scholarly journals Age-dependent statistical learning trajectories reveal differences in information weighting

2019 ◽  
Author(s):  
Steffen A. Herff ◽  
Shanshan Zhen ◽  
Rongjun Yu ◽  
Kat Rose Agres
Keyword(s):  
Older Adults ◽  
Learning Strategies ◽  
Statistical Learning ◽  
Computational Models ◽  
Rule Learning ◽  
Learning Trajectories ◽  
Delta Rule ◽  
Learning Rates ◽  
Age Related ◽  
Age Dependent

Statistical learning (SL) is the ability to generate predictions based on probabilistic dependencies in the environment, an ability that is present throughout life. The effect of aging on SL is still unclear. Here, we explore statistical learning in healthy adults (40 younger and 40 older). The novel paradigm tracks learning trajectories and shows age-related differences in overall performance, yet similarities in learning rates. Bayesian models reveal further differences between younger and older adults in dealing with uncertainty in this probabilistic SL task. We test computational models of three different learning strategies: (1) Win-Stay, Lose-Shift, (2) Delta Rule Learning, (3) Information Weights to explore whether they capture age-related differences in performance and learning in the present task. A likely candidate mechanism emerges in the form of age-dependent differences in information weights, in which young adults more readily change their behavior, but also show disproportionally strong reactions towards erroneous predictions. With lower but more balanced information weights, older adults show slower behavioral adaptation but eventually arrive at more stable and accurate representations of the underlying transitional probability matrix.

Aging and Cognitive Skill Learning

2019 ◽  
Author(s):  
Jack Kuhns ◽  
Dayna R. Touron
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Learning Strategies ◽  
Cognitive Processing ◽  
Cognitive Processes ◽  
Cognitive Skill ◽  
Skill Learning ◽  
Functional Perspective ◽  
Age Related ◽  
Cognitive Skill Learning

The study of aging and cognitive skill learning is concerned with age-related changes and differences in how we gather, store, and use information and abilities. As life expectancy continues to rise, resulting in greater numbers and proportions of older individuals in the population, understanding the development and retention of skills across the lifespan is increasingly important. Older adults’ task performance in cognitive skill learning is often equal to that of young adults, albeit not as efficient, where older adults often require more time to complete training. Investigations of age differences in fundamental cognitive processes of attention, memory, or executive functioning generally reveal declines in older adults. These are related to a slowing of cognitive processing. Slowing in cognitive processing results in longer time necessary to complete tasks which can interfere with the fidelity of older adults’ cognitive processes in time-limited scenarios. Despite this, older adults maintain comparable rates of learning with young adults, albeit with some reduced efficiency in more complex tasks. The effectiveness of older adults’ learning is also impacted by a lesser tendency to recognize and adopt efficient learning strategies, as well as less flexibility in strategy use relative to younger adults. In learning tasks that involve a transition from using a complex initial strategy to relying on memory retrieval, older adults show a volitional avoidance of memory that is related to lower memory confidence and an impoverished mental model of the task. Declines in learning are not entirely problematic from a functional perspective, however, as older adults can often rely upon their extensive knowledge to compensate for certain deficiencies, particularly in everyday tasks. Indeed, domains where older adults have maintained expertise are somewhat insulated from other age-related declines.

scholarly journals Age differences in retrieval-related reinstatement reflect age-related dedifferentiation at encoding

2020 ◽  
Author(s):  
Paul F. Hill ◽  
Danielle R. King ◽  
Michael D. Rugg
Keyword(s):  
Older Adults ◽  
Age Differences ◽  
Source Memory ◽  
Neural Differentiation ◽  
Memory Performance ◽  
Independent Manner ◽  
Age Related ◽  
Age Dependent ◽  
With Memory ◽  
Age Independent

