Doing Psychological and Brain Science Research: A Field Report On Scientific Workflows

Author

Rich Ramsey

Published

October 29, 2026

Preface

This book has one fundamental premise. The foundations of scientific claims should be easy to access and verify. This is not just about promoting trust between scientists to help build on past research effectively. It also stems from a moral obligation. Most modern science is publicly funded, and therefore it should be available to serve the public.

Of course, the need to verify the foundations for other scientist’s claims is far from a new problem. For centuries (or longer) scientists have been confronted with this problem. This book just takes a snapshot of how modern tools can be arranged into a workflow to address it.

What follows is not a suggestion that this workflow is “correct” in any meaningful way. It is just one concrete template of a workflow that gets closer to a reality where we can meet the fundamental challenge that our work can be easy to access and verify. As such, this book is a field report on current scientific workflows from an active cognitive neuroscience lab. It is not a manifesto for change or a best-practice manual.

Who is this book for

This book is primarily written for future me (so I don’t forget), as well as for people in my group and for collaborators. The hope is that it replaces conversations that tend to happen repeatedly as new people join a project. Such conversations are necessary but hard to scale, and people cannot reasonably retain everything instantly.

Of course, other psychology or brain science researchers may find it useful too. At the broadest level, given that the fundamentals apply to any quantitative project, folks in wider domains of behavioural science, medicine, biology, and neuroscience might be interested too. Ultimately, the book is situated in psychological and brain science research, since that is what I am familiar with.

Prerequisites

No prior material understanding of psychology or cognitive neuroscience is required: it is the principles and infrastructure that matters most, rather than domain-specific topics or methods.
Basic programming skills in R (or another language).
Familiarity with the basic aims of common data analysis and statistical approaches.
Some basic sense of common research designs, such as experimental vs. cross-sectional designs.
An understanding that much of psychology and cognitive neuroscience research involves data collected from human participants.

Basic structure

After introductory chapters, which provide relevant historical context and general aims and scope, the book follows the rough chronology of a research project — from the initial commitment to make your work findable and reusable, through planning, data management, processing, visualisation, and analysis, to dissemination. The infrastructure that holds all of this together (code, version control, reproducible pipelines) gets its own chapter early on, because without it the rest is harder. Each chapter is short by design. The goal is to be clear about what we do and not to be comprehensive. Where others have written better and more technical accounts of a particular topic, I point to them and move on.

Themes

There are two broad themes that intersect across the book.

Theme 1: Domain-general software tools that are likely to be relevant for any scientific project.

Theme 2: A scienfitic workflow for research projects in psychology, neuroscience and related disciplines.

What this book is not

This book is not:

A psychology or cognitive neuroscience textbook. Therefore, it does not cover core topics, methods or controversies in cognitive neuroscience.
An attempt to describe or prescribe “best-practice” in any sense. Instead, the book just reflects current and ongoing practice in one lab. Therefore, it reflects a specific stack of tools, practices, and choices that have accumulated in one lab over one particular period. Other labs may have made different choices for good and/or bad reasons.
A manifesto for “open science” in the sense of supporting or advocating for an organised movement associated with open science practices.
A “how-to” guide with tutorials on specific implementation.

A note on tools

Where specific tools are mentioned (e.g., R, brms, Stan, Git, OSF, Docker, Zenodo), keep in mind that these reflect what we currently use, not what we think everyone should use. The underlying principles of reproducibility, transparency, and clear uncertainty quantification are the point. The tools are one implementation of those principles.

How should you read this book?

Ideally, the book is intended to be read linearly, as the chapters do build on each other. And the later chapters may be easier to digest and understand if you understand the basic aims and setup. However, each chapter is largely self-contained and can be read in isolation. Therefore, if there is a particular topic that you want to focus on, then just go straight to that chapter.

Living document and updates

The book is intended to be a living document, which changes as things change in scientific workflows. Therefore, substantial updates will be released and versioned accordingly.

Disclaimers

I am not a software engineer and I have no formal training in this domain. My training is in experimental psychology and cognitive neuroscience. The purpose of this book is to provide a practical example of a current scientific workflow based on my training and perspective as an active researcher. Therefore, in the sections on infrastructure and software, I will discuss tools that I use, rather than develop myself. This means that I am very much a beginner in the software space and I use these tools out of what I perceive to be a necessary condition of doing modern science.

