15 June 2016: The role of mood in reward learning: function and dysfunction

Eran Eldar
Wellcome Trust Centre for Neuroimaging
Max Planck UCL Centre for Computational Psychiatry and Ageing Research
University College London

Unexpected rewards impact our mood, which may in turn impact our evaluation of subsequent rewards. I will show how this two-way interaction between mood and reward learning may serve an adaptive role, ‘correcting’ learning to account for widespread changes in reward availability in the environment. I will then present theoretical and experimental evidence indicating that this mechanism can also have maladaptive consequences, in particular by engendering mood instability that may contribute to psychiatric mood disorders.

Postdoc position available at the Niv Lab at Princeton University

The lab of Dr. Yael Niv at Princeton University (http://www.princeton.edu/~nivlab) is seeking a talented postdoctoral or more senior research associate to work as part of the newly formed CCNP. Research in the lab focuses on behavioral and imaging experiments and computational modeling of learning and decision making and their interaction with attention and memory processes.

The successful candidate will be exceptionally talented and motivated, with a clinical research background and a keen interest in applying methods from computational cognitive modeling to help understand and treat mental illness. The specific area of research is flexible, including anxiety and mood disorders, addiction, PTSD, OCD, schizophrenia. We are particularly looking for someone with initiative and creative ideas who will help chart a path for the lab in transitioning to research in the emerging field of computational psychiatry.

The Princeton Neuroscience Institute and the Psychology Department at Princeton are highly interdisciplinary and collaborative, and provide excellent support for career development. You will be joining a vibrant and international research group, and will have opportunities to interact with and learn from a large number of world-class researchers in cognitive and computational neuroscience. Initial appointments are for one year with the possibility of reappointment based on satisfactory performance and funding.

Essential Qualifications: PhD in psychology, psychiatry, neuroscience, cognitive science, or other closely related field; a strong track record of research; and experience with research on mental illness and psychiatric populations.

Preferred Qualification: Proficiency with computer programming (Matlab, Python, R or equivalent) and strong analytical and quantitative skills are strongly preferred. Experience with behavioral experiments (decision making/psychophysics) and model-based data analysis, fMRI (event related designs and model-based analysis techniques), and/or computational modeling (machine learning, reinforcement learning, Bayesian models) are an advantage, though not strictly required.

If you are interested please email a CV, research statement, and contact information for at least 2 references to yael@princeton.edu, and upload these materials at https://jobs.princeton.edu (Requisition #1600435).

Princeton University is an equal opportunity/affirmative action employer and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability status, protected veteran status, or any other characteristic protected by law. This position is subject to the University’s background check policy.

8 June 2016: Malfunction and bounded rationality views of psychopathology

Peter Hitchcock
Department of Psychology
Drexel University

I will contrast two views of mental health problems: the malfunction and bounded rationality views. The malfunction view states that mental health problems are due to faulty machinery which produces irrational behavior. The bounded rationality view states that people with mental health difficulties act in a rational, which is to say goal-consistent, manner, but that their goals are sometimes maladaptive due to the boundedness of rationality (where boundedness is due to the limits of knowledge and computational capacity, and to the opportunity cost inherent in action selection). According to the malfunction view, biology is the science of prime relevance to mental health; according to the bounded rationality view, the science of intelligence is most relevant. Computational researchers have a long history of adopting a stance of bounded rationality when characterizing new problems and describing human behavior. What is less well-known is that cognitive-behavioral therapy researchers adopt a strikingly similar stance during case formulation and treatment development, as I will show through examples. The aim of this talk is to brainstorm with the CCNP community about whether this similar approach to solving problems offers opportunities for generating new predictions and for making progress on problems in common.