The brain scientist asking how we learn to learn
How do children, adolescents, and adults learn from the outcomes of their actions?
Interviewee:
Interview by:
Kate Nussenbaum studies how we change our learning strategies across different environments. Annie Brookman-Byrne finds out more.
Annie Brookman-Byrne: Tell me about your research on learning.
Kate Nussenbaum: I study how children, adolescents, and adults learn from the outcomes of their actions and form memories of their experiences, which guide future decisions. I specifically focus on how we adapt our learning strategies to different environments.
For example, in some environments we can learn more effectively if we pay more attention to positive than negative feedback, while in other environments, the reverse is true. If a teacher frequently offers praise for both excellent and mediocre work, then such positive feedback is likely uninformative, and learners should adjust their actions more in response to rare criticism. On the flip side, if a parent reprimands most behavior, then attending to and learning from the parent’s praise becomes more useful.
As another example, when we learn, sometimes we need to focus on the specific details of experiences. For instance, it helps to distinguish between this dog, which is friendly, and that dog, which bites people. Other times, extracting generalities is more important – there are no friendly mosquitos.
How do we shift our learning strategies across contexts? How do we learn how to learn? And how do these “learning-to-learn” processes change over the course of development?
I see children’s development as a learning-to-learn process that unfolds over multiple environments across multiple time frames. I want to understand how and why aspects of our environments influence how we learn, leading to differences in how we think and how we behave.
“I see children’s development as a learning-to-learn process that unfolds over multiple environments across multiple time frames.”
Annie: What are the benefits of this research?
Kate: I hope that in the long term, this work will help us better tailor learning environments to the specific strengths of individuals. I also hope my research will shed light on the ways in which biases in how we learn contribute to the emergence of mental health challenges, so that treatments for disorders like anxiety or depression can be made more effective.
I also think that our lives are enriched by a deeper understanding of who we are as people and how our brains work. This is perhaps idealistic, but I think gaining and sharing knowledge about how people become who they are can foster a greater sense of empathy and connection, and an appreciation for how special biological life is. Learning about the seemingly magical cascade of processes that enable increasingly sophisticated behavior from infancy to early adulthood has been one of the central joys of my life, and I hope that the knowledge my lab generates can instill a little bit of that sense of wonder in others.
Annie: What changes have you seen in developmental science?
Kate: Two big changes have occurred since I entered this field. A decade ago, much of the work on how experience shapes brain development focused on how stressful or adverse early-life environments led to deficits in learning and thinking. Increasingly, researchers are recognizing that these “deficits” are, at least in part, rational responses to the environments people have experienced. This shift away from seeing certain developmental pathways as purely good or bad is useful. It leads to more nuanced conversations and research into how specific experiences shape learning.
“This shift away from seeing certain developmental pathways as purely good or bad is useful.”
Second, more researchers — myself included — have embraced computational approaches. This means translating our sometimes fuzzy theories about learning into specific mathematical models. With these models, we can make more precise predictions about how various cognitive processes develop and interact. Of course, attaching numbers to our theories doesn’t, in and of itself, advance our understanding of development, but this approach can be very useful for testing predictions about how hidden cognitive processes give rise to different patterns of behavior.
Annie: What is the biggest challenge in this field?
Kate: A few years ago, a number of influential researchers argued that “reward is enough” — that intelligent behaviors, like perception and language, emerge as people (or animals) seek out as much reward as possible. This idea informs a lot of my work, but it also raises the question of what we mean by “reward.” What rewards do children, adolescents, and adults learn from in the real world?
In my work, we often circumvent this challenging question by defining a very clear reward within a laboratory task. For example, we tell participants to win as many coins as possible by selecting between different slot machines. Of course, the real world is more complex than these games. When researchers try to understand developmental changes in learning, we focus on how people use rewards to update their beliefs. But the nature of the rewards, and how they are distributed across different environments, may also contribute to differences in behavior. An infant learning from a parent’s smile may share similarities with, but also differ from, a teenager learning from a “like” on an Instagram post. A challenge for the field will be to understand the distributions and characteristics of real-world rewards that people experience at different ages.
Annie: What are your hopes for the future?
Kate: It’s an exciting time to study the development of reward-guided learning because it’s a relatively young subfield. I’ve been inspired by research on both language and visual development. Language researchers have done an amazing job characterizing the naturalistic language input that infants and children hear in their daily lives. And vision researchers have developed beautiful models of how experiences lead to specialization of visual perception. I hope that in the not-too-distant future, we will follow in these fields’ footsteps to better characterize the landscape of rewards that children experience in their daily lives, and build better models of how those rewards, in turn, sculpt reward-learning systems in the brain. In the long term, of course, I hope that we will harness this knowledge to develop behavioral and pharmacological interventions capable of eradicating psychiatric disorders like anxiety and depression.
While it’s an exciting time for the field, it’s a disheartening time to be a researcher, at least in the United States. I hope that federal funding for basic research does not continue to be slashed, and I also hope that universities are able to reclaim their status as pillars of social good and engines of positive change in society. The continued attacks on research and higher education are scary, not just because the continual generation of new knowledge is essential to improving people’s lives, but also because I love what I do. I want to keep doing it, and I want future generations of students to have the same opportunities that I’ve been lucky enough to experience.
Footnotes
Kate Nussenbaum is an Assistant Professor of Psychological & Brain Sciences at Boston University. She directs the Computation, Learning, & Development Lab, where her team combines computational modeling, neuroimaging, and behavioral experiments to understand developmental changes in value-guided learning, memory, and exploration from childhood to early adulthood. Kate received her ScB from Brown University, an MSc from the University of Oxford, and her PhD from New York University. She then conducted postdoctoral work as a CV Starr Fellow at the Princeton Neuroscience Institute prior to starting her lab at Boston University in 2025. Kate is a 2026-2028 Jacobs CIFAR Research Fellow.
Read more about Kate’s work on her lab website and Google Scholar, and follow on Bluesky.
This interview was edited for clarity.
