Individuals with schizophrenia suffer from marked cognitive impairment, which is highly predictive of social, occupational, and community functioning. As a result, cognitive impairment is a prime target for intervention. Abnormalities in cortical plasticity are hypothesized to underlie cognitive impairment. However, because it was not possible to evaluate human cortical plasticity in vivo until very recently, the extent to which cortical plasticity is impacted in schizophrenia is unclear. Furthermore, it is unknown whether cortical plasticity changes over phase of illness. Animal studies indicate that cortical plasticity declines with age. It is possible that in schizophrenia, normative maturational declines in cortical plasticity interact synergistically with disease pathophysiology over the developmental course of the illness. Thus, cortical plasticity may be less compromised in the early phase of illness. Finally, little is known about the real-world consequences of abnormal cortical plasticity for individuals with schizophrenia. This K23 project is consistent with strategies outlined in the NIMH Strategic Plan, particularly Strategy 1.1., to describe the neural circuits associated with complex behaviors, Strategy 2.1, to characterize the developmental trajectories of brain maturation and dimensions of behavior to understand the roots of mental illnesses across diverse populations, and Strategy 2.2, to identify clinically useful biomarkers that predict change across the trajectory of illness. Specifically, the proposal involves a plan for the applicant to work closely with a diverse team of distinguished researchers with expertise in neuroscience, clinical and developmental psychology, and biostatistics to investigate biomarkers of cortical plasticity in schizophrenia within a neurodevelopmental framework. Using newly-developed EEG paradigms that permit non-invasive assessment of plasticity in the human sensory cortex, we will study individuals with recent-onset schizophrenia, chronic schizophrenia, and matched non-psychiatric comparison participants to investigate: 1) whether cortical plasticity is abnormal in schizophrenia, 2) whether cortical plasticity changes over phase of illness, and 3) potential correlates of cortical plasticity in schizophrenia, including performance-based tasks of perceptual processing and higher-order cognition, and daily functioning. The findings will inform the field about the developmental course of the neural underpinnings of impaired cognition in schizophrenia, and will inform plasticity-based interventions to improve cognition in this population. Mentored training in advanced EEG analytic methods and developmental psychopathology will permit the applicant to develop an independent, interdisciplinary program of clinical research that combines electrophysiology and behavioral methods to investigate cognition and functioning in severe psychopathology across the lifespan.
Beyond the obvious personal costs, the cost of schizophrenia to society is tremendous; the economic burden of schizophrenia exceeds $62 billion in the US, and approximately 50% of the total can be attributed to costs associated with impaired functioning. Using advanced EEG methods within a neurodevelopmental framework, this project will investigate the neural underpinnings of impaired cognition, a major predictor functional disability in schizophrenia, to determine whether neural processes become increasingly abnormal over the course of illness, and to identify external correlates of the neural processes. This research is expected to inform developmental and treatment research regarding the trajectory of impaired cognition over phase of illness in schizophrenia, and indicate optimal timing for cognitive training interventions.
Martin, Elizabeth A; McCleery, Amanda; Moore, Melody M et al. (2018) ERP indices of performance monitoring and feedback processing in psychosis: A meta-analysis. Int J Psychophysiol 132:365-378 |
McCleery, Amanda; Wynn, Jonathan K; Mathalon, Daniel H et al. (2018) Hallucinations, neuroplasticity, and prediction errors in schizophrenia. Scand J Psychol 59:41-48 |