Introduction

Introduction#

This guide explores computational techniques and concepts central to modern cognitive neuroscience, with practical applications using PsyNeuLink. It designed for students, researchers, and practitioners who are interested in building and simulating cognitive and neural models.

The guide is divided into chapters. Each chapter covers a specific topic, such as decision making or reinforcement learning, and includes a mix of theoretical background, practical examples, and exercises.

Some pages include interactive Jupyter notebooks that allow you to run code and experiment with the concepts. The recommended way to use these notebooks is via live code, google colab, or binder. You can activate on of these mode clicking on the launch button at the top left of the page (the rocket symbol). This will allow you to run the code without installing anything on your computer. You can also download the jupyter notebooks and run them locally but some of the interactive features might not work. The guide uses tags to organize the content and make it easier for you to navigate. Here are the tags used in this guide:

  • 🎯️: Exercises - These sections include exercises to help you practice the concepts.

  • 💡: Hints - These sections provide hints to help you solve the exercises.

  • ✅: Solutions - These sections provide solutions to the exercises.

Content#

1 Primer

2 Dynamics in Perception

3 Decision Making

4 Reinforcement Learning

5 Statistical Learning and Backpropagation

Prerequisites#

This guide introduces PsyNeuLink, a Python package for building cognitive and neural models. It assumes familiarity with Python, Numpy, and basic programming concepts.

We recommend completing the PsyNeuLink Beginner Tutorial to gain foundational knowledge of the PsyNeuLink environment, unless you are already familiar with it.

When Things Go Wrong#

This guide is a living document, and we are constantly working to improve the language and its documentation.

If you encounter any issues or have suggestions for improvement, let us know by:

Your feedback is invaluable in improving this guide and the PsyNeuLink ecosystem.

Additional Resources#

Contents