AbstractAge-related reductions in neural specificity have been linked to cognitive decline. We examined whether age differences in specificity of retrieval-related cortical reinstatement could be explained by analogous differences at encoding, and whether reinstatement was associated with memory performance in an age-dependent or age-independent manner. Young and older adults underwent fMRI as they encoded words paired with images of faces or scenes. During a subsequent scanned memory test participants judged whether test words were studied or unstudied and, for words judged studied, also made a source memory judgment about the associated image category. Using multi-voxel pattern analyses, we identified a robust age-related decline in scene reinstatement. This decline was fully explained by age differences in neural differentiation at encoding. These results suggest that, regardless of age, the specificity with which events are neurally processed at the time of encoding determines the fidelity of cortical reinstatement at retrieval.

scholarly journals Gaining Insights Into the Estimation of the Circadian Rhythms of Social Activity in Older Adults From Their Telephone Call Activity With Statistical Learning: Observational Study (Preprint)

2020 ◽  
Author(s):  
Timothée Aubourg ◽  
Jacques Demongeot ◽  
Nicolas Vuillerme
Keyword(s):  
Older Adults ◽  
Circadian Rhythms ◽  
Statistical Learning ◽  
Elderly Population ◽  
Social Activity ◽  
The Elderly ◽  
Telephone Call ◽  
Data Set ◽  
Age Related ◽  
The Social

BACKGROUND Understanding the social mechanisms of the circadian rhythms of activity represents a major issue in better managing the mechanisms of age-related diseases occurring over time in the elderly population. The automated analysis of call detail records (CDRs) provided by modern phone technologies can help meet such an objective. At this stage, however, whether and how the circadian rhythms of telephone call activity can be automatically and properly modeled in the elderly population remains to be established. OBJECTIVE Our goal for this study is to address whether and how the circadian rhythms of social activity observed through telephone calls could be automatically modeled in older adults. METHODS We analyzed a 12-month data set of outgoing telephone CDRs of 26 adults older than 65 years of age. We designed a statistical learning modeling approach adapted for exploratory analysis. First, Gaussian mixture models (GMMs) were calculated to automatically model each participant’s circadian rhythm of telephone call activity. Second, k-means clustering was used for grouping participants into distinct groups depending on the characteristics of their personal GMMs. RESULTS The results showed the existence of specific structures of telephone call activity in the daily social activity of older adults. At the individual level, GMMs allowed the identification of personal habits, such as morningness-eveningness for making calls. At the population level, k-means clustering allowed the structuring of these individual habits into specific morningness or eveningness clusters. CONCLUSIONS These findings support the potential of phone technologies and statistical learning approaches to automatically provide personalized and precise information on the social rhythms of telephone call activity of older individuals. Futures studies could integrate such digital insights with other sources of data to complete assessments of the circadian rhythms of activity in elderly populations.

scholarly journals Spatial pattern completion deficits in older adults

2021 ◽  
Author(s):  
Meera Paleja ◽  
Julia Spaniol
Keyword(s):  
Older Adults ◽  
Spatial Pattern ◽  
Age Differences ◽  
Computational Models ◽  
Pattern Separation ◽  
Pattern Completion ◽  
Completion Task ◽  
Age Related ◽  
Baseline Task ◽  
Cue Availability

Aging may have an impact on the CA3 autoassociative network of the hippocampus, posited by computational models as supporting pattern completion. Twenty-five young (YAs) and 25 older adults (OAs) performed a spatial pattern completion task using a computerized navigational paradigm analogous to a rodent pattern completion task reliant on the CA3. Participants identified a previously seen goal location, and the availability of distal cues in the environment was manipulated such that 0, 2, or 4 cues were missing. Performance in both groups declined as a function of decreased cue availability. However, controlling for age differences in task performance during a pre-experimental baseline task, OAs performed equivalently to YAs when all cues were available, but worse than YAs as the number of cues decreased. These findings suggest spatial pattern completion may be impaired in OAs. We discuss these findings in the context of a growing body of literature suggesting age-related imbalances in pattern separation vs. pattern completion.

scholarly journals Reduced corticospinal responses in older compared with younger adults during submaximal isometric, shortening, and lengthening contractions

