Pharmacological Neuroimaging & Computational Modeling
This line of research is funded by the The NIH Director’s Early Independence Award (DP5)
Psychiatry has made substantial progress towards understanding disease through basic neuroscience. Recently, cognitive neuroscience has informed our understanding of mental illness by linking neural findings with behavioral deficits observed in patients. However, there remains a vast explanatory gap between these disciplines. The challenge facing the field of clinical neuroscience is to close this gap between evolving findings at the level of neural systems and discoveries at the basic cellular-level. The overarching objective of this research arm is to bridge levels of explanation to mechanistically understand human psychiatric symptoms by combining computational, pharmacological and clinical neuroimaging. Such an understanding is vital for progress towards rational treatment development for neuropsychiatric illness, in particular schizophrenia.
While schizophrenia is frequently associated with disturbances in belief and perception, cognitive deficits are a core feature of this illness. Cognitive deficits emerge before other cardinal symptoms, persist throughout illness course, and are not alleviated by available therapies. Therefore, understanding and treating cognitive deficits in schizophrenia represents a fundamental step towards improving patients’ lives. However, the cellular mechanisms underlying cognitive deficits remain elusive. One leading hypothesis proposes possible disruptions in the balance of excitation and inhibition in the cortical micro-circuitry resulting from hypo-function of the N-methyl-D-aspartate (NMDA) glutamate receptor. There is increasing evidence that N-Methyl-D-aspartic acid (NMDA) abnormalities may play a critical role in the pathophyshiology of schizophrenia and cognitive deficits found in this illness. Furthermore, a growing body of work has shown the promise of using neuropharmacology, in combination with fMRI, to better understand the pathophyshiology of psychosis as well as specific symptoms. Our group collaborates closely with Dr. John Krystal, employing NMDA blockade in healthy volunteers as a model of psychosis with the specific aim of understanding circuitry confering delusion content as well as emotional dysfunction. To further elucidate synaptic mechanisms in humans we are combining these approaches with state-of-the-art biophysically-realistic computational models of cognitive function developed by our collaborators Dr. Xiao-Jing Wang and John D. Murray.
This line of research is funded by:
- Read the NIH Press Release
- Read the Yale University Press Release
- Read a relevant article on Anticevic Lab research