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Brain Aging - Models, Methods, and Mechanisms (Paperback)
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Brain Aging - Models, Methods, and Mechanisms (Paperback)
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Recognition that aging is not the accumulation of disease, but
rather comprises fundamental biological processes that are amenable
to experimental study, is the basis for the recent growth of
experimental biogerontology. As increasingly sophisticated studies
provide greater understanding of what occurs in the aging brain and
how these changes occur, new possibilities emerge for limiting the
effects of aging on neural function. A single source reference is
necessary to keep abreast of the recent advances and future
directions of gerontology research. Brain Aging: Models, Methods,
and Mechanisms offers a selective overview of the research in this
rapidly expanding field. A valuable resource for new and
established investigators of the aging brain, this volume reviews
critical studies of brain aging in new animal models, as well as
advances in brain imaging techniques that permit investigations in
aging humans with increasingly higher resolution. Detailed
discussions link the information from human and animal studies to
illustrate a comprehensive picture of the mechanism of aging.
Emphasizing normal brain aging rather than pathological
degeneration, the text provides an understanding of fundamental
age-related changes in the nervous system and hypothesis-driven
research into their basis. The book includes critical analyses of
the distinct methodological challenges inherent in investigating
the aging nervous system. Contributions from distinguished leaders
and pioneers in their respective fields address data and
mechanisms, as well as models and methods that are key to the study
of aging. Each chapter is extensively referenced and highlights
experimental concerns that are magnified or unique to the aging
brain. Outlining relevant methods and techniques, this book
provides scientists, researchers, and clinicians with a broad
understanding of the important progress and implications for the
future of this significant field.
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