Edited by: Shulan Hsieh, National Cheng Kung University, Taiwan
Reviewed by: Miriam Gade, Medical School Berlin, Germany; Yoav Kessler, Ben-Gurion University of the Negev, Israel
This article was submitted to Cognition, a section of the journal Frontiers in Psychology
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Working memory (WM) declines with increasing age. The WM capacity is often measured by means of the computerized version of the
Working memory (WM) is a complex system, in which incoming information is maintained and processed despite interference and distraction (
Different tasks require more or less activation of the central executive. There are situations in which only short-term memory capacity (STMC), a domain-specific skill is challenged, for example when we need to keep a telephone number in mind. Information has to be stored but not manipulated. Executive attention is required when we need to process additional information simultaneously (
However, more recent models questioned the existence of the central executive and provided a functional explanation of processes involved in WM. The crucial functions are updating, i.e., the ability to replace stored information by new upcoming information (
Executive functions decline with increasing age (
It has been frequently shown that aging is associated with WM decline (
It has been assumed that STMC is less vulnerable to age than WMC (
Age-related changes of WM capacity were reported in several studies using different WM-tasks (
The
Aging effects in this task have been reported repeatedly (
The ambiguous results from the little research in this area raise even more questions whether the
Studies in which
Findings that speak against
Interestingly, another study has shown that results from an
Updating WM with new information is substantial for high-level cognition, such as arithmetic operation, comprehension, and reasoning (e.g.,
Previous research reported above evaluated a general association between
First, in accordance with previous findings on age-associated cognitive impairments, we hypothesize that fluid cognitive functions like attention, memory and executive control decline as a function of age (
Third, we expect that the age-related reduction of WM performance as reflected in the
The data for the present study have been collected in multiple studies: pre-tests of two training studies with old (
A total of 533 healthy subjects without neurological or psychiatric impairments participated in the present study and completed the
All experiments, in which the data were collected, were reviewed and approved by the ethics committee of the Leibniz Research Centre of Working Environment and Human Factors, Dortmund, Germany. All subjects gave written informed consent in accordance with the Declaration of Helsinki.
Participants were seated comfortably in front of a monitor (17 in., refresh rate: 100 Hz, resolution: 640 × 480 pixels). The distance between the eyes and the monitor was approximately 70 cm. The letters were presented within a 16 × 16 mm matrix in the middle of the monitor (1.6° matrix/eye). Each letter was centrally adjusted. A checkpoint (5 × 5 mm, 0.5° checkpoint/eye) was presented before each stimulus, which was also located in the center of the monitor. The interstimulus interval (ISI-time) was set to 1,500 ms. Maximum reaction time (RT) of 1,200 ms and a minimum RT of 100 ms were allowed. Premature and late responses were categorized as missings. Two blocks were applied. The 0-back block (two-alternative forced choice task) served as a control condition with low WM demands. This block consisted of 102 trials. Participants were asked to respond to the occurrence of each letter ‘X’ by pressing a key with the index finger of the right hand. The task in the second block (2-back condition) demanded WM capacity. In the 2-back-condition (i.e., experimental condition), participants were asked to decide for each stimulus whether it matches the second last one, again by pressing the designated key. Otherwise no response was required. The 2-back-condition consisted of 156 trials. Each block consisted of 20% target and 80% non-target letters. RT and missings were analyzed for each block. The two blocks were presented without a break. Each participant received the same random series of letters. Each stimulus was presented for 300 ms regardless of whether the participant pressed a key or not.
In the Forward/Backward-Digit-Span-Task (‘Forward/ Backward-DS,’ from NAI,
In the Word Fluency Test (from LPS,
The Verbal Learning and Memory Test is a German version of the as Rey Auditory Verbal Learning Test (RAVLT;
The Multiple Choice Vocabulary Test (MWT-B;
The Digit-Symbol-Test is an evaluation tool used to assess cognitive functioning. It initially was part of the Wechsler Adult Intelligence Test (WAIS;
In the d2 Test (
The Stroop task (from NAI,
In order to further validate the results, we used error rates of a computer-based Stroop task from the block including interference (see
The Trail Making Test (TMT) consists of parts A and B. Both parts consist of 25 circles distributed over a sheet of paper. In Part A, the circles are numbered 1–25, and the participant should draw lines to connect the numbers in ascending order. In Part B, the circles include both numbers (1–13) and letters (A–L). As in Part A, the participant draws lines to connect the circles in an ascending pattern, but with the added task of alternating between the numbers and letters (i.e., 1-A-2-B-3-C, etc.). The test is thought to measure speed of processing, focussed attention, task switching and updating, which represent crucial executive functions.