Acknowledgements

License and citation

Code

@book{RamseyDoingPsychBrainScience2026,
  title = {Doing Psychological and Brain Science Research: A Field Report On Scientific Workflows},
  author = {Ramsey, Richard},
  year = {2026},
  month = {10},
  edition = {version 0.1},
  url = {https://rich-ramsey.github.io/doing-psych-brain-science/}
}

# Preface {.unnumbered} This book has one fundamental premise. The foundations of scientific claims should be easy to access and verify. This is not just about promoting trust between scientists to help build on past research effectively. It also stems from a moral obligation. Most modern science is publicly funded, and therefore it should be available to serve the public. Of course, the need to verify the foundations for other scientist's claims is far from a new problem. For centuries (or longer) scientists have been confronted with this problem. This book just takes a snapshot of how modern tools can be arranged into a workflow to address it. What follows is not a suggestion that this workflow is "correct" in any meaningful way. It is just one concrete template of a workflow that gets closer to a reality where we can meet the fundamental challenge that our work can be easy to access and verify. As such, this book is a field report on current scientific workflows from an active cognitive neuroscience lab. It is not a manifesto for change or a best-practice manual. ## Who is this book for This book is primarily written for future me (so I don't forget), as well as for people in my group and for collaborators. The hope is that it replaces conversations that tend to happen repeatedly as new people join a project. Such conversations are necessary but hard to scale, and people cannot reasonably retain everything instantly. Of course, other psychology or brain science researchers may find it useful too. At the broadest level, given that the fundamentals apply to ***any*** quantitative project, folks in wider domains of behavioural science, medicine, biology, and neuroscience might be interested too. Ultimately, the book is situated in psychological and brain science research, since that is what I am familiar with. ## Prerequisites - No prior material understanding of psychology or cognitive neuroscience is required: it is the principles and infrastructure that matters most, rather than domain-specific topics or methods. - Basic programming skills in R (or another language). - Familiarity with the basic aims of common data analysis and statistical approaches. - Some basic sense of common research designs, such as experimental vs. cross-sectional designs. - An understanding that much of psychology and cognitive neuroscience research involves data collected from human participants. ## Basic structure After introductory chapters, which provide relevant historical context and general aims and scope, the book follows the rough chronology of a research project — from the initial commitment to make your work findable and reusable, through planning, data management, processing, visualisation, and analysis, to dissemination. The infrastructure that holds all of this together (code, version control, reproducible pipelines) gets its own chapter early on, because without it the rest is harder. Each chapter is short by design. The goal is to be clear about what we do and not to be comprehensive. Where others have written better and more technical accounts of a particular topic, I point to them and move on. ## Themes There are two broad themes that intersect across the book. **Theme 1:** Domain-general software tools that are likely to be relevant for ***any*** scientific project. **Theme 2:** A scienfitic workflow for research projects in psychology, neuroscience and related disciplines. ## What this book is not This book is not: - A psychology or cognitive neuroscience textbook. Therefore, it does not cover core topics, methods or controversies in cognitive neuroscience. - An attempt to describe or prescribe "best-practice" in any sense. Instead, the book just reflects current and ongoing practice in one lab. Therefore, it reflects a specific stack of tools, practices, and choices that have accumulated in one lab over one particular period. Other labs may have made different choices for good and/or bad reasons. - A manifesto for "open science" in the sense of supporting or advocating for an organised movement associated with open science practices. - A "how-to" guide with tutorials on specific implementation. ## A note on tools Where specific tools are mentioned (e.g., R, brms, Stan, Git, OSF, Docker, Zenodo), keep in mind that these reflect what we currently use, not what we think everyone should use. The underlying principles of reproducibility, transparency, and clear uncertainty quantification are the point. The tools are one implementation of those principles. ## How should you read this book? Ideally, the book is intended to be read linearly, as the chapters do build on each other. And the later chapters may be easier to digest and understand if you understand the basic aims and setup. However, each chapter is largely self-contained and can be read in isolation. Therefore, if there is a particular topic that you want to focus on, then just go straight to that chapter. ## Living document and updates The book is intended to be a living document, which changes as things change in scientific workflows. Therefore, substantial updates will be released and versioned accordingly. ## Disclaimers I am not a software engineer and I have no formal training in this domain. My training is in experimental psychology and cognitive neuroscience. The purpose of this book is to provide a practical example of a current scientific workflow based on my training and perspective as an active researcher. Therefore, in the sections on infrastructure and software, I will discuss tools that I use, rather than develop myself. This means that I am very much a beginner in the software space and I use these tools out of what I perceive to be a necessary condition of doing modern science. ## Acknowledgements ## License and citation © Rich Ramsey, ETH Zürich. Licensed under [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/). ```{r} #| eval: false @book{RamseyDoingPsychBrainScience2026, title = {Doing Psychological and Brain Science Research: A Field Report On Scientific Workflows}, author = {Ramsey, Richard}, year = {2026}, month = {10}, edition = {version 0.1}, url = {https://rich-ramsey.github.io/doing-psych-brain-science/} } ```