Kavli Workshops

The annual meeting will once again include two workshops, The Kavli Foundation Neuroscience Workshop and The Kavli Foundation Social and Decision Science Workshop.  Please see the various descriptions below and you will be able to indicate which workshop you would like to attend when you register for the meeting.

The Kavli Foundation Social and Decision Science Workshop I

Friday October 6, 2017, 14:15 – 15:45

Johannes Haushofer

Johannes Haushofer

Princeton University and Busara Center for Behavioral Economics

The interests of my lab lie at the intersection of development economics and behavioral economics/psychology. In particular, we ask whether poverty has particular psychological consequences, and whether and how these consequences, in turn, affect economic behavior. To answer these questions, we combine laboratory experiments with randomized controlled trials of development programs such as health insurance and unconditional cash transfers in Kenya and Sierra Leone. In one recent study, we found that unconditional cash transfers sent to poor Kenyan households by the NGO GiveDirectly led to substantial reductions in stress and depression among recipients; conversely, we have shown that negative income shocks induced by periods of low levels of rainfall lead to increased levels of stress. Our laboratory experiments have shown that such shocks, and the resulting stress, can affect economic behavior by making people less patient. Together, these findings suggest that poverty may perpetuate itself partly through a psychological feedback loop.

“Neuroeconomics in the field”

Abstract: While neuroeconomic research in lab settings affords experimental control and facilitates replicability, field settings are attractive to establish external validity and move neuroeconomic research beyond “WEIRD” populations. I will discuss the practicalities of conducting behavioral and pharmacological research in field settings, especially in developing countries.

The Kavli Foundation Social and Decision Science Workshop II

Friday October 6, 2017, 16:05 – 17:35

Emily Falk

Emily Falk

University of Pennsylvania

Emily Falk is an Associate Professor of Communication, Psychology, and Marketing at the University of Pennsylvania. Prof. Falk employs a variety of methods drawn from communication science, neuroscience and psychology. Her work traverses levels of analysis from individual behavior, to diffusion in group and population level media effects. In particular, Prof. Falk is interested in predicting behavior change following exposure to persuasive messages and in understanding what makes successful ideas spread (e.g. through social networks, through cultures). Prof. Falk is also interested in developing methods to predict the efficacy of persuasive communication at the population level. At present, one line of her research focuses on developing more effective health communications, including recent work linking neural responses to health messages to individual and population level behavioral outcomes. Another core focus in the lab examines how ideas spread through social networks, and how social network properties influence and are influenced by psychological and neural responses.  Other areas of interest include political communication, cross-cultural communication, and the spread of culture, social norms and sticky ideas. Prof. Falk’s work has been funded by NCI, NICHD, NIDA/the NIH Director’s New Innovator Award, ARL, DARPA and ONR. Prior to her doctoral work, Prof. Falk was a Fulbright Fellow in health policy, studying health communication in Canada. She received her bachelor’s degree in Neuroscience from Brown University, and her Ph.D. in Psychology from the University of California, Los Angeles (UCLA)

“New Approaches to Studying How Ideas and Behaviors Spread”

Abstract:  In this talk, I will provide an overview of work linking neural responses in small groups of people to individual behavior change and the spread of ideas outside of the lab, as well as population level behaviors that go beyond the individuals whose brains are scanned.  I will also describe recent research linking brain activity to behavior outside of the lab that incorporates social network measurements and suggest new questions at the intersection of brains and social networks.

The Kavli Foundation Neuroscience Workshop I

Sunday August 28, 14:15 – 15:45

Russell Alan Poldrack

Russell Alan Poldrack

Stanford University

Russell A. Poldrack is the Albert Ray Lang Professor in the Department of Psychology at Stanford University, and Director of the Stanford Center for Reproducible Neuroscience. His research uses neuroimaging to understand the brain systems underlying decision making and executive function. His lab is also engaged in the development of neuroinformatics tools to help improve the reproducibility and transparency of neuroscience, including the OpenfMRI.org and Neurovault.org data sharing projects and the Cognitive Atlas ontology.

“Reproducibility in neuroimaging: Challenges and solutions”

Abstract: It has become widely appreciated that common scientific practices can lead to inflated rates of false results, and many features of neuroimaging suggest that it may be particularly liable to these problems. My talk will discuss a number of the potential threats to reproducibility in neuroimaging research, including small sample sizes, analytic flexibility, and multiple comparisons. I will also discuss the particular challenges raised by increasingly powerful analysis methods such as machine learning techniques. For each of these challenges I will propose solutions that together have the potential to improve the reproducibility of neuroimaging results.

The Kavli Foundation Neuroscience Workshop II

Friday October 6, 2017, 16:05 – 17:35

Tor Wager

Tor Wager

University of Colorado at Boulder

Tor Wager is Professor of Psychology, Neuroscience, and Cognitive Science at the University of Colorado, Boulder. He received his Ph.D. from the University of Michigan in Cognitive Psychology in 2003, and served as an Assistant and Associate Professor at Columbia University from 2004-2009. Since 2010, he has directed Boulder’s Cognitive and Affective Neuroscience laboratory. Much of the lab’s work centers on the neurophysiology of pain and emotion and how they are shaped by cognitive and social influences. In particular, Dr. Wager is interested in how thoughts and beliefs influence affective experiences, affective learning, and brain-body communication. In addition to negative emotions and stressors, the lab also focuses on prosocial emotions, including compassion and empathy. In addition to basic research, Dr. Wager’s lab is involved in developing analysis methods for fMRI analysis. He and his group have developed several publically available software toolboxes. He regularly teaches workshops on fMRI analysis and has co-authored a book on the subject, titled Principles of fMRI. Finally, a third focus is on collaborative, translational research incorporating brain systems-level analyses into the study of clinical disorders, including chronic pain, PTSD, Parkinson’s Disease, depression, and schizophrenia. More information about the lab’s activities, publications, and software can be found at http://wagerlab.colorado.edu.

“Reproducible, generalizable brain models of affective processes”

Abstract: Recent years have seen dramatic advancement in the measurement of biology at a systems level. Researchers routinely obtain thousands or millions of simultanous measures of dynamic systems.  In humans, this includes neuroimaging, which can be used to probe the brain bases of affect and emotion in increasingly sophisticated ways. Neuroimaging can provide measures of activity in 300,000 brain locations and 60 billion functional associations every second. However, the complexity of these measures presents new challenges in maintaining scientific transparency and reproducibility. In this talk, I describe several new models of the brain bases of affective processes, including models that predict the intensity of negative affect, autonomic responses, prosocial emotions, and pain. These models reduce complex neuroimaging data to measures that can be readily replicated and generalized across laboratories. They can be tested prospectively on new participants, providing unbiased estimates of effect size that are often dramatically larger than single regions from standard brain maps. By asking which stimuli and psychological states these measures respond to across studies, we can induce the nature of their associated psychological constructs, providing a foundation for understanding how affect and emotion are generated in the brain.