2019 ◽  
Vol 126 (4) ◽  
pp. 1015-1031 ◽  
Author(s):  
Jakob Škarabot ◽  
Paul Ansdell ◽  
Callum G. Brownstein ◽  
Kirsty M. Hicks ◽  
Glyn Howatson ◽  
...  
Keyword(s):  
Older Adults ◽  
Motor Control ◽  
Motor Evoked Potentials ◽  
Production Capacity ◽  
Emg Activity ◽  
Younger Adults ◽  
Lengthening Contractions ◽  
Age Related ◽  
Age Dependent ◽  
Contraction Type

The aim of this study was to assess differences in motor performance, as well as corticospinal and spinal responses to transcranial magnetic and percutaneous nerve stimulation, respectively, during submaximal isometric, shortening, and lengthening contractions between younger and older adults. Fifteen younger [26 yr (SD 4); 7 women, 8 men] and 14 older [64 yr (SD 3); 5 women, 9 men] adults performed isometric and shortening and lengthening dorsiflexion on an isokinetic dynamometer (5°/s) at 25% and 50% of contraction type-specific maximums. Motor evoked potentials (MEPs) and H reflexes were recorded at anatomical zero. Maximal dorsiflexor torque was greater during lengthening compared with shortening and isometric contractions ( P < 0.001) but was not age dependent ( P = 0.158). However, torque variability was greater in older compared with young adults ( P < 0.001). Background electromyographic (EMG) activity was greater in older compared with younger adults ( P < 0.005) and was contraction type dependent ( P < 0.001). As evoked responses are influenced by both the maximal level of excitation and background EMG activity, the responses were additionally normalized {[MEP/maximum M wave (Mmax)]/root-mean-square EMG activity (RMS) and [H reflex (H)/Mmax]/RMS}. (MEP/Mmax)/RMS and (H/Mmax)/RMS were similar across contraction types but were greater in young compared with older adults ( P < 0.001). Peripheral motor conduction times were prolonged in older adults ( P = 0.003), whereas peripheral sensory conduction times and central motor conduction times were not age dependent ( P ≥ 0.356). These data suggest that age-related changes throughout the central nervous system serve to accommodate contraction type-specific motor control. Moreover, a reduction in corticospinal responses and increased torque variability seem to occur without a significant reduction in maximal torque-producing capacity during older age. NEW & NOTEWORTHY This is the first study to have explored corticospinal and spinal responses with aging during submaximal contractions of different types (isometric, shortening, and lengthening) in lower limb musculature. It is demonstrated that despite preserved maximal torque production capacity corticospinal responses are reduced in older compared with younger adults across contraction types along with increased torque variability during dynamic contractions. This suggests that the age-related corticospinal changes serve to accommodate contraction type-specific motor control.

scholarly journals Spatial pattern completion deficits in older adults

2021 ◽  
Author(s):  
Meera Paleja ◽  
Julia Spaniol
Keyword(s):  
Older Adults ◽  
Spatial Pattern ◽  
Age Differences ◽  
Computational Models ◽  
Pattern Separation ◽  
Pattern Completion ◽  
Completion Task ◽  
Age Related ◽  
Baseline Task ◽  
Cue Availability

Aging may have an impact on the CA3 autoassociative network of the hippocampus, posited by computational models as supporting pattern completion. Twenty-five young (YAs) and 25 older adults (OAs) performed a spatial pattern completion task using a computerized navigational paradigm analogous to a rodent pattern completion task reliant on the CA3. Participants identified a previously seen goal location, and the availability of distal cues in the environment was manipulated such that 0, 2, or 4 cues were missing. Performance in both groups declined as a function of decreased cue availability. However, controlling for age differences in task performance during a pre-experimental baseline task, OAs performed equivalently to YAs when all cues were available, but worse than YAs as the number of cues decreased. These findings suggest spatial pattern completion may be impaired in OAs. We discuss these findings in the context of a growing body of literature suggesting age-related imbalances in pattern separation vs. pattern completion.

scholarly journals Age-dependent statistical learning trajectories reveal differences in information weighting.

