the CCN Lab

Prof. Anne GE Collins

Photo of Anne Collins

Contact: annecollins@berkeley.edu

I am an Assistant Professor in the department of Psychology and a member of the The Helen Wills Neuroscience Institute at UC Berkeley.

Previously, I was a post-doctoral research associate at Brown University, in the Laboratory of Neural Computation and Cognition (LNCC), with Prof. Michael Frank. Here is my old web page at Brown. I studied math and science at Ecole Polytechnique (Palaiseau, France) as an undergrad, then got my PhD in Cognitive Science from UPMC (Paris, France), with Prof. Etienne Koechlin, at the laboratory for cognitive neuroscience (ENS, INSERM). You can find a full cv here.

Postdoctoral Researchers

Sam McDougle

Photo of Sam McDougle

After receiving a BA in Neuroscience & Behavior at Vassar College (class of '09), ​I spent two years as a research assistant with Prof. Javier Medina at the University of Pennsylvania​​. At Penn I studied how computations in the mouse cerebellum ​give rise to well-timed, coordinated movements. After a short stint as a musician and science and tech blogger, I began a PhD in Psychology & Neuroscience at Princeton University in 2013​, work​ing​ with Prof​s​. Jordan Taylor​ (primary adviser)​ and Yael Niv​ (secondary adviser), and collaborat​ing​ with Prof. Rich​ard​ Ivry (UC Berkeley). My main research focus concerns modeling human motor and reinforcement learning, and mapping different learning systems to their respective neural substrates​ using a combination of theoretical, behavioral, and neurophysiological methods​. ​I joined the Computational Cognitive Neuroscience Lab​ in the summer of 2018​.​ Here's a long-winded question that bugs me: How do different learning systems in the human brain, each with different evolutionary histories, learning algorithms,​​ and neural ​correlates, work together to give rise to the astounding repertoire of skills every human on earth acquires and maintains over their lifetime?

Photo of Beth Baribault

Beth Baribault

Contact: baribault@berkeley.edu

After earning my BA in Psychology at SUNY Purchase College, I obtained my MA in Psychology and PhD in Cognitive Science at UC Irvine. My background is in computational cognitive modeling, with a special emphasis on hierarchical Bayesian modeling. The overarching goal of my research has been to investigate how combining different modeling approaches enables us to ask (and answer!) qualitatively new questions about the nature of human behavior. While working with Dr. Joachim Vandekerckhove at UC Irvine, I used this approach to study different aspects of higher-order cognition, such as how attention ability underpins decision-making behavior. I have also worked on new design techniques that increase the replicability and robustness of psychological research.

At the Computational Cognitive Neuroscience Lab, I would like to test how merging different modeling approaches might deepen our understanding of reinforcement learning. Specifically, I’d like to know: How do higher-order cognitive abilities, such as working memory and attention, and cognitive processes, such category learning and decision-making, intersect and interact with reinforcement learning? In what environments do these interactions become more or less salient? And finally, how do individual differences shape the collective dynamics of these processes to allow for the diverse range of behaviors we observe across people?

Graduate Students

Photo of Maria Eckstein

Maria Eckstein

Contact: maria.eckstein@berkeley.edu

I got my undergraduate degrees in psychology and philosophy from LMU University in Munich, Germany, then started a PhD in neuroscience at GSN in Munich, before transferring into the psychology PhD program at UC Berkeley, where I am working with Silvia Bunge and Anne Collins. I am interested in the ways we think and learn and use computational models and neurophysiological measures to answer some open questions in these fields, such as: How do we (learn to) represent the world around us? How do we infer regularities and how do we use these regularities when reasoning about the world? More fundamentally, how do we learn to infer certain regularities rather than others? That is, how do we learn to see some events rather than others as part of the same whole? I am also interested in how we learn differently at different ages, and how pubertal hormones affect brain development. I am studying this question with behavioral methods and computational modeling, combined with hormone analysis. Lastly, I am interested in the difference between habit-based and planning-based decisions, and whether practice improves decisions of each kind. I am using model-based and model-free reinforcement learning algorithms to study this question.

Photo of Jimmy Xia

Jimmy Xia

Contact: jimmyxia@math.berkeley.edu

I obtained my undergraduate degrees in Pure Mathematics and Computational Mathematics from the University of Chicago. Currently I am a PhD candidate in Applied Mathematics at UC Berkeley. I am working with Dr. Anne Collins in using trial-by-trial modeling of the reinforcement learning system to answer questions of how humans learn and generalize previous knowledge.



Photo of Jimmy Xia

Milena Rmus

Contact: milena_rmus@berkeley.edu

I obtained my undergraduate degree in Cognitive Neuroscience from Brown University, after which I spent a year working as a research assistant at Princeton University. My research interests include studying cognitive mechanisms of learning, memory, and decision-making using computational models and neuroimaging.












Lab Manager

Photo of Amy Zou

Amy Zou

Contact: amyzou@berkeley.edu

I obtained my undergraduate degrees in Cognitive Science and Linguistics from UC Berkeley. Previously, I worked under Dr. Linda Wilbrecht to investigate the effects of early-life food insecurity in mice, and Dr. Anne Collins to develop reinforcement learning models to analyze their cognitive performance. I was also involved in the collaborative project investigating how learning and memory changes throughout development.

Undergraduate Research Assistants

Josie Christon

Helen Lu

Ham Huang

Aram Moghaddassi

Daniela Muñoz-Lopez

Vy Pham

Flora Dong

Eliana Shaulson

Sabrina Ni

Lab Alumni

Sarah Master (Lab Manager - now Research Assistant at the Max Planck Institute)
Nora Harhen (Undergraduate Honors Student - now Lab Manager at the Bedny Lab at John Hopkins)
Haley Keglovits (Undergraduate Honors Student)
Lucy Whitmore (Undergraduate Honors Student)
Zisu Dong (Undergraduate Research Assistant - now at Facebook AI)
Justin Morillo (Undergraduate Research Assistant)
Lucy Eletel (Undergraduate Research Assistant)
Nithya Rajakumar (Undergraduate Research Assistant)
Katya Brooun (Undergraduate Research Assistant)
Wendy Shi (Undergraduate Research Assistant)
Zoe Temple (Undergraduate Research Assistant)
Rachel Arsenault (Undergraduate Research Assistant)
Avanti Mehrotra (Undergraduate Research Assistant)
Lucy Eletel (Undergraduate Research Assistant)
Nithya Rajakumar (Undergraduate Research Assistant)
Daniel Scott (Intern - now in the Lab for Neural Computation and Cognition (LNCC) at Brown University)
Julie Liu (Research Assistant)
Talia Welte (Undergraduate Research Assistant)
Tanya Smith (Undergraduate Research Assistant)
Ching Fang (Undergraduate Research Assistant)
Gayatri Sabne (Undergraduate Research Assistant)
Benjamin Tang (Undergraduate Research Assistant)