Bachelorproject
Individual Differences in Trainability on
Executive Functions in Healthy Seniors
Learning a Second Language
Milan Groot
Student number: 10560130 Accompanist: Jessika Buitenweg University of Amsterdam
Date: 27-05-2016
Total words abstract: 126 Total words article: 5050
Abstract
The increased amount of seniors that experience cognitive impairments, led to
investigations into possible coping strategies. That is why this study aimed to
investigate if individual differences may contribute in trainability on executive
functions. Thirteen subjects participated and performed an Italian training for three
weeks. Before and after the training, three cognitive tasks were assessed to measure
their executive functioning, such as inhibition, updating and switching. Three
individual differences (quality of sleep, physical activity and attitude towards aging)
were taken into account to see if they were of any influence in trainability on
executive functions. The results did not show any significant relation and therefore,
the hypothesis was not supported. Hence, it was concluded that these three individual
Introduction
At this moment, our life span is increasing tremendously compared to a
hundred years ago. Due to that, the number of seniors has grown (cbs, 2011). These
seniors are being confronted with restrictions associated with aging in their daily
functions. Aging often causes cognitive decline, like cognitive slowing, slight
difficulties on attention tasks, and severe memory impairment (Buckner, 2004). These
cognitive functions are part of the executive functions, which control and monitor our
behaviour and learning through life. This mainly happens unconsciously (Salthouse,
Atkinson, & Berish, 2003). Executive functions become especially active in new
situations and can be divided into three domains: shifting, updating, and inhibition,
based on latent factor analysis by Miyake and colleagues (2000; as cited in
Buitenweg, Murre, & Ridderinkhof, 2012).
The first function, shifting, refers to the possibility to switch between tasks or
actions. If the environment changes, different from a well-known situation, someone
has to adapt. This requires shifting to anticipate properly in the new situation. The
next function is updating, this is an essential aspect of working memory. Working
memory controls all incoming information and adjusts this information to be
remembered and stored in memory (Klingberg, 2010). The last function, inhibition, is
the ability to inhibit certain behavior and manage distractions from the environment.
This ability is required especially during learning or conversations in a social
environment that is associated with concentration (Hasher & Zacks, 1988; Andrés,
Guerrini, Phillips, & Perfect, 2008).
The executive functions do not have a precise location in the brain, but the
part of the brain that is most involved when using these functions, is the frontal lobe
(Hedden & Gabrieli, 2004). The frontal lobe reaches full maturity around the age of
compared to the rest of the brain (Fuster, 2002). Due to shrinkage of the
hippocampus, prefrontal cortex, and the basal ganglia, which are also very important
structures associated with cognition, executive functions will take more effort when
aging (Buitenweg, Murre, & Ridderinkhof, 2012).
For years, people thought that brain plasticity remains static after a critical
period in early childhood (Raz, 2000). Brain training or any other form of cognitive
training was seen as a waste of time. Research showed that the brain remains plastic,
even into adulthood (Hedden & Gabrieli, 2004). This is a remarkable discovery,
especially for adults and seniors, because now we know that we can still train our
brains in order to prevent deterioration. To keep the brain healthy as long as possible
and slow down the process of cognitive decline, several interventions are possible.
Cognitive training, also known as brain training, is one possibility to train
several aspects of executive functions and postpone cognitive decline. To evaluate the
effects of training and their results on executive functions, research that examined
shifting, inhibition and updating will be discussed. Kramer, Hahn and Gopher (1999)
examined differences in switch performances between young and older adults. The
first results from the tasks showed age-related differences in switch costs, but after
some practice the switch costs between the two groups were equivalent (Kramer,
Hahn, Gopher, 1999). This suggests that this form of cognitive practice will
contribute in moments of switching, like dealing with several aspects to process at the
same moment. Elderly can train this function to feel pleasanter in new situations
where a lot of new information has to be processed.
A different study that focussed on memory showed that healthy seniors
improved on several memory tasks after practicing an updating working memory task.
A list of unknown letters (varying between five and eleven) was shown and the
memory performances of the participants and achievements for unpractised tasks
improved as well (Morrison & Chein, 2011). This suggests that training working
memory skills will result in fewer decline compared to no exercise. Brain training,
such as puzzles, is a fun and doable way to improve memory, which results in less
difficulty in recalling information (Nouchi et al., 2013).
