Brain Ageing in the New Millennium

Trollor, Julian N.; Valenzuela, Michael

doi:10.1046/j.1440-1614.2001.00969.x

Cited by 68 publications

(41 citation statements)

References 212 publications

(237 reference statements)

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“…This decrease is relatively diffuse and uniform in cerebral white matter but shows some regional differences in grey matter, with frontal and parietal cortex more affected than temporal and occipital cortex and with the striatum also affected [10][11][12][13]. Brain volume reductions increase from about 0.1-0.2%/year at age 30-50 years to 0.3-0.5%/year over the age of 70 years, in agreement with brain weight studies.…”

Section: Esirisupporting

confidence: 82%

Ageing and the brain

2007

The Journal of Pathology

177

111

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In this review, the evidence for changes in the human brain with ageing at both the macroscopic and microscopic levels is summarized. Loss of neurons is now recognized to be more modest than initial studies suggested and only affects some neuron populations. Accompanying loss of neurons is some reduction in the size of remaining neurons. This reflects a reduced size of dendritic and axonal arborizations. Some of the likely causes of these changes, including free radical damage resulting from a high rate of oxidative metabolism in neurons, glycation and dysregulation of intracellular calcium homeostasis, are discussed. The roles of genes and environmental factors in causing and responding to ageing changes are explored.

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Section: Esirisupporting

confidence: 82%

Ageing and the brain

2007

The Journal of Pathology

177

111

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“…Studies have shown, for example, that older age brings about declines in fluid intelligence (Berg, 2000;Carroll, 1993;Van Gerven et al, 2000), crystallized intelligence (Berg, 2000;Christensen, 2001;Meyer et al, 2001), processing speed (Berg, 2000;Deary, 2000;Troller and Valenzuela, 2001;Wood et al, 2005), working memory (Berg, 2000;Meyer et al, 2001;Troller and Valenzuela, 2001;Wood et al, 2005;Zacks et al, 2000), episodic memory (Burke and Mackay, 1997;Zacks et al, 2000), learning abilities (Albert, 1997;Rabbitt, 1997;Troller and Valenzuela, 2001), and the ability to filter out irrelevant information (Van Gerven et al, 2000;Zacks et al, 2000).…”

Section: Decline In Cognitive Abilitiesmentioning

confidence: 99%

Simple pen interaction performance of young and older adults using handheld computers

Hourcade¹,

Berkel²

2008

Interacting with Computers

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Several experiments have documented how older adults have greater difficulty using input devices than young adults. None of these experiments, however, have provided information on the challenges faced by older adults when using pens to interact with handheld computers. To address this need, we conducted a study comparing the performance of twenty 18-22 year olds, twenty 50-64 year olds, and twenty 65-84 year olds conducting selection and steering tasks. We found that for the most part, older adults were able to complete tasks accurately and efficiently. An exception occurred with the low accuracy rates achieved by 65-84 year old participants when tapping on targets of the same size as the standard radio buttons on the PocketPC. An alternative selection technique we refer to as ''touch'' enabled 65-84 year olds to select targets significantly more accurately. If tapping to select, making standard-sized targets 50% larger provided 65-84 year olds with similar advantages to switching to ''touch'' interactions.

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“…Decreases in brain volume, cerebral metabolism, and blood flow have been found to occur with aging (Leenders et al, 1990; Marchal et al, 1992;D'Esposito et al, 1999;Buckner et al, 2000;Trollor and Valenzuela, 2001). However, it is highly unlikely that such age-related changes would systematically result in group differences that are regionally dissociated (e.g., decreased activation in the caudate and prefrontal cortex along with increased parietal activation in older adults relative to younger adults).…”

Section: Goldmanmentioning

confidence: 99%

Neural Mechanisms Underlying Probabilistic Category Learning in Normal Aging

Fera¹,

Weickert²,

Goldberg³

et al. 2005

J. Neurosci.

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Probabilistic category learning engages neural circuitry that includes the prefrontal cortex and caudate nucleus, two regions that show prominent changes with normal aging. However, the specific contributions of these brain regions are uncertain, and the effects of normal aging have not been examined previously in probabilistic category learning. In the present study, using a blood oxygenation leveldependent functional magnetic resonance imaging block design, 18 healthy young adults (mean age, 25.5 Ϯ 2.6 years) and 15 older adults (mean age, 67.1 Ϯ 5.3 years) were assessed on the probabilistic category learning "weather prediction" test. Whole-brain functional images acquired using a 1.5T scanner (General Electric, Milwaukee, WI) with gradient echo, echo planar imaging (3/1 mm; repetition time, 3000 ms; echo time, 50 ms) were analyzed using second-level random-effects procedures [SPM99 (Statistical Parametric Mapping)]. Young and older adults displayed equivalent probabilistic category learning curves, used similar strategies, and activated analogous neural networks, including the prefrontal and parietal cortices and the caudate nucleus. However, the extent of caudate and prefrontal activation was less and parietal activation was greater in older participants. The percentage correct and reaction time were mainly positively correlated with caudate and prefrontal activation in young individuals but positively correlated with prefrontal and parietal cortices in older individuals. Differential activation within a circumscribed neural network in the context of equivalent learning suggests that some brain regions, such as the parietal cortices, may provide a compensatory mechanism for healthy older adults in the context of deficient prefrontal cortex and caudate nuclei responses.

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Brain Ageing in the New Millennium

Cited by 68 publications

References 212 publications

Ageing and the brain

Ageing and the brain

Simple pen interaction performance of young and older adults using handheld computers

Neural Mechanisms Underlying Probabilistic Category Learning in Normal Aging

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