May of my classes are centered around using models to understand brain and cognition. Sadly, there exists no textbook that I could use. Some common textbooks (Sutton and Barto for reinforcement learning; Abbot and Dayan for neural networks) are expensive and will be used only for very specific pieces of my class. So, most of the time, I have used a collection of review papers to cover the different topics, which turned out to be quite unsatisfactory. A couple of years back, I bit the bullet and, together with my colleague Catherine Sibert, I began writing our own free “textbook”. It is still a work-in-progress, but here it is.
It is online, rather than printed, for a variety of reasons. First, it is not polished. Far from it. In fact, I appreciate any feedback on any of its aspects. Second, it is not only made of printed material. All the figures are generated by actual, running demo code that is available on Jupyter Notebooks. And, finally, I want to keep updating it often.
The entire book can be downloaded here: Exploratory Models in Cognitive Neuroscience 
And here is a table of contents. I will put it online as a I convert the PDF into HTML.
- Introduction
- Part 1: Symbolic models
- Reinforcement Learning Models
- Accumulator Models
- Models of Long-term Memory
- Part 2: Neural networks
- Feedforward neural networks
- Hebbian-learning methods
- Autoassociators
- Recurrent networks and Large Language models
Andrea Stocco 