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Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
Published on: February 14, 2014
White matter and cognitive decline in aging: a focus on processing speed and variability.
Jonna Nilsson1, Alan J Thomas1, John T O'Brien2
1Institute of Ageing and Health, Newcastle University, United Kingdom.
White matter changes are linked to cognitive decline in aging. New imaging methods and measuring processing speed variability can help understand this relationship better.
Area of Science:
- Neuroscience
- Cognitive Aging
- Neuroimaging
Background:
- White matter (WM) changes are associated with age-related cognitive decline.
- Processing speed is a key cognitive function affected by aging.
- Intra-individual variability in processing speed is a sensitive indicator of cognitive and neurological status.
Purpose of the Study:
- To review methodological advances in understanding the role of white matter in age-related processing speed changes.
- To highlight the combined potential of intra-individual variability and neuroimaging for studying the white matter-processing speed relationship.
Main Methods:
- Review of current literature on white matter changes and cognitive aging.
- Focus on advancements in neuroimaging techniques for assessing white matter.
- Emphasis on the measurement of intra-individual variability in processing speed tasks.
Main Results:
- Neuroimaging techniques for assessing white matter have become more sensitive.
- Intra-individual variability in processing speed is a sensitive proxy for cognitive and neurological decline.
- The combination of these methods offers a promising approach to study the white matter-processing speed link.
Conclusions:
- Methodological advances, particularly in neuroimaging and variability assessment, enhance our ability to study white matter's role in cognitive aging.
- The integrated use of intra-individual variability and sensitive neuroimaging techniques can specify the white matter-processing speed relationship.
- This approach has implications for both normative aging studies and clinical populations.
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