2020 ◽  
Vol 35 (8) ◽  
pp. 1090-1104
Author(s):  
Steffen A. Herff ◽  
Shanshan Zhen ◽  
Rongjun Yu ◽  
Kat R. Agres
Keyword(s):  
Statistical Learning ◽  
Learning Trajectories ◽  
Age Dependent

scholarly journals Age-related neural dedifferentiation for individual stimuli: An across-participant pattern similarity analysis

2021 ◽  
Author(s):  
Joshua D Koen
Keyword(s):  
Older Adults ◽  
Memory Effect ◽  
Source Memory ◽  
Computational Models ◽  
Similarity Analysis ◽  
Memory Encoding ◽  
Neural Representations ◽  
Age Related ◽  
Pattern Similarity ◽  
Subsequent Memory Effect

Age-related neural dedifferentiation - reductions in the regional specificity and precision of neural representations - is proposed to compromise the ability of older adults to form sufficiently distinct neural representations to support episodic memory encoding. The computational model that spurred investigations of age-related neural dedifferentiation initially characterized this phenomenon as a reduction in the specificity of neural patterns for individual items or stimuli. Most investigations have focused on reductions in neural differentiation for patterns of neural activity associated with category level information, such as reduced neural selectivity between categories of visual stimuli (e.g., scenes, objects, and faces). Here, I report a novel across-participant pattern similarity analysis method to measure neural distinctiveness for individual stimuli that were presented to participants on a single occasion. Measures of item level pattern similarity during encoding showed a graded positive subsequent memory effect in younger, with no significant subsequent memory effect in older adults. These results suggest that age-related reductions in the distinctiveness of neural patterns for individual stimuli during age differences in memory encoding. Moreover, a measure of category level similarity demonstrated a significant subsequent memory effect associated with item recognition (regardless of an object source memory detail), whereas the effect in older was associated with source memory. These results converge with predictions of computational models of dedifferentiation showing age-related reductions in the distinctiveness of neural patterns across multiple levels of representation. Moreover, the results suggest that different levels of neural representations support successful encoding in young and older adults.

scholarly journals Gaining Insights Into the Estimation of the Circadian Rhythms of Social Activity in Older Adults From Their Telephone Call Activity With Statistical Learning: Observational Study

10.2196/22339 ◽  
2021 ◽  
Vol 23 (1) ◽  
pp. e22339
Author(s):  
Timothée Aubourg ◽  
Jacques Demongeot ◽  
Nicolas Vuillerme
Keyword(s):  
Older Adults ◽  
Circadian Rhythms ◽  
Statistical Learning ◽  
Elderly Population ◽  
Social Activity ◽  
The Elderly ◽  
Telephone Call ◽  
Data Set ◽  
Age Related ◽  
The Social

Background Understanding the social mechanisms of the circadian rhythms of activity represents a major issue in better managing the mechanisms of age-related diseases occurring over time in the elderly population. The automated analysis of call detail records (CDRs) provided by modern phone technologies can help meet such an objective. At this stage, however, whether and how the circadian rhythms of telephone call activity can be automatically and properly modeled in the elderly population remains to be established. Objective Our goal for this study is to address whether and how the circadian rhythms of social activity observed through telephone calls could be automatically modeled in older adults. Methods We analyzed a 12-month data set of outgoing telephone CDRs of 26 adults older than 65 years of age. We designed a statistical learning modeling approach adapted for exploratory analysis. First, Gaussian mixture models (GMMs) were calculated to automatically model each participant’s circadian rhythm of telephone call activity. Second, k-means clustering was used for grouping participants into distinct groups depending on the characteristics of their personal GMMs. Results The results showed the existence of specific structures of telephone call activity in the daily social activity of older adults. At the individual level, GMMs allowed the identification of personal habits, such as morningness-eveningness for making calls. At the population level, k-means clustering allowed the structuring of these individual habits into specific morningness or eveningness clusters. Conclusions These findings support the potential of phone technologies and statistical learning approaches to automatically provide personalized and precise information on the social rhythms of telephone call activity of older individuals. Futures studies could integrate such digital insights with other sources of data to complete assessments of the circadian rhythms of activity in elderly populations.

Sign in / Sign up

Export Citation Format

Share Document