Top-Down Modulation & Neural Networks in Cognitive Aging

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DESCRIPTION (provided by applicant): The broad objective of this proposal is to support the candidate's development of skills necessary to perform functional magnetic resonance imaging (fMRI) and event-related potential recordings (ERP) to investigate alterations in top-down modulation and neural networks in aging, as well as his continued development as an independent physician-scientist. The research training component includes the mentored development of skills in cognitive experimental design, attaining and processing fMRI and ERP data, multivariate statistical analysis, imaging data - behavioral correlations and the introduction of older participants into the fMRI and ERP environment. The goal of this grant is to identify common neural mechanisms whose impairments underlie a range of age-related cognitive deficits. To accomplish this, experiments will focus on top-down modulation, a process that forms a critical foundation for memory and attention. Both fMRI and ERP will be utilized in counterbalanced studies designed to selectively manipulate and monitor different aspects of top-down modulation in younger and older subjects. The superb spatial resolution of fMRI and high temporal resolution of ERP provide complimentary data to explore the nature and mechanism of this process and its potential alteration in aging. The older age group will be subdivided into different performance groups based on independent neuropsychological testing to facilitate meaningful interpretation of aging findings. A recently developed multivariate method will be applied to investigate age-related changes in neural networks subserving top-down modulation. The University of California at Berkeley provides the perfect training environment as it has a multidisciplinary group of researchers working on advanced fMRI and ERP techniques, as well as many researchers with interest and experience in normal aging research. The proposed research and training plan will provide highly specialized training for the candidate and facilitate the development of an independent cognitive neuroscience research program that will compliment his role as a cognitive neurologist. This training will also serve to support the candidate in his long-term goals of becoming a bridge between large-scale neural network and reductionist approaches to cognitive neuroscience.