3 experiments examined serial pattern learning in younger and older adults. Unlike the usual repeating pattern, the sequences alternated between events from a repeating pattern and those determined randomly. The results indicated that no one was able to describe the regularity, but with practice every individual in all 3 age groups (including old old) became faster, more accurate, or both, on pattern trials than on random trials. Although this indicates that adults of all ages are able to learn second-order statistical dependencies in a sequence, age-related deficits were obtained in the magnitude of pattern learning. There were also age differences in what was learned, with only younger people revealing sensitivity to higher order statistical dependencies in the sequence. In addition, whereas younger people revealed evidence of their pattern learning in a subsequent conceptually driven production test, young-old and old-old people did not.

Diffusion tensor imaging (DTI) measures diffusion of molecular water, which can be used to calculate indices of white matter integrity. Early DTI studies of aging primarily focused on two global measures of integrity; the average rate (mean diffusivity, MD) and orientation coherence (fractional anisotropy, FA) of diffusion. More recent studies have added measures of water movement parallel (axial diffusivity, AD) and perpendicular (radial diffusivity, RD) to the primary diffusion direction, which are thought to reflect the neural bases of age differences in diffusion (i.e., axonal shrinkage and demyelination, respectively). In the present study, patterns of age differences in white matter integrity were assessed by comparing younger and healthy older adults on multiple measures of integrity (FA, AD, RD). Results revealed two commonly reported patterns (Radial Increase Only and Radial/Axial Increase), and one relatively novel pattern (Radial Increase/Axial Decrease) that varied by brain region and may reflect differential aging of microstructural (e.g., degree of myelination) and macrostructural (e.g., coherence of fiber orientation) properties of white matter. In addition, larger age differences in FA in frontal white matter were consistent with the anterior-posterior gradient of age differences in white matter integrity. Together, these findings complement other recent studies in providing information about patterns of diffusivity that are characteristic of healthy aging. KeywordsAging; axial diffusivity; DTI; fractional anisotropy; radial diffusivity Brain aging research has been dominated by examinations of age-related differences in the structure and function of gray matter (Cabeza, et al. 2005), with the other half of the brainwhite matter-having been largely ignored. The lack of attention to white matter aging in the past likely resulted from limitations in imaging technology, because the relatively recent Address correspondence to: Ilana J. Bennett, Georgetown University, Department of Psychology, 301 N White Gravenor Building, Washington, DC 20057, PH: 202-687-4099, FX: 202-687-6050, ijb5@georgetown.edu. Preliminary findings from this project were presented at the Society for Neuroscience Conferences in San Diego, CA in November, 2007 and Washington, DC in November, 2008; NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author Manuscript advent of diffusion tensor imaging (DTI) has led to widespread in interest in age-related changes in white matter.DTI is a magnetic resonance imaging (MRI) technique that measures the diffusion of molecular water (Basser, et al. 1994;. Water diffuses 3-7 times more rapidly along the length of axons aligned in white matter tracts compared to movement perpendicular to the axons (Le Bihan 2003; because the latter is restricted by axonal cell membranes, myelin sheaths, and neurofilaments (Beaulieu 2002). Various properties of water diffusion can be calculated from DTI-based eigenvalue measures (λ1, λ2, and λ3; which indicate the rate of diffusion along the...

The influence of sleep on motor skill consolidation has been a research topic of increasing interest. In this study, we distinguished general skill learning from sequence-specific learning in a probabilistic implicit sequence learning task (alternating serial reaction time) in young and old adults before and after a 12-h offline interval which did or did not contain sleep (p.m.-a.m. and a.m.-p.m. groups, respectively). The results showed that general skill learning, as assessed via overall reaction time, improved offline in both the young and older groups, with the young group improving more than the old. However, the improvement was not sleep-dependent, in that there was no difference between the a.m.-p.m. and p.m.-a.m. groups. We did not find sequence-specific offline improvement in either age group for the a.m.-either p.m. or p.m.-a.m. groups, suggesting that consolidation of this kind of implicit motor sequence learning may not be influenced by sleep.

The influence of structure and age on sequence learning was investigated by testing 24 young and 24 older participants for 10 sessions in an alternating serial response time task in which pattern trials alternated with random trials. Individuals encountered lag-2 or lag-3 structure, and learning was measured by the difference (in response time and accuracy) between pattern and random trials. Both ages learned lag-2 structure, but the young learned more than the older participants. Only the young people learned lag-3 structure, and they did so more slowly and to a lesser degree than they learned lag-2 structure. These age deficits in higher order sequence learning after extended practice are consistent with simultaneity theory and with theories positing that age-related deficits in neuromodulation lead to less distinctive representations.

It has become widely accepted that sleep-dependent consolidation occurs for motor sequence learning based on studies using fingertapping tasks. Studies using another motor sequence learning task [the serial response time task (SRTT)] have portrayed a more nuanced picture of off-line consolidation, involving both sleep-dependent and daytime consolidation, as well as modifying influences of explicit awareness. The present study used a variant of the SRTT featuring probabilistic sequences to investigate off-line consolidation. Probabilistic sequences confer two advantages: first, spontaneous explicit awareness does not occur, and second, sequence learning measures are continuous, making it easier to separate general skill from sequence-specific learning. We found that sleep did not enhance general skill or sequence-specific learning. In contrast, daytime enhancement occurred for general skill but not for sequence-specific learning. Overall, these results suggest that motor learning does not always undergo consolidation with sleep.

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Serial pattern learning was investigated in a variation of the task introduced by Nissen and Bullemer (1987). We presented an asterisk at 1 of 4 spatial locations on each trial, and Ss either responded with a keypress or observed the event. The first 4 blocks contained 10 repetitions of a 10- or 16-element pattern, and the 5th block contained a random sequence. The difference in response time on the 5th random block and the previous patterned block served as an indirect measure of pattern learning. A direct measure was obtained in a final test block in which Ss predicted the next asterisk position. Equivalent learning occurred for responding and observing with indirect measures, but observation was superior with direct measures. These findings indicate that knowledge of serial order can develop through simple perceptual experience, and this is more available to deliberate recall than is knowledge acquired while responding.

Adult age differences in learning and retention of a nonverbal sequence were examined using the serial reaction-time task of Nissen and Bullemer (1987), with 20 younger and 20 older Ss. An asterisk appeared in one of 4 spatial locations, and the Ss responded with a corresponding key press. The first 4 blocks each contained 10 repetitions of a 10- or 16-element spatial sequence, and the 5th block contained a random sequence. The difference between response time on Blocks 5 and 4 served as an indirect measure of pattern learning. The direct measure was accuracy in a final generation block in which the Ss predicted which location would appear next. Results were similar to those with verbal materials; the indirect measure revealed age similarity for patterns of both lengths, but the direct measure yielded age differences favoring the young. For both ages and types of measures, the long patterns led to poorer learning than did the short patterns.