A mixed analysis of variance (mixed ANOVA) was conducted to compare the effect of age (young vs. middle-aged vs. old; between-subjects factor) and task condition (0-back vs. 2-back; within-subject factor) on RT and the number of missings. Significant interactions and group differences were further analyzed using one-way ANOVAs with
For the analyses of psychometric tests with multiple conditions, such as Forward–Backward-DS, Stroop, and TMT, mixed ANOVAs were conducted to compare the effect of age group and task condition. In the digit-span task, the number of correctly repeated numerical series in the Forward vs. Backward-DS task was analyzed. In the Stroop task, effects of the task type (Stroop 1, Stroop 2, Stroop 3) on the time needed to perform the task was analyzed. To assess interference costs, a difference score between Stroop 3 and Stroop 2 was conducted and evaluated. Similarly, in the TMT task, the time to perform tasks A and B was analyzed. The difference between tasks A and B represents switch costs.
Tasks consisting of only one condition, such as word-fluency, MWT-B, d2, and Digit-Symbol-Test, were analyzed using one-way ANOVAs. Also, the different memory components in the VLMT, like
As a revised version of the d2 Test (d2-R) which is not directly comparable to the original version was used in a part of the sample, we report
Finally, we report re-test reliability scores (Pearson correlations) of the tests, which reflects the extent to which similar scores are obtained when the scale is administered on different occasions. Re-test reliability was obtained from 141 participants from the oldest and from 58 of the middle-aged groups. The re-tests were conducted as post-measures in the context of two training studies (
As the measures of interest in the correlation analyses we defined the differences in RT and accuracy between the 0-back and 2-back condition, which should reflect the specific WM-related task demands (storage and updating). By means of three correlation analyses (separate analyses for the three age groups), we investigated the relationships between effects of task condition in the
Additionally we conducted a correlation analysis for the 2-back–0-back difference scores and the difference score incongruent–congruent in accuracy of a computer-based Stroop task for each age group separately. This analyses included
The repeated measures ANOVA indicated main effects of task condition [0-back vs. 2-back;
RTs in 0-back- and 2-back tasks in young, middle-aged, and old groups. Error bars reflect standard deviations.
A similar pattern was found for the number of missed targets (Figure
Percent of missed targets in 0-back- and 2-back tasks in young, middle-aged, and old groups. Error bars reflect standard deviations.
The ANOVA of the Forward/Backward-DS revealed main effects for task condition [‘Forward’ vs. ‘Backward’;
In the Backward-condition, both young and middle-aged participants outperformed older subjects (
Figure
Digit span. Number of correctly repeated numerical series in forward and in reverse order in young, middle-aged, and old groups. Error bars reflect standard deviations.
The one-way ANOVA yielded a significant effect of age group [
Total number of correctly produced words in the Verbal-Fluency Test in young, middle-aged, and old groups. Error bars reflect standard deviations.
A series of one-way ANOVAs conducted for the most relevant parameters of the VLMT showed reliable group differences (see Figure
Total number of correctly produced words in subtests of the Verbal Learning and Memory Test (VLMT) in young, middle-aged, and old groups. Error bars reflect standard deviations.
The learning performance as reflected by the total score of the trials 1 to 5 showed an age-related decrease [
Also, recall of the interference list B (trial 6) showed significant group differences [
The delayed recall of the list (trial 7) showed a similar pattern of decreasing performance with increasing age [
The recognition trial of 15 old and 15 similar new words revealed no differences between groups [
The one-way ANOVA revealed an effect of age group [
Total number of correctly marked words in Multiple Choice Vocabulary Test (MWT-B) in young, middle-aged, and old groups. Error bars reflect standard deviations.
The one-way ANOVA revealed significant group differences in the number of correctly filled symbols [
Total number of correctly produced symbols in the Digit-Symbol-Test (DST) in young, middle-aged, and old groups. Error bars reflect standard deviations.
The one-way ANOVA indicated significant differences between age groups [
The ANOVA with the factors task type and age group revealed main effects for task type [Stroop 1 vs. Stroop 2 vs. Stroop 3;
Mean time in seconds needed to conduct Stroop 1, 2, and 3 tasks in young, middle-aged, and old groups. Error bars reflect standard deviations.
Finally, the interference effect assessed by the difference score between Stroop 3 and Stroop 2 was also substantially increased with age [
The ANOVA with the factors task type (TMT-A vs. TMT-B) and age group conducted for the TMT task revealed main effects of task type indicating longer performance time of the B than A version [68 s vs. 28 s;
Mean time in seconds needed to conduct TMT-A and TMT-B tasks in young, middle-aged, and old groups. Error bars reflect standard deviations.
In order to assess the effect of switching between task dimensions and to decompose the interaction, a difference score between TMT-B and TMT-A was computed and compared between age groups. A one-way ANOVA showed an increase in the switching ability as a function of age [
Table
Correlations between
Age group | Young ( |
Middle ( |
Old ( |
|||
---|---|---|---|---|---|---|
Measure | RT | Acc | RT | Acc | RT | Acc |
Psychometric task | ||||||
Digit Span Task (forward) | -0.093 | -0.160 | -0.054 | 0.003 | -0.153 | |
Digit Span Task (backward) | -0.136 | -0.201 | -0.143 | -0.117 | -0.157 | |
Word Fluency Test | -0.076 | -0.116 | -0.013 | -0.162 | -0.179 | -0.234∗ |
Digit Symbol Test | -0.251∗ | -0.205 | -0.235 | -0.267∗ | -0.211∗ | |
d2 Test (correct) | -0.205 | -0.225∗ | -0.067 | -0.185 | -0.154 | |
VLMT (Σ1-5) | -0.089 | -0.100 | -0.229 | -0.160 | 0.082 | -0.273∗ |
VLMT (recognition) | -0.073 | 0.014 | -0.151 | -0.187 | 0.047 | -0.225∗ |
Stroop Task (part 1) | 0.162 | 0.221∗ | 0.029 | 0.024 | 0.056 | |
Stroop Task (part 2) | 0.197 | 0.237∗ | -0.073 | 0.149 | 0.141 | |
Stroop Task (part 3) | 0.210 | 0.148 | 0.234∗ | 0.186 | 0.106 | |
Trial Making Test (A) | 0.261∗ | 0.236∗ | -0.027 | 0.227 | 0.179 | |
Trial Making Test (B) | 0.244∗ | -0.051 | 0.126 | |||
Finally, we conducted a confirmatory correlation analysis using difference scores (incompatible–compatible) for accuracy from a computer-based Stroop task. Whereas the young group showed a correlation between the
In the present study, we examined performance of young, middle-aged, and older participants in the
The first hypothesis, claiming that performance in the
However, the most important results are those in relation to our second hypothesis: the correlations between
The results show that
Although, as discussed above, the correlational analysis provided moderate coefficients, the finding was strengthened by the results of the confirmatory correlation analysis using interference scores from a computerized version of the Stroop test: while a substantial correlation between interference scores in accuracy of the Stroop test and
The substantial correlations between Stroop 3 and 2-back in young participants strengthen the findings of
Our findings are also consistent with age-related decline of executive functions described in the literature but the mechanisms underlying compensatory strategies to perform a task that requires executive control are still less understood (
In sum, our findings are consistent with previous results reporting age-related reduction in
Taken together, the 2-back task is a complex cognitive task that measures a conglomerate of distinct cognitive functions that are differently involved depending on age. Further research is needed to extract the functional components in more detail.
PG designed the study, analyzed the data, and wrote the manuscript. EH analyzed the data and wrote the manuscript. MF designed the study and approved the final version of the manuscript. ST analyzed the data and wrote the manuscript. EW wrote the manuscript and approved the final version of the manuscript.
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
We thank Claudia Frieg, Ines Mombrei, and Christiane Westedt for conducting the testing and Ludger Blanke for developing the software and technical support. We wish to thank the team of the Dortmund Vital Study Silke Joiko and Carola Reiffen. The research reported in the present article was partly supported by the Insurance Association (GDV, Gesamtverband der Deutschen Versicherungswirtschaft). We also wish to thank the reviewers for important and thoughtful comments on the previous version of this article. The publication was supported by the openaccess fund of the Leibniz Society and Technical University of Dortmund.