Contents

Acknowledgements

One page cannot contain everyone who has shaped me and this dissertation. Thank you, everyone. A little bit of you is in each of these pages.

First, I want thank my advisor Konrad for taking a chance on a PhD student in a different field wanting to start it all over. My life took a different turn in that moment. Konrad gifts his lab a true freedom. In the following years I was free to think, to grow, and to discover neuroscience and find my place within it. Few scientists have such a willingness to question the big picture. I’m especially thankful for his conviction that science is a social enterprise, and everything that meant for our lab and broader scientific community. I feel very fortunate to have “grown up” in this kind, curious, and lively environment and to have absorbed some of his wise approach to science.

I’d like to thank all the members of the Kording lab, past and present, who showed me how to ask better questions and find meaning within computational neuroscience. It was easy to find purpose with the easy guidance of friends who knew their stuff.

Computational neuroscience is a wonderful community, and I’m lucky to have found myself within it. The COSYNE conference community, Neuromatch, Penn’s computational neuroscience, and the CCN conference have made this science very enjoyable. Thank you for such an open and collaborative community.

I have many collaborators to thank. Thank you to Josh Glaser and Roozbeh Farhoodi, with whom it was always a pleasure to work aside. Pavan Ramkumar kindly shared his knowledge and showed me gracious patience when I was just a first-year. Thanks to David Rolnick, whose lively discussion I always looked forward to. The same is true for Richard Lange, who I also wish to thank for his thoughtful insight on many issues in representation learning and Bayesian inference. I have a warm thanks for Professor Lee Miller and Matthew Smith and their collaboration, and especially to Matt who has lent a kind perseverance as our paper has had its odyssey in peer review. Ling-Qi Zhang has been a partner in thought in wonderful ways. For showing me the world of visual psychophysics, I am also thankful to Cheng Qiu and Alan Stocker.

For shaping me as a scientist, I also must thank the incredible educators of Northampton, MA, as well as every physics professor at Williams College. You showed me how to think and demonstrated a truly infectious love of teaching. Also to Joe Cruz and Safa Zeki at Williams who, though they do not know it, sparked an interest in the mind and brain that grew to this dissertation.

Thank you, Kate, for encouraging me to stay true to what I love, for building a life with adventure, care, and curiosity, and for showing me what an active, ethical engagement with society can look like.

Finally, I am infinitely grateful to my parents, who saw the creative, curious scientific spark in me at a young age and did everything to encourage it. Their boundless care for me and my wellbeing made me everything I am.

References

This online format of this dissertation was developed by Patrick Minealt for The Good Research Code Handbook¶ . This book was generated by jupyterbook, which builds on Sphinx. The stylesheet is an adaptation of tufte.css.