Research

Elisabeth Brauner 

Website:  Elisabeth Brauner, Dr. rer. nat.　

Benzion Chanowitz

Website: Benzion Chanowitz, Ph.D.　

Hanah Chapman 

Website:　 Hanah Chapman, Ph.D.

Rebecca Chalmers

Website: Rebecca Chalmers, Ph.D.　

Cheryl Carmichael

close relationships, emotion regulation, health, perceived responsiveness, romantic attachment

The Health, Emotions, and Relationships Team (HEaRT) Lab conducts research aimed at discovering why people with stronger social connections live longer, happier, healthier lives. We examine how personal characteristics (e.g., attachment security) and responsive relationship behaviors (e.g., support provision, physical contact) promote relationship quality, health, and well-being. Our research participants include college students, community couples, and online workers. We collect self-report, behavioral, and psychophysiological measures using a combination of experimental and experience sampling approaches to study relationships processes in the laboratory and in the ebb and flow of day to day life..

Website:　http://bcheartlab.com/

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Elizabeth Chua

metamemory, memory, metacognition, neuroimaging, eye tracking, brain stimulation

Our research focuses on memory and metacognition. We are interested in, not just how information is encoded and retrieved, but also our knowledge and awareness of our memory, and how this impacts our behavior. Much of our work focuses on how we monitor our memory and the basis of confidence in memory.  We are also beginning to examine how our confidence guides the strategic choices we make for improving memory performance. We use a variety of behavioral and cognitive neuroscience techniques, including functional and structural MRI, TMS, tDCS, eye tracking, and psychophysiology to understand our memory, our confidence in our memory, and when our confidence and accuracy go together and when they do not.

Website:　http://userhome.brooklyn.cuny.edu/echua/

Matthew Crump

computational modeling, skill-learning, memory, attention, natural-language processing, pattern-recognition and production

How do people learn new skills like playing a musical instrument or typing on a computer keyboard? How does memory work? How do people pay attention to their surroundings? How do people become sensitive to patterns and regularities in their environment? We investigate these kinds of questions with experiments that test theoretical and computational models of human cognition. Students with a strong interest in computer programming and data-analysis are encouraged to contact Dr. Crump.

Website:　https://crumplab.github.io/

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Andrew Delamater

associative learning, reward processing, interval timing, Pavlovian extinction learning, cortico-striato-limbic pathways in associative learning, relational learning processes, prediction error mechanisms, connectionist network models

The Delamater lab explores the psychological and neurobiological mechanisms involved in simple forms of associative learning mostly in rodent models. We use a variety of behavioral and behavioral neuroscience techniques including (a) targeted brain structure lesions, (b) pharmacological inactivation, (c) chemogenetic manipulations using DREADDs, (d) immunohistochemistry labeling (e.g., cFos), and (e) sophisticated behavioral tests. One project investigates the nature of reward processing where we focus on the question of how the brain learns to anticipate “what” reward is likely to occur in the near future as well as precisely “when” it will occur. We ask whether these two aspects of learning engage separate underlying neural systems, and we also ask to what extent “prediction errors” along these different “what” and “when” dimensions might be critical for brain plasticity. Another project explores the nature of the associative network that could give rise to the ability to time future rewards. To explore this we have devised a neural net model that is capable of showing temporally organized behavior as well as various phenomena related to interval timing. A third project examines the nature of extinction learning in Pavlovian conditioning. In particular, we ask what conditions might be especially helpful in promoting response loss after learning has taken place. Here, as well, we attempt to dissect learning into its separate components (sensory, temporal, emotional) and ask whether extinction processes might differentially impact these different forms of learning. Additional projects address other aspects of associative learning including (a) learning about higher order conditional relationships among stimuli, and (b) assessing striatal contributions to goal-directed and habitual control of associatively learned instrumental behaviors.

Website:　http://academic.brooklyn.cuny.edu/psych/delam/

Angello DiBello

Website: Angello DiBello, Ph.D.