Dr. Eva Pool
Lecturer & Principal Investigator, University of Geneva
Postdoctoral Fellow, California Institute of Technology
PhD, University of Geneva
As a trainee in clinical psychology, Eva Pool spent long hours in hospitals, working with patients whose lives were shaped by maladaptive decisions—addiction, binge eating, and impulsive behaviors. Eva increasingly felt that diagnostic categories described what patients did, but not why they kept doing it. Why did people persist in pursuing outcomes that no longer brought pleasure? Why were some people more prone than others to getting stuck in patterns they themselves wished to escape? This dissatisfaction turned out to be a generative force and became the foundation for her scientific career. Today, Dr. Eva Pool leads the Affect, Learning & Decisions lab at the University of Geneva, combining fundamental mechanistic neuroscience with her longstanding commitment to mental health. Her group uses rich behavioral quantification, human neuroimaging, and computational modeling to understand how differences in value learning and affective decision-making can predict vulnerability or resilience to maladaptive behaviors.
Eva grew up in a small town in the Italian-speaking region of Switzerland, with no plans of ever becoming a scientist. Initially drawn to psychology through an interest in mental health, the desire for a deeper, more formal understanding of how affect—like pleasure or fear—shapes decisions led her to give up a career in psychotherapy and turn to cognitive neuroscience instead. The transition did not come without challenges. Moving to the French-speaking part of Switzerland for a masters degree, Eva had to work twice as hard to conduct her studies in a new language. As she started to consider a PhD more seriously, she worried that her limited fluency in English would make research inaccessible. With the encouragement of a mentor highlighting that many researchers before her had overcome the same barrier, Eva decided to improve her language skills through a “full immersion” in the vibrant, seaside town of Brighton, UK for two months. Upon returning to Switzerland, she joined a PhD program in affective sciences at the University of Geneva, a highly interdisciplinary program studying how mood, emotions, and motivations shape cognition and behavior. At the time, fear conditioning was the dominant paradigm in the field, celebrated for its successful translation from rodent circuits to human neuroimaging and clinical anxiety. Inspired by this, Eva began to ask whether reward learning could be studied with similar mechanistic rigor: how the brain assigns and updates positive value, and how these processes go awry in addiction.
Eva’s doctoral work with Dr. David Sander focused on developing rich tasks to quantify various aspects of reward-based behaviors. One theme gradually crystallized and remains central to her work: value-guided decision-making is not a unitary process, but is instead composed of multiple, partially separable components. For example, motivation (“wanting”) and pleasure (“liking”) can diverge. Late-night stress before an exam or seeing the logo of your favorite fast-food chain may trigger a craving for comfort snacks but may not elicit the same pleasure during eating as when hungry. To identify this dissociation neurally, Eva used high-resolution fMRI as human participants learned to associate abstract visual cues with different odors. These cues were later used as motivational incentive in a follow-up task, thus isolating the motivation to obtain the odor from the pleasantness of the sensory experience of the odor itself. At first, unable to find any meaningful signal in the fMRI data, she worried she had done something wrong. It was years later, with new analysis pipelines, that Eva showed that motivational drive and pleasure are represented in distinct subregions of the ventral striatum in humans. These findings mirror evidence in rodents and may explain why people can work hard to obtain rewards they no longer find pleasurable—a hallmark of addictive behavior. Along the way, Eva discovered a deep affinity for computational approaches like reinforcement learning models as a way to formalize cognitive processes using algorithms: how the brain learns and updates value, and how those learned values drive decisions over time.
Now completely enthralled by research, Eva moved across the Atlantic for a postdoctoral position in the lab of one of her scientific heroes: Dr. John O’Doherty at Caltech, in Los Angeles. The two years in LA were inspiring—she found a highly collaborative research environment that was technically rigorous, supportive, and generous with shared code and ideas. In fact, it was there that she developed the technical depth to revisit the neuroimaging data from her PhD and discover the relevant neural signals in what she had earlier feared were “failed experiments”. During her postdoc, Eva focused on learning mechanisms for Pavlovian conditioning in humans, using eye-tracking to dissociate different components of conditioned behavior, with pupil dilation as an index of arousal and gaze patterns as an index of anticipatory orienting. She showed that these two conditioned responses to the same cue could differ in their flexibility: arousal responses diminished when the outcome was devalued, but gaze responses remained stable. She corroborated this behavioral study with further neural evidence that even “simple” Pavlovian learning comprises multiple parallel processes, only some of which flexibly track current value. Eva’s work suggests that perseveration is not inherently pathological; rather, problems arise when devaluation-insensitive learning systems dominate behavior, as may occur in addiction.
Although Eva was happy in the team environment at Caltech, she knew that she couldn’t stay a postdoc forever. She found the opportunity to move back to Geneva as a senior researcher under a non-tenure track principal investigator scheme. As a six year position, it offered more stability than a conventional annually-renewed postdoc contract, enabling her to build a team and finally launch longitudinal studies as well as translational projects. This was later followed by a transition to an Assistant Professor position, wherein she could carry much of the team and momentum forward.
Consistent across the Pool lab’s set of projects is a multidimensional approach to behavior and an emphasis on individual differences. Recent work from the lab used survey analysis of hundreds of patients to relate different components of habits—automaticity versus routine—to distinct forms of psychopathology. Automaticity refers to actions that are triggered quickly and often without awareness, like reaching for your phone the moment a notification appears, or opening a food delivery app without consciously deciding to do so. It is associated with problematic reward-seeking such as in addiction or excessive Internet use, and may be exacerbated in modern environments saturated with such cues. Routine, on the other hand, reflects a preference for structure and repetition, and is more strongly associated with compulsivity. Eva argues that taking the multidimensionality of habit seriously can reveal distinct risk profiles underlying mental health problems. Connecting this to computational and neural mechanisms will answer a more precise question: which components of affective decision-making dominate behavior, and under what conditions? This shift from “labels” to “mechanisms” addresses the very gap that frustrated Eva in the clinic and gives her research both explanatory power and translational promise.
Looking back, Eva would tell her younger self—or students standing at similar crossroads—to trust that it is possible to take risks, like making a career pivot, and to not be daunted by uncertainty. It is a perspective that echoes her scientific work: the importance of flexibility over the pull of routine. She argues that early-career researchers benefit from resisting rigid scripts about what they “should” already know, and should instead find questions that genuinely motivate them. Passion, she believes, is often a better predictor of persistence and success, and supportive mentors can provide the scaffolding that makes adaptation possible when confidence wavers.
Eva’s work reframes addiction not as a moral or cognitive failure, but as the outcome of learning systems doing what they evolved to do—sometimes under conditions that push them out of balance. Eva will continue building this framework that connects brain, behavior, and mental health with a unique precision, turning questions that once puzzled her in the clinic into insights that can guide more effective patient care.
Find out more about Eva and her lab’s research here.
Listen to Margarida’s full interview with Eva on June 30, 2025 below!
