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Cognitive Neuroscience of AgingLinking cognitive and cerebral aging$
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Roberto Cabeza, Lars Nyberg, and Denise Park

Print publication date: 2004

Print ISBN-13: 9780195156744

Published to Oxford Scholarship Online: May 2009

DOI: 10.1093/acprof:oso/9780195156744.001.0001

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Neurocomputational Perspectives Linking Neuromodulation, Processing Noise, Representational Distinctiveness, and Cognitive Aging

Neurocomputational Perspectives Linking Neuromodulation, Processing Noise, Representational Distinctiveness, and Cognitive Aging

Chapter:
(p.354) 15 Neurocomputational Perspectives Linking Neuromodulation, Processing Noise, Representational Distinctiveness, and Cognitive Aging
Source:
Cognitive Neuroscience of Aging
Author(s):

Shu-Chen Li

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780195156744.003.0015

This chapter begins with a brief overview of how to conceptualize “representation”in the context of cognitive neuroscience of aging or life span development. It then reviews recent computational approaches to neuromodulation and their applications in cognitive aging research. It highlights a cross-level integrative theoretical link: deficient neuromodulation leads to noisy neural information processing, which in turn might result in less-distinctive cortical representation and various subsequent behavioral manifestations of commonly observed cognitive aging deficits. The brain is an open system and life span cognitive development is a dynamic, cumulative process that shapes the neurocognitive representations of ongoing interactions with the environment and sociocultural contexts through experiences. Therefore, not only feed-upward effects from neural mechanisms to cognition and behavior, but also downward contextual and experiential influences on neurocognitive processing should be investigated. The final section of the chapter presents a set of simulations exploring the utility of neurocomputational models for investigating the trade-offs between aging-related deficiency in neuromodulation and contextual tuning of cortical representational distinctiveness.

Keywords:   neurocognitive, representation, aging, cognition, computational approaches

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