The Rutgers-Princeton Center for Computational Cognitive Neuropsychiatry (CCNP): In spite of advances in genetics and basic neuroscience, our understanding of the brain mechanisms involved in psychiatric disorders remains in its infancy, seriously limiting our ability to develop desperately needed new treatments for mental illness. Therefore, developing a better understanding of how the work that the brain does becomes disrupted, and how this leads to psychiatric symptoms, is now a major emphasis at the National Institute of Mental Health. It has been argued by leaders in the field that, at present, we do not fully understand the neurobiological bases for even a single symptom of a single psychiatric disorder. To address this problem, researchers in the cognitive and brain sciences have forged several productive partnerships that have resulted in the field of cognitive neuropsychiatry (CNP). CNP attempts to clarify the nature and patterns of brain activity that form the basis of specific symptoms, such changes in mood, arousal, reality testing, threat perception, and other dimensions whose extremes represent mental illness. However, progress in CNP has been slower than anticipated, largely due to the high cost of CNP research and the long length of time it takes to complete research studies. Therefore, new methods are needed to accelerate progress. While animal modeling can test new hypotheses and treatments more quickly than is the case with human patients, this line of research is limited in scope because many aspects of psychiatric disorders are uniquely human. This limitation is now being addressed with a new field called Computational Cognitive Neuropsychiatry. Computational cognitive neuropsychiatry is highly interdisciplinary and involves the use of mathematics and computer simulations to rapidly explore the effects of changes in individual biological variables, and their combinations, on the functioning of neural systems and human behavior. By being able to test the effects of changes in many variables quickly, the most likely causes of psychiatric symptoms, and the most likely treatment approaches, can be identified in far less time than would be the case with the usual trial-and-error approach to animal modeling and human research. This means that studies in human patients are more likely to be testing the most relevant disease mechanisms and the treatments that are most likely to provide symptom relief. Connecting psychiatric disorders to the function of the biological organ that supports them, the brain, has been a great challenge. This in part reflects the challenge of neuroscience generally: the great complexity of the brain and the difficulty bridging neural machinery to complex human behaviors of the sort affected by mental illness. However, recent advances in cognitive and computational neuroscience provide a new, often quantitative and precise, understanding of how multiple aspects of brain function support complex processes such as perception, memory, decision-making and executive control. Because these mechanisms contribute heavily to evaluation, anxiety, mood, control and compulsion – precisely the sorts of functions affected by mental illnesses such as schizophrenia, post-traumatic stress disorder, depression and drug abuse – they provide a promising new foundation for a neuroscientific understanding of these illnesses. Indeed, alterations in such functions have been identified as ‘endophenotypes’ that are common to many disorders. Computational psychiatry is well-suited for the identification and characterization of endophenotyopes, and promises to provide a new level of biological understanding of these disease-related dysfunctions.
The Rutgers-Princeton Center for Cognitive Computational Neuropsychiatry (CCNP) has been formed to pursue this exciting opportunity. The goal is to leverage the expertise in Princeton’s department of Psychology and Neuroscience Institute, and in Rutgers’ departments of Psychology, Psychiatry and Computer Science, Rutgers University Behavioral Health Care, Robert Wood Johnson Hospital, and the Rutgers Brain Health Institute, in a major collaborative initiative that has the potential to be much greater than the sum of its individual parts.