Dr. Nicole Rust
Professor, University of Pennsylvania
Dr. Nicole Rust remembers the moment that sparked her interest in neuroscience with perfect clarity. She was reading The Astonishing Hypothesis: The Scientific Search for the Soul by Francis Crick, when she read a profound passage:
“‘You’, your joys and your sorrows, your memories and your ambitions, your sense of personal identity and free will, are in fact no more than the behavior of a vast assembly of nerve cells and their associated molecules.”
Crick’s words were transformative for Nicole, shifting her plans from following in the footsteps of her family, a lineage of engineers living in the Idaho panhandle, to embarking on her own “search for the soul”—studying the brain. Now, as a Professor and brain researcher in the Department of Psychology at the University of Pennsylvania, Nicole has a long history of studying the neural and computational basis of vision and visual memory. Following on insights she gained while writing her recent book, she's transitioning to study the equivalent for human emotion and mood.
Nicole was an undergraduate at the University of Idaho when she decided she wanted to pursue a career in neuroscience, but her university didn’t have many early research opportunities. She supplemented her major in molecular biology and biochemistry with summer research experiences through programs at the University of Florida Whitney Lab and the University of Texas, Houston. She also worked as a lab technician before starting her PhD at New York University (NYU). She chose her PhD advisor at NYU, Tony Movshon, because their first conversations about science were so fascinating that she couldn’t go to sleep that night out of pure excitement. Her enthusiasm paid off and over the course of her PhD and a brief postdoc (jointly advised by Eero Simoncelli), she published groundbreaking research about how motion is perceived holistically in the hierarchy of the visual system.
When we perceive a moving object, the early responses of motion-selective neurons in the primary visual cortex (V1), which respond to the motion of object parts, must be integrated into a percept of coherent object motion by brain areas further downstream along the path of visual processing. At the time of her PhD, the middle temporal area (MT) had been identified as a location that contributes to this integration, but the algorithm it used to transform V1 inputs into more holistic motion wasn’t fully understood. Nicole designed a computational model that captured how MT might pool and normalize inputs from V1 that included "hidden" suppression (not reflected in spiking responses following thresholding). She validated this model using neural spike recordings from monkeys viewing drifting gratings and patterns, and she published her results in Nature Neuroscience in 2006. Her findings advanced the field by establishing a model of hierarchical sensory processing incorporating “hidden inhibition” and set the stage for her next scientific endeavor.
In her postdoc at MIT, Nicole worked with Jim DiCarlo studying visual object perception at ascending levels of visual processing. Specifically, she aimed to understand the neural basis of object invariance, where we can perceive an object's identity as consistent and tolerant to changes in position, size, and background context. For example, when you’re looking for your phone, you can identify it even when it is on its side, across the room, or jammed between couch cushions. She presented monkeys with images of objects, including images of 10 objects captured at different angles, sizes, and backgrounds. The monkeys were trained to identify and respond to specific objects with an eye movement, and while they performed the task, Nicole recorded neural spiking from V4 and the inferior temporal cortex (IT), a high-level processing region near the hippocampus associated with object recognition. To effectively identify an object, neurons must be selective—their firing rate should increase for that object and others related to it. They must also respond with invariance—increased firing rates independent of an object's position, size, or background context. Nicole tested whether she could decode a given object's identity from the neuronal spiking pattern using a hierarchical modeling approach. Compared to neurons in V4, neurons in IT were more selective and more invariant to visual objects. Nicole describes the outputs of the hierarchy modeling approach with an analogy: imagine each object identity is a piece of paper. In V4, the sheets are more crumpled together and difficult to distinguish, but in IT, they have been smoothed out and are easier to separate. Her work at MIT set the stage for the emergence of powerful biologically inspired modeling approaches like artificial neural networks.
Since starting her lab at University of Pennsylvania, Nicole has studied visual object memory. Previous cognitive behavioral research has demonstrated that humans have the capacity to recognize tens of thousands of unique visual images, even after a single exposure. This can be described as an image’s familiarity—a photograph of your childhood home is more familiar than one of a random house because you’ve seen it before. We also find some images inherently more memorable than others—the Mona Lisa is more memorable than the watercolor print in a hotel room, even the first time you see it. To understand the algorithms the brain might use to remember familiar images and respond to memorable ones, Nicole’s team recorded neural spiking from area IT in monkeys as they performed a visual image recognition task. They discovered that neurons in IT code image memorability as an increase in firing rate. Conversely, familiar images show a decrease in firing rate. These two signals, memorability and familiarity, are mixed in the brain’s visual processing areas. Recent work in Nicole's lab has focused on creating models that capture how seeing an image is transformed into a memory of it, constrained by these results.
While Nicole has enjoyed considerable success in her career, she has grown increasingly concerned by a sentiment expressed by many of her colleagues: with all the progress that has been made in molecular and systems neuroscience in the past few decades, why haven't we been seeing more progress in the treatment of human neurological disease and psychiatric conditions? Nicole was similarly concerned, but she was also curious. In response, she decided to write a book surveying the state of the field and investigating why translational outputs have been falling behind. Her book, Elusive Cures: Why Neuroscience Hasn’t Solved Brain Disorders – And How We Can Change That, was published this year. In addition to providing a transformative perspective for the field, the book has been transformative for Nicole herself. Her experience writing the book catalyzed a career pivot: she aims to spend the next phase of her professional life studying mood.
Supported by aSimons Foundation Pivot Fellowship, Nicole will spend a year with Dr. Yael Niv’s lab at Princeton, where she will learn methods to study mood and mental health in humans. By leveraging her computational and systems background, Nicole will join efforts to advance the neuroscience of human emotion. In a world where 20% of all adults experience a mood disorder in their lifetime, we need neuroscientists like Nicole who are willing to jump into the fray. Maybe someday students will pick up Nicole’s book, just like she picked up Francis Crick’s, and be inspired to pursue a career in neuroscience, joining the chase for elusive cures.
Find out more about Nicole and her lab’s research here.
Listen to Melissa’s full interview with Nicole on May 12, 2025 below!
