Schizophrenia is a complex disorder with a wide array of symptoms. People with schizophrenia are challenged by psychosis: they have unusual beliefs and perceptual experiences that are often highly distressing. Many also have difficulties with motivation and social engagement, often referred to as negative symptoms. In addition, people with schizophrenia also have cognitive impairments that limit their ability to work, pursue educational goals, and function independently in the community. We conduct research in all three of these areas, trying to understand the basic cognitive and neural mechanisms that are implicated in these different aspects of the illness. The long-term goal of this work is to develop a mechanistic understanding of the origins of these symptoms in order to guide novel treatment development strategies.



Many people experience highly unusual perceptual and sometimes disturbing experiences. Our work is premised on the idea that it is possible to understand these experiences as resulting from alterations in the processes involved in how we all come to form beliefs and perception of the world around us.

(i) Predictive Coding as a framework for understanding psychosis (In collaboration with Dr. Phillip Corlett, Yale University): Adopting the RDoC approach, we propose that symptoms of psychosis may be the result of abnormalities in the basic neural and cognitive processes that underlie perception, the formation of beliefs, and the generation of action. We are using functional magnetic resonance imaging (fMRI) during tasks of perception, action and electroencephalography. We bring together behavioral and brain data with formal computational modeling that will allow us to estimate, from each individual subject's data, the strength of their priors and prediction errors across a hierarchy of representational richness from simple stimuli through more complex percepts, action choices, and beliefs.

(ii) Clinical High Risk (CAPER, Computerized assessment of psychosis risk study) : Early detection and intervention with young people showing signs of being at clinical high risk (CHR) for psychosis is critical for targeting primary and secondary prevention efforts with the goal of altering the trajectory of psychosis. In our 5-site collaborative project, we aim to guide research that will enhance the sensitivity, specificity, and availability of CHR screening. Our collaborators for this study include: Dr. Vijay Mittal, Northwestern University, Dr. Lauren Ellman, Temple University, Dr. Gregory Strauss, University of Georgia, Dr. Phillip Corlett, Yale University, Dr. Scott Woods,Yale University


Many, but not all people with schizophrenia, have difficulties initiating and sustaining goal-directed behavior. These difficulties are central causes of the disability that is characteristic of the illness, but the origins of these difficulties remains poorly understood. Our work is premised on the idea that these symptoms result from alterations in decision-making and learning.

(i) Reward Processing and Decision Making in Individuals with Schizophrenia (In collaboration with Dr. James Waltz, Maryland Psychiatric Research Center and Dr. Michael Frank, Brown University) : This line of work is designed to address the role of dopamine (DA) in the reinforcement learning and decision- making deficits of patients with schizophrenia (SZ) through the integration of computational modeling with a program of behavioral experiments designed to test model based predictions. The goal of the work is to provide an integrative account of how abnormalities in DA function may underlie many of the disabling cognitive and motivational deficits of SZ, and explore the impact of antipsychotic treatments on these functions. Guided by this computational framework, we propose a series of interrelated studies designed to examine the integrity of different dopamine-mediated behavioral processes in SZ and to explicitly test the role of antipsychotic effects on these systems. This set of behavioral studies is complimented by studies using functional magnetic resonance imaging (fMRI) to measure changes in brain activity related to the receiving positive and negative feedback. With these studies we hope to determine the neural correlates of reward processing abnormalities in people with schizophrenia.


Cognitive deficits, across perception, memory, problem-solving, and executive control are central feature of schizophrenia. These deficits arise early in development, and are largely independent of psychotic symptoms. We focus on the study of attention and working memory because these cognitive functions interact with nearly every other aspect of cognitive functioning.

(i) Cognitive Neuroscience of Attention and Working Memory in Schizophrenia  ( In collaboration with Dr. Steve Luck, UC Davis): The goal of this research program is to identify specific, low-level building blocks of cognition that are impaired in people with schizophrenia (PSZ), are linked with neurobiology, and can explain deficits in a higher- level cognitive function. 

(ii) Our lab is also part of the CNTRACS ( Cognitive Neuroscience Test Reliability And Clinical applications for Schizophrenia) consortium, which was formed to optimize tasks that have been developed to test cognitive neuroscience theories so that they can be used to improve measurement of clinical outcomes in schizophrenia. This team includes the following collaborators: Dr. Deanna Barch, Washington University, Dr. Cam Carter, UC Davis, Dr. Steve Silverstein, Rutgers University, Dr. Angus MacDonald, University of Minnesota

Go to the Participate page to get involved in our research!





MRI measures blood flow in the brain while performing computer tasks in the scanner.



EEG is measuring brain activity through electrodes placed on the scalp and face. Our stetups vary between studies and use anywhere from 32-64 electrodes.

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This nonenvasive method uses an eye tracking camera and computer monitor to measure motion and location of eyes on the screen as a computer task is being performed.

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