The Social Neuroscience Laboratory studies mechanisms of social cognition and self-regulation, in the mind and brain, to understand prejudice, stereotyping, and discrimination.
How do we form impressions, attitudes, and prejudices regarding people and groups? How does prejudice affect our social perceptions and behaviors, often implicitly, and how these effects be controlled? Furthermore, how do these effects relate to social goals, emotions, social roles and hierarchies, and economic factors?
Although our program of research is constantly evolving, recent topics include:
- The role of instrumental learning in the formation of attitudes, prejudices, and trait impressions, vis-a-vis other learning mechanisms. We use computational modeling of behavior and neural activity, paired with reinforcement learning paradigms, to investigate these processes.
- The Memory Systems Model of implicit social cognition and attitudes, and its implications for intergroup bias and discrimination
- Motivated perception of faces as a mechanism of self-regulation--that is, how a person's motivation leads them to see people in a way that will justify their (often discriminatory) actions
- Perceptual dehumanization--how group memberships and social motives lead to selective impairments in early face encoding
- Effects of resource scarcity on the encoding of racial minority faces and its effect on economic decisions
- Effects of social anxiety on implicit bias and cognitive control
- Social power effects on control, reward learning, and economic decision making
- Proactive (anticipatory) forms of control and its interplay with reactive (i.e., corrective) control mechanisms
Our research takes an integrative social neuroscience approach.
Our research integrates theory and ideas from social psychology, cognition, cognitive/affective neuroscience, behavioral economics, sociology, and computer science to inform our ideas and experimental designs. We always choose the methods that best suit our theoretical question, and these often include combinations of behavioral paradigms, self-report measures, computational modeling, neuroimaging (fMRI/EEG/ERP), and psychophysiological assessments.
Our NYU space includes laboratories for EEG, psychophysiological measures (e.g., EMG, SCR, EKG), and eye-tracking, and we use a variety of newly-designed shared spaces for behavioral testing, along with fMRI and MEG scanning in the NYU Center for Brain Imaging, located in our building. Similar resources are available at the UvA.
Major themes of our research include:
We examine the role of different memory systems in the formation and expression of implicit bias. Knowing how implicit biases are encoded in the mind and brain can help us predict the way it will influence behavior and inform ways to reduce its impact. Implicit Bias
Self-regulation is the process of overcoming biases, distractions, and temptations in order to act according to our goals.A major focus of our research concerns the mechanisms of prejudice control. That is, how exactly does control operate in the mind and brain? Self-Regulation
Bias in Visual Perception
Can we always believe what we see? Our research is revealing that the visual processing of faces can be influenced by our prejudices, group membership, economic scarcity, feelings of power, and other social factors. Bias in Visual Perception
Computational Social Cognition
Computational social cognition is a new approach to studying the mechanisms of social cognition—that is, for understanding how we form social impressions and attitudes, represent them in the mind, and use them to guide our choices and actions. Instrumental Social Learning