resources

Articles and scholars that have captured my attention, challenged my scientific convictions, shaped my understanding, and inspired my favorite discussions.

Filter by topic, or explore a few favorites. ★ marks a favorite.

26 articles

• ★ Botch, T. L., & Finn, E. S. (2025). Sensory context as a universal principle of language in humans and LLMs. PsyArXiv Preprints. ›› [§ Botch, T. L., & Finn, E. S. (2025). Sensory context as a universal principle of language in humans and LLMs. PsyArXiv Preprints.]
• Celen, E., van Rijn, P., Lee, H., & Jacoby, N. (2025). Are Expressions for Music Emotions the Same Across Cultures?. arXiv preprint arXiv:2502.08744. ›››› [§ Celen, E., van Rijn, P., Lee, H., & Jacoby, N. (2025). Are Expressions for Music Emotions the Same Across Cultures?. arXiv preprint arXiv:2502.08744.]
• Cooney, G., & Wheatley, T. (2025). Conversation. In D. T. Gilbert, S. T. Fiske, E. J. Finkel, & W. B. Mendes (Eds.), The handbook of social psychology (6th ed.). Situational Press. ››› [§ Cooney, G., & Wheatley, T. (2025). Conversation. In D. T. Gilbert, S. T. Fiske, E. J. Finkel, & W. B. Mendes (Eds.), The handbook of social psychology (6th ed.). Situational Press.]
• Dingemanse, M., & Enfield, N. J. (2024). Interactive repair and the foundations of language. Trends in Cognitive Sciences, 28(1), 30-42. ››› [§ Dingemanse, M., & Enfield, N. J. (2024). Interactive repair and the foundations of language. Trends in Cognitive Sciences, 28(1), 30-42.]
• ★ Fedorenko, E., Duncan, J., & Kanwisher, N. (2013). Broad domain generality in focal regions of frontal and parietal cortex. PNAS, 110(41), 16616-16621. › [§ Fedorenko, E., Duncan, J., & Kanwisher, N. (2013). Broad domain generality in focal regions of frontal and parietal cortex. PNAS, 110(41), 16616-16621.]
• Fedorenko, E., Ivanova, A. A., & Regev, T. I. (2024). The language network as a natural kind within the broader landscape of the human brain. Nature Reviews Neuroscience, 25(5), 289-312. ›› [§ Fedorenko, E., Ivanova, A. A., & Regev, T. I. (2024). The language network as a natural kind within the broader landscape of the human brain. Nature Reviews Neuroscience, 25(5), 289-312.]
• Fedorenko, E., Piantadosi, S. T., & Gibson, E. A. (2024). Language is primarily a tool for communication rather than thought. Nature, 630(8017), 575-586. › [§ Fedorenko, E., Piantadosi, S. T., & Gibson, E. A. (2024). Language is primarily a tool for communication rather than thought. Nature, 630(8017), 575-586.]
• FeldmanHall, O., & Chang, L. J. (2018). Social learning: Emotions aid in optimizing goal-directed social behavior. In Goal-directed decision making (pp. 309–330). Academic Press. ››› [§ FeldmanHall, O., & Chang, L. J. (2018). Social learning: Emotions aid in optimizing goal-directed social behavior. In Goal-directed decision making (pp. 309–330). Academic Press.]
• ★ FeldmanHall, O., & Heffner, J. (2022). A generalizable framework for assessing the role of emotion during choice. American Psychologist, 77(9), 1017. ›› [§ FeldmanHall, O., & Heffner, J. (2022). A generalizable framework for assessing the role of emotion during choice. American Psychologist, 77(9), 1017.]
• FeldmanHall, O., & Nassar, M. R. (2021). The computational challenge of social learning. Trends in Cognitive Sciences, 25(12), 1045–1057. ››› [§ FeldmanHall, O., & Nassar, M. R. (2021). The computational challenge of social learning. Trends in Cognitive Sciences, 25(12), 1045–1057.]
• Heffner, J., & FeldmanHall, O. (2022). A probabilistic map of emotional experiences during competitive social interactions. Nature Communications, 13(1), 1718. ››› [§ Heffner, J., & FeldmanHall, O. (2022). A probabilistic map of emotional experiences during competitive social interactions. Nature Communications, 13(1), 1718.]
• Hoemann, K., Lee, Y., Kuppens, P., Gendron, M., & Boyd, R. L. (2023). Emotional granularity is associated with daily experiential diversity. Affective Science, 4(2), 291-306. ›› [§ Hoemann, K., Lee, Y., Kuppens, P., Gendron, M., & Boyd, R. L. (2023). Emotional granularity is associated with daily experiential diversity. Affective Science, 4(2), 291-306.]
• Houlihan, S. D., Kleiman-Weiner, M., Hewitt, L. B., Tenenbaum, J. B., & Saxe, R. (2023). Emotion prediction as computation over a generative theory of mind. Philosophical Transactions of the Royal Society A, 381(2251), 20220047. ››› [§ Houlihan, S. D., Kleiman-Weiner, M., Hewitt, L. B., Tenenbaum, J. B., & Saxe, R. (2023). Emotion prediction as computation over a generative theory of mind. Philosophical Transactions of the Royal Society A, 381(2251), 20220047.]
