Headshot of Benjamin Young.

Benjamin Young

Associate professor of philosophy
University of Nevada, Reno

Benjamin Young is associate professor and director of graduate studies in philosophy at the University of Nevada, Reno. He is also a member of the graduate faculty in interdisciplinary neuroscience at the university’s Institute for Neuroscience. Previously he held a Kreitman Postdoctoral Fellowship in the Department of Brain and Cognitive Sciences at Ben-Gurion University of the Negev, as well as a visiting assistant professorship and postdoctoral fellowship in the Department of Cognitive Science at Hebrew University. Young conducts research at the intersection of cognitive neuroscience and philosophy, with a particular emphasis on olfaction.

Young’s book “Stinking Philosophy!” (MIT Press, 2024) brings together more than a decade of research on olfactory philosophy. His research on non-conceptual content, qualitative consciousness in the absence of awareness, and the perceptible objects of smell have appeared in journals such as Mind & Language, Neuroscience and Biobehavioral Reviews, Pacific Philosophical Quarterly and Philosophical Studies. Additionally, he is co-editor of the textbook “Mind, Cognition, and Neuroscience” (Routledge, 2022) and the collection “Theoretical Perspectives on Smell” (Routledge, 2023). Young is currently working on a book about the unconscious and our sense of self, tentatively titled “Don’t Tell Anyone.”

Explore more from The Transmitter

Illustration of a sheet of paper with a topography map-like pattern on it.

Why neural foundation models work, and what they might—and might not—teach us about the brain

These models can partly generalize across species, brain regions and tasks, suggesting that a set of machine-learnable rules govern neural population activity. But will we be able to understand them?

By Juan Gallego
13 April 2026 | 8 min read
A fragmenting cube hovers over a person reading a book.

Error equation predicts brain’s ability to generalize

Four statistical measurements of neural network geometry capture how well brains and artificial networks use what they already know to solve new problems, a study suggests.

By Natalia Mesa
10 April 2026 | 5 min read
A large, abstract shape flows out of a small box.

Embrace complexity to improve the translatability of basic neuroscience

Researchers must learn to view heterogeneity as an essential feature of the systems they study and a central consideration in experimental design, not a variable to control for or reduce.

By Linda Douw, Klaus Eyer, Lara Keuck
9 April 2026 | 5 min read