Sampling
  • NivTurk - Niv lab tools for securely serving and storing data from online computational psychiatry experiments.

Machine Learning

  • Tianshou - A reinforcement learning platform based on pure PyTorch.
  • Variational Bayesian Monte Carlo - VBMC is an approximate inference method designed to fit and evaluate computational models with a limited budget of potentially noisy likelihood evaluations.
  • BADS - BADS is a fast hybrid Bayesian optimization algorithm designed to solve difficult optimization problems, in particular related to fitting computational models

Talk

Summer School

Tutorial

Other tutorials see Online Resources for Systems and Computational Neuroscience

Intro:

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Books

Open Data

Podcast