• ★ Jackson, J. C., Rand, D., Lewis, K., Norton, M. I., & Gray, K. (2017). Agent-based modeling: A guide for social psychologists. Social Psychological and Personality Science, 8(4), 387-395. ››› [§ Jackson, J. C., Rand, D., Lewis, K., Norton, M. I., & Gray, K. (2017). Agent-based modeling: A guide for social psychologists. Social Psychological and Personality Science, 8(4), 387-395.]
• ★ Jackson, J. C., Watts, J., Henry, T. R., List, J. M., Forkel, R., Mucha, P. J., et al. (2019). Emotion semantics show both cultural variation and universal structure. Science, 366(6472), 1517-1522. ››› [§ Jackson, J. C., Watts, J., Henry, T. R., List, J. M., Forkel, R., Mucha, P. J., et al. (2019). Emotion semantics show both cultural variation and universal structure. Science, 366(6472), 1517-1522.]
• ★ Kroll, J. F., Bobb, S. C., & Hoshino, N. (2014). Two languages in mind: Bilingualism as a tool to investigate language, cognition, and the brain. Current Directions in Psychological Science, 23(3), 159-163. › [§ Kroll, J. F., Bobb, S. C., & Hoshino, N. (2014). Two languages in mind: Bilingualism as a tool to investigate language, cognition, and the brain. Current Directions in Psychological Science, 23(3), 159-163.]
• Malik-Moraleda, S., Ayyash, D., Gallee, J., Affourtit, J., Hoffmann, M., Mineroff, Z., et al. (2022). An investigation across 45 languages and 12 language families reveals a universal language network. Nature Neuroscience, 25(8), 1014-1019. ›› [§ Malik-Moraleda, S., Ayyash, D., Gallee, J., Affourtit, J., Hoffmann, M., Mineroff, Z., et al. (2022). An investigation across 45 languages and 12 language families reveals a universal language network. Nature Neuroscience, 25(8), 1014-1019.]
• O’Nell, K. C., Sanchez, K. L., & Finn, E. S. (2025). Complex mutual adaptation in dyads’ semantic similarity trajectories predicts conversation success. PsyArXiv. ›››› [§ O’Nell, K. C., Sanchez, K. L., & Finn, E. S. (2025). Complex mutual adaptation in dyads’ semantic similarity trajectories predicts conversation success. PsyArXiv.]
• Rubio-Fernandez, P., Berke, M. D., & Jara-Ettinger, J. (2025). Tracking minds in communication. Trends in Cognitive Sciences, 29(3), 269-281. ›››› [§ Rubio-Fernandez, P., Berke, M. D., & Jara-Ettinger, J. (2025). Tracking minds in communication. Trends in Cognitive Sciences, 29(3), 269-281.]
• ★ Schloss, K. B. (2024). Color semantics in human cognition. Current Directions in Psychological Science, 33(1), 58–67. ›› [§ Schloss, K. B. (2024). Color semantics in human cognition. Current Directions in Psychological Science, 33(1), 58–67.]
• ★ Teoh, Y. Y., & FeldmanHall, O. (2025). Deviations from normative emotion representation predicts social and affective dysfunction. PsyArXiv Preprints. ››› [§ Teoh, Y. Y., & FeldmanHall, O. (2025). Deviations from normative emotion representation predicts social and affective dysfunction. PsyArXiv Preprints.]
• Tuckute, G., Kanwisher, N., & Fedorenko, E. (2024). Language in brains, minds, and machines. Annual Review of Neuroscience, 47, 277-301. ››› [§ Tuckute, G., Kanwisher, N., & Fedorenko, E. (2024). Language in brains, minds, and machines. Annual Review of Neuroscience, 47, 277-301.]
• Williams, C. C., Owen, L. L. W., Gunsilius, C., Nassar, M. R., & Petzschner, F. H. (2026). Computational signatures of pain chronification: Duration-dependent decision-making shifts across acute and chronic pain (Version 2). bioRxiv. ›› [§ Williams, C. C., Owen, L. L. W., Gunsilius, C., Nassar, M. R., & Petzschner, F. H. (2026). Computational signatures of pain chronification: Duration-dependent decision-making shifts across acute and chronic pain (Version 2). bioRxiv.]
• Wilson, R. C., & Collins, A. G. E. (2019). Ten simple rules for the computational modeling of behavioral data. eLife, 8, e49547. ›› [§ Wilson, R. C., & Collins, A. G. E. (2019). Ten simple rules for the computational modeling of behavioral data. eLife, 8, e49547.] [code & examples]
• ★ Wolna, A., Szewczyk, J., Diaz, M., Domagalik, A., Szwed, M., & Wodniecka, Z. (2024). Domain-general and language-specific contributions to speech production in a second language. Scientific Reports, 14(1), 57. ›› [§ Wolna, A., Szewczyk, J., Diaz, M., Domagalik, A., Szwed, M., & Wodniecka, Z. (2024). Domain-general and language-specific contributions to speech production in a second language. Scientific Reports, 14(1), 57.]
• Zada, Z., Goldstein, A., Michelmann, S., Simony, E., Price, A., Hasenfratz, L., et al. (2024). A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations. Neuron, 112(18), 3211–3222.e5. ››››› [§ Zada, Z., Goldstein, A., Michelmann, S., Simony, E., Price, A., Hasenfratz, L., et al. (2024). A shared model-based linguistic space for transmitting our thoughts from brain to brain in natural conversations. Neuron, 112(18), 3211–3222.e5.]