Inhibitory processes require executive control that is supported by the frontal
cortex. Because of shrinkage of some structures in the frontal lobe, inhibition of
distracting factors takes more effort when getting older (West, 1996; Jurado &
Rosselli, 2007). Results from a Stroop interference practicing study showed that older
adults have hard times in developing new automatic processes and to adjust their
existing processes (Andrés, Guerrini, Phillips, & Perfect, 2008). Bilingualism is
associated with positive cognitive progress, based on developmental studies (boek, E
bialystok, 2001). That is why a lot of research studied bilinguals on several cognitive
tasks, like inhibition tasks, and compared the results to monolinguals. Results were
associated with more frontal activation, which is associated with executive functions.
Blumenfeld and Marian (2011) showed that bilinguals are better at suppressing
task-irrelevant information compared to monolinguals. Because the results from bilingual
studies are promising, the aim of this study is to examine if individual differences in
elderly may contribute in learning a new language as cognitive training.
Besides cognitive training, individual differences may be important factors
that have their influence on the training process. Research is mostly based on
participants divided into two or more groups. Their conclusions tell something about
an effect based on an average of the population. This study will look at the individual
differences to see if personal factors influence their trainability, because individual
differences are factors that influence performances on cognitive tasks (Humphreys &
some individual differences, such as the quality of sleep, physical activity, and
attitude towards aging, which may contribute in cognitive training.
The first individual difference that is being discussed is attitude towards aging.
When we get older, as discussed above, physical and cognitive performances will
decline. Difficulty with retrieving information will be interpreted as the first signs of
dementia (Hess, Auman, Colcombe, & Rahhal, 2003). This goes along with
negativity, because it is frustrating for people when information cannot be
remembered. Negative judgements about aging can intensify cognitive decline. But
on the other hand, interventions that activate positive stereotypes of aging improve
memory performance, memory self-efficacy and views of aging in old participants
(Hess, Auman, Colcombe, & Rahhal, 2003). These results suggest that having a
negative idea about aging will influence cognitive performances in a negative manner.
The opposite is true when having a positive view. That is why this study will ask the
subjects to share their experiences of aging and if their experiences are in a way
positive or negative, to check if their attitude towards aging has any influence on
trainability.
Quality of sleep is another individual difference that is an important factor
when training cognitive performances, demonstrated in a research by Walker et al.
(2002). The association between good quality of sleep and cognitive performance is
strong. Differences between poor and good sleepers on tests of working memory,
attentional set shifting, and abstract problem solving were significant (Nebes et al.,
2009). Due to these results, this study will include quality of sleep as an individual
difference and examine if there is a positive association with cognitive performances.
This will also count for the physical activity of the participants. A research from
Bixby et al. (2007) supported the relationship between physical activity and cognition
lobe (besides the benefits from cognitive stimulation), the region that is mainly
associated with executive functions. Speed, spatial, controlled, and executive
functions derived benefit from aerobic training (Raz, 2000). Therefore, this study will
include the hours of physical activity from the participants to see if there is a positive
relation between physical activity and trainability.
A good number of articles have been written about interventions to prevent
seniors from cognitive decline. This study will investigate a new intervention to
explore brain training from a new perspective and hopefully will add some promising
data to the existing literature. Based on the promising results from bilingual studies
discussed above, the cognitive training in this study will contain Italian language
training. Individual differences will be used as moderators to test if they contribute in
trainability. Figure 1 shows this relationship.
Three Individual Differences
Language Training Executive functions
Figure 1. Three individual differences that influence the effect of language training on
executive functions.
However, Verreyt et al. (2016) did find prove against the idea that dominating
a second language will compensate for age-related deterioration, and thinks that
switching itself results in less decline in executive functioning instead of dominating a
second language. To check this hypothesis, participants in this study will get training
in a new language, lasting for three weeks. Before and after the training, executive
functions will be measured using different cognitive tasks. Afterwards, the scores
from the participants will be analysed to see if their cognitive performances improved
compared to their scores before the training, and individual differences will be taken
individual differences, a higher score on physical activity, the quality of sleep and
view of aging, is associated with a higher score on the cognitive tests and the
language quiz.
Method
ParticipantsA total of 26 healthy seniors participated in this experiment, consisting 15
females. Other researches that engaged in this study hypothesized that learning a
second language would improve executive functions, and therefore they used a
control condition with 25 participants to investigate the effect of language training on
executive functions. This study did not take the control condition into account. The
healthy seniors from 65 years of age and above (M = 70.15, SD =4.24) were recruited
from flyers and via several elderly associations and societies. Participants were
excluded from participation in this experiment if they had any history of
neuropsychological diseases. Besides the psychological health, subjects who were
bilinguals, or had any experience with the Italian language, they were not allowed to
participate in this study. These exclusion criteria were based on the idea that
executive functions will be better performed when dominating a second language
(Bialystok et al., 2004). All participants came to the laboratory for two sessions, of
approximately 1 hour each. The interval between the two sessions was three weeks.