Simple companions for everyday science.

• An Introduction to Pipelines and Code-building with ClassesAn approachable introduction to Python classes and object-oriented programming, especially for the moment when a collection of scripts starts becoming a pipeline.
• Coding Cheat SheetsA collection of quick references for the syntax and tools that don’t always stay in one’s head.
• {here}A simpler way to find your files in R, and a little less time wondering where your working directory has wandered.

For the intersection of scientific clarity and visual curiosity: ways of making patterns easier to see, understand, and share.

• ninejs galleryA gallery of interactive visualization examples to explore when thinking about how a figure might invite a little more participation.
• The R Graph GalleryA collection of charts made with R, with code to help turn a visual idea into a figure.

Collections that make it possible to ask new questions about language, meaning, and the ways we relate to one another.

• CLICSA database of cross-linguistic colexifications: cases in which a language uses the same word for multiple concepts. A starting point for exploring how languages connect meanings.
• CANDORA corpus of naturalistic conversations, with audio, video, transcripts, and speakers’ reflections on their interactions. For those of us interested in what unfolds between people; access requires an application.

A gathering of essays, blogs, and other pieces that don’t quite belong on a textbook shelf. I don’t necessarily share the opinions in any given piece; I merely appreciate a thought-provoking read, and the conversations it might invite.

• A coding agent is six functions in a trenchcoatHadley Wickham on the small set of tools behind a coding agent.
• Theory of Mind as a Central Skill for ResearchersTom McCoy on considering other minds in the everyday work of writing, teaching, reviewing, and collaborating.
• The machines are fine. I’m worried about us.An essay from Ergosphere on AI and the people using it.
• Emotion research has a communication conundrumA piece from The Transmitter on how we talk about emotion in science.
• Slack is bad for thinkingTodd Gureckis on the relationship between our communication tools and the space we leave for thought.

References and support for organizing, carrying out, and communicating research.

• BIDSThe Brain Imaging Data Structure: a shared approach to organizing neuroimaging data.
• FreeSurferWikiDocumentation and guidance for structural and functional MRI analysis.
• Científico Latino Writing CenterSTEM writing support and resources.

A few places to begin, revisit the basics, or work through something new.

• Sam Hutchinson’s fMRI tutorialA walk through the Kanwisher Lab’s fMRI workflow, from localizer data to an analysis you can follow step by step.
• Naturalistic Data AnalysisFor studying brains amid stories, films, and other experiences that look a little more like life. A collection of Python tutorials on shared responses, individual differences, and the dynamics of naturalistic data.
• How to create a Slurm scriptA practical introduction from Johns Hopkins to asking a computing cluster to do some work for you.
• How Transformers Work: A Detailed, Conceptual ExplanationA video walkthrough by IbanDlank for thinking through transformers without beginning with code or equations.
• Computational Neuroscience: Exploring fMRI Data Analysis with PythonAn introduction to exploring fMRI data in Python, with examples to work through along the way.
• Andy’s Brain BookNeuroimaging walkthroughs, from getting oriented to working through an analysis.
• 3Blue1BrownAnimated mathematics by Grant Sanderson; a lovely invitation to build intuition alongside technique.