After the training, participants received a little present, a brochure about keeping the
brain healthy as long as possible, and they could keep the language training if
preferred.
This study examined language trainability in seniors, which included language
training in Italian. The training contains a written book with vocabulary and grammar
material, and an audiotape with different exercises (Studieplan, Italiaans voor
beginners). The participants had to practice daily for 30 minutes, during three weeks
(Cohen, 2011). The subjects were given a log book to fill in, in order to check if the
training was performed daily, how well the subject slept the night before, and how
many hours of physical activity was performed. This log book was used to analyse
individual differences as explained above. Before and after the training, participants
had to perform three executive function tasks in the laboratories. The first was the
Simon Task, developed by J. R. Simon, who first published the effect in 1967 (Simon,
& Wolf, 1963; Bialystok, et al., 2004). This task measures the ability of inhibition.
Participants had to respond to two different colored lights, green or blue, after a focus
cross in the middle of the screen of a laptop. When the green light popped up, the
subject had to press a key with the right index finger and when the blue light popped
up, the subject had to use the left index finger. The location of the stimulus differed
throughout the experiment; the stimulus location was congruent or incongruent to the
index finger. The task consisted 16 practice trials, and two blocks of 36 trials (36
congruent, 36 incongruent). This amount of trials was based on a study by Bialystok,
Craik, Klein, & Viswanathan (2004). The second task was the Corsi Block task,
which assesses short-term working memory (Kessels et al., 2000). This task involved
mimicking a computer as it tapped a sequence of identical spatially separated blocks.
Participants had to click on the blocks using the mouse of the computer to mimic the
tapped sequence. The task began with 2 numbers of blocks, rose until the subject
made two errors in a row, and closed after the errors. The last task was the Trail
Making Test, which assesses task switching (Gaudino, Geisler, & Squires, 1995;
connect a set of numbered dots (1 to 10), or dots with a letter of the alphabet (a to j),
in the right order. The first part consisted only numbers or letters, and in the second
part, the subject had to alternate between the numbers and letters (1, A, 2, B, etc.).
The participants had to finish both parts as quickly as possible, and the time to
complete the task was used as a performance metric. Besides the executive function
tasks, the Shipley questionnaire was used to measure the IQ of each participant. The
questionnaire consisted 20 questions about sequences of numbers or words that had to
be completed (Shipley, 1940; Schmand & Smeding, 2000). For example: white -
black, short - tall, down - ... At last, the participants had to perform a language quiz
with 32 questions, consisting of words or small sentences in Dutch or Italian, as a
manipulation check. Participants had to translate the questions to Dutch or Italian.
This test was performed before and after the training, The two language quizzes were
randomized in order to make sure that the level of difficulty was equal.
Procedure
All the participants were emailed with an intake questionnaire, which
contained personal questions like age, experience with a Roman language, but also
their view of aging and how they experienced the phenomenon of getting older on a 1
to 7 scale (1 = negative, 7 = positive). This was a check to see if the subjects met any
of the exclusion criteria and to measure some individual differences. If the
participants were approved to participate in this study, they were invited for the first
session. When the participants arrived at the lab, they had the ability to read the
information brochure about the study and had to sign the informed consent if agreed.
This session began with the Shipley test, to measure their IQ. When finished, all three
executive functions tasks were performed in the following order, Simon task, Corsi
After the first session, the experimenter explained how to use the language training
they got to take home, and how to fill in the log book. The second session took place
after three weeks and the participants had to bring their log book. In this session, only
the three executive functions tasks and the language quiz were performed. At the end
of the session, the participants were thanked for participation and were handed a small
present and a brochure with information about keeping the brain healthy as long as
possible.
Results
The aim of this study was to test the hypothesis that individual differences
may contribute in learning a new language and will improve executive functioning in
elderly. Based on an a priori sample size calculator for Multiple Regression
(http://www.danielsoper.com/), the required sample size was 76 with a power level of
0.8. This study started with only 26 participants, but nine participants dropped out
because they thought the training was too onerous and four participants were
excluded from this study, two due to illness and two due to refusal to study Italian.
The data of the remaining thirteen participants was used in the analyses. Two outliers
were found in de data, but because of interest in individual differences, these outliers
were not excluded from the data.
To make sure that the participants studied any Italian during the training and
improved their Italian, a manipulation check was executed. The average from the
language quiz before and after the training was calculated with the accompanying
standard deviation, see Table 1.
Table 1
Average Language Quiz scores and Standard Deviations of the Pre- and Post-test
Experimental Condition
16,5 (1,9) 26,2 (2,7) 9,7
Note. Effect = Post test – Pre test.
On average, the scores from the participants on the language quiz were higher
after the language training (M = 26.2, SE = 9.6), compared to their scores before the
training (M = 16.5, SE = 6.7). This difference, 9.7, was significant t(12) = -3.417, p =
.005. A significance level of 5% was used in this study (Field, 2013), and therefore,
the manipulation check succeeded.
A Multiple Regression was used in this study, because this study is interested
in the relationship of the individual differences in trainability, rather than the average
scores and the effect of the training on cognitive performances. The three cognitive
task scores are separately analysed in relation to the individual differences and the
training because a Multivariate test cannot analyse the overall model. Three separate
Multiple Regressions will be executed, in which the cognitive task scores are the
dependent variables and the language training and individual differences are the
independent variables.
First, the individual differences and the language training were analysed in
relation to the difference scores of the Simon task. The assumptions of normality,
linearity between the independent and dependent variables, reliability and
homoscedasticity were met. Because the effect was not significant F(8) = .270, p =
.889, the model was not able to predict the outcome variable. However, the
unstandardized beta coefficients were taken into account to see the influence of
individual differences in trainability on executive functions. Participants' predicted
Simon scores were equal to -422 + 22 (sleep) + .2 (physical) + 35 (attitude), where
scale score. Participants' Simon scores increased with 22 points for each hour of
sleep, .2 points for each unit of physical activity (in percentages) and 35 points for
each extra point on the attitude scale. Figure 2 shows the individual scores on the
Simon task.
Figure 2. Mean scores per individual on the Simon task, before and after the training.
Figure 2 shows that the majority of the participants had a lower average score
after the training compared to their scores before the training. This implies that the
participants were more accurate and faster when responding to the congruent and
incongruent stimuli. The positive scores on the y-axis correspond to the more correct
responses to congruent stimuli compared to incongruent stimuli. However, hours of
sleep, hours of physical activity and attitude towards aging were not significant
Second, the individual differences and the language training were analysed in
relation to the difference scores of the Corsi Block task. The assumptions of
normality, linearity between the independent and dependent variables, reliability and
homoscedasticity were met. Because the effect was not significant F(8) = .294, p =
.874, the model was not able to predict the outcome variable. However, the
unstandardized beta coefficients were taken into account. Participants' predicted Corsi
Block scores were equal to -4 - .06 (sleep) + .02 (physical) + .4 (attitude).
Participants' Corsi Block scores decreased with .06 points for each hour of sleep,
increased with .02 points for each unit of physical activity (in percentages) and .4
points for each extra point on the attitude scale. Figure 3 shows the individual scores
on the Corsi Block task.
Figure 3. Mean scores per individual on the Corsi Block task, before and after the
training.
Figure 3 shows that the participants scored variously before and after the
scored worse. Based on these findings, the results did not accord with the hypothesis.
In response to these findings and the insignificant results from the analysis, the three
individual differences were not significant predictors of the Corsi Block scores.
At last, the individual differences and the language training were analysed in
relation to the difference scores of the Trail Making Test. The assumptions of
normality, linearity between the independent and dependent variables, reliability and
homoscedasticity were met. Because the effect was not significant F(8) =1.969, p =
.192, the model was not able to predict the outcome variable. However, the
unstandardized beta coefficients were taken into account. Participants' predicted TMT
scores were equal to 254 - 27 (sleep) - .3 (physical) - 4 (attitude), thus their TMT
scores decreased with 27 points for each hour of sleep, .3 points for each unit of
physical activity (in percentages) and 4 points for each extra point on the attitude
scale. Figure 4 shows the individual scores on the TMT task.
Figure 4 shows that the participants scored variously before and after the
training. Some participants performed better, corresponding to a lower score after the
training, and others scored worse. Based on these findings, the results did not accord
with the hypothesis. Hours of sleep, hours of physical activity and attitude towards
aging were not significant predictors of the TMT scores.
The overall effects were not significant and therefore it was concluded that
individual differences did not contribute in trainability on cognitive functions. This
accounted for the individual differences that were analysed together in comparison to
the executive functions. The analyses also showed the significance results per
individual difference in the coefficients table, in comparison to the executive
functions. None of the individual differences showed any significant effect in
comparison to the executive functions.
Discussion
The aim of this study was to investigate if individual differences contribute in
trainability on cognitive performances. No significant relationship was found between
the three individual differences and the three cognitive scores. Therefore, it was
concluded that quality of sleep, physical activity and attitude towards aging did not
influence trainability. These findings are not in line with the literature discussed
above about the three individual differences and their effect on executive functions.
The study by Nebes et al. (2009) showed significant results between poor and
good sleepers on working memory, attentional shifting and problem solving. The
exact hours of sleep per night and the association between good cognitive
performances has not yet been found. Hence, a positive relation has been found
The results in this study did not confirm any of these findings. This may be due to the
assessment of quality of sleep. Participants had to report how many hours they slept
the night before in their log book. The averages hours of sleep per night were 6.9
(1.13), but the hours of day time napping were not reported. At the second session,
several participants reported that it is really common to have a nap during daytime.
Because of these naps, the hours of sleep at night have been less compared to their
lives before. This was not taken into account and therefore, the quality of sleep has
not been assessed correctly. Results from previous studies showed an association
between hours of daytime napping and cognition. Blackwell et al. (2005) showed that
women of 65 years of age or older, had worse cognition when taking a nap for two
hours or more. Based on these results, assessment of the quality of sleep has not been
executed correctly.
Another individual difference, physical activity, has not been assessed in the
right way. Participants were asked to report if they performed less or more than 30
minutes of physical activity per day. Participants reported that they performed more
than 30 minutes per day due to walking, grocery shopping and going to the gym.
Walking and grocery shopping are no physical activities in which the heart rate is
really much increased. Therefore, the reports in this study were not accurate.
However, a study by Aichberger et al. (2010) showed that any type of regular activity
influenced cognitive decline in a positive way after a study of 2,5 years. But when the
participants engaged in vigorous activities more than once a week, they showed even
less cognitive decline. Accordingly, the participants in this study had to be informed
properly to get an accurate measure of physical activities. Due to the incorrect
assessment, the data consisted of percentages of the total days of less or more than 30
minutes of physical activity, from the three weeks of training. These results were
Besides the incorrect ways of measuring the individual differences, a
remarkable matter in this study was the low amount of participants. Based on the
calculation of the sample size, 76 people should have participated in this study with a
power level of 0.8 to be able to find an effect (http://www.danielsoper.com/).
Unfortunately, the time that was set for recruiting people for this study was very
short. Additionally, the exclusion criteria were very strict and the amount of
self-study during the experiment led to the fact that a lot of potential participants were not
allowed or wanted to participate. The information brochure and flyers that were
distributed in several elderly associations and societies or on the streets were provided
with the exclusion criteria, such as bilingualism, no experience with Italian or
suffering a neuropsychological diseases. Also, the amount of self-study was reported,
and based on the reactions of potential participants, it was concluded that the amount
of self-study was too much due to the short period of time that was arranged.
These reactions in combination with the expectations about the short period
that was arranged to study Italian, led to the conclusion that only three weeks of
training would not result in any effects. Morrison and Chein (2011) found a
significant improvement in memory performances in elderly after a training lasting
for eight weeks. The existing literature about mastering the basics of a new language
did not contain a certain amount of hours of practicing to find an effect. Therefore, it
is not possible to determine the minimum amount of hours of practice during an
experiment, but based on literature about learning a new language, the more time is
spend, the better you manage a language and has it effects on cognition (Scovel,
2003). However, the participants in this study showed a significant effect when
comparing the language results before and after the training. But the improvement did
not result in any effect on executive functions. Hence, it was concluded that only
individual difference scores on the language test.
Figure 5. Mean scores per individual on the language task, before and after the
training.
Figure 5 shows that the majority of the participants improved their scores on
the language task after training. The mean differences per individual were small. This
may be due to the fact that the period of training was only three weeks. Besides, the
mean scores on the first language task were higher than expected, because one of the
exclusion criteria was that the participant was not skilled in Italian. But based on the
results from the first language test, it seems that some of the participants already knew
Italian. This may be due to the fact that some participants went to Italy for holidays or
watch Italian television or films, and remember some basic words on the test. In this
multicultural society we live in. Some basic knowledge of Italian was already known
or might have been inferred if they knew French or Spanish, and that could explain
the high scores on the first language test.
At last, in the intake the participants had to answer the question if they
suffered from any neuropsychological diseases. None of the participants answered
yes, but the intake did not contain a question about intake of medicines. This may be
an imported question because medicines could have influences on cognitive
performances. Altogether, these points of discussion discussed above, should be taken
into account in replication studies.
The number of participants should be 76, to be able to find a significant effect
(http://www.danielsoper.com/). Only with this minimum amount of participants a
study is able to find a possible significant outcome. To reach this number of
participants, the period of training should be extended to as long as possible (Scovel,
2003). This would decline the intensity of the training and make it possible for the
participants to have enough time to study well and master a new language. Besides
the time of training, an individual self training will mostly led to less improvement
compared to a mandatory language training (Feldman, 2003). A mandatory class will
cause regularity in training and study, which occurs less in self-study. This change in
training will led to a big improvement in a new language, and therefore, a significant
result in its effect on executive functions.
At last, any replication should be really accurate in the way of measuring
individual differences. Literature about similar topics should help to assess the
components properly. Besides, the individual differences did not effect trainability on
executive functions, but there might be other individual differences that could be
taken into account and investigate their effect in trainability on executive functions.
the individual differences (sleep, physical activity and attitude towards aging)
contribute in trainability on cognitive performances. Due to the small amount of
participants no relevant conclusion can be made about the hypothesis. A replication of
this study with at least 76 participants could show more promising data about the
influence of individual differences in trainability on cognitive performances. At this
moment, with the immense growth of the elderly population, these studies should
shed light on possible interventions that people can take to prevent cognitive decline.
More research about this subject should be implemented to give elderly and
prospective seniors evidence-based results to handle cognitive deterioration and
References
Aichberger, M., Busch, M., Reischies, F., Ströhle, A., Heinz, A., & Rapp, M. (2010). Effect of Physical Inactivity on Cognitive Performance after 2.5 Years of Follow-Up. GeroPsych, 23(1), 7-15.
Andrés, P., Guerrini, C., Phillips, L. H., & Perfect, T. J. (2008). Differential effects of aging on executive and automatic inhibition. Developmental
Neuropsychology, 33(2), 101-123.
Bialystok, E. (2001). Bilingualism in development: Language, literacy, and cognition. Cambridge, UK: Cambridge University Press.
Bialystok, E., Craik, F. I., Klein, R., & Viswanathan, M. (2004). Bilingualism, Aging, and Cognitive Control: Evidence From the Simon Task. Psychology and
Aging, 19(2), 290-303.
Bixby, W. R., Spalding, T. W., Haufler, A. J., Deeny, S. P., Mahlow, P. T.,
Zimmerman, J. B., & Hatfield, B. D. (2007). The unique relation of physical activity to executive function in older men and women. Medicine &
Science in Sports & Exercise, 39(8), 1408-1416.
Blackwell, T., Yaffe, K., Ancoli-Israel, S., Schneider, J. L., Cauley, J. A., Hillier, T. A., Stone, K. L. (2006). Poor Sleep Is Associated With Impaired Cognitive Function in Older Women: The Study of Osteoporotic Fractures. The Journals
of Gerontology Series A: Biological Sciences and Medical Sciences, 61(4),
405-410.
Blumenfeld, H. K., & Marian, V. (2011). Bilingualism influences inhibitory control in auditory comprehension. Cognition, 118(2), 245-257.
Bonner, S. E. and G. B. Sprinkle. 2002. The effects of monetary incentives on effort and task performance: Theories, evidence, and a framework for research.
Accounting, Organizations and Society 27(4-5): 303-345.
Buckner, R. L. (2004). Memory and executive function in aging and AD. Neuron,
44(1), 195-208.
Buitenweg, J. I., Murre, J. M., & Ridderinkhof, K. R. (2012). Brain training in progress: A review of trainability in healthy seniors. Frontiers in Human
Neuroscience Front. Hum. Neurosci., 6.
Calculator: A-priori Sample Size for Multiple Regression. (n.d.). Retrieved May 04, 2016, from http://www.danielsoper.com/statcalc/calculator.aspx?id=1
Carlson, S. M., & Meltzoff, A. N. (2008). Bilingual experience and executive functioning in young children. Developmental Science Developmental Sci,
Cohen, A. D. (2011). Strategies in learning and using a second language. Harlow, England: Longman.
Dahlin, E., Bäckman, L., Neeley, A., & Nyberg, L. (2009). Trainig of the executive component of working memory: subcortical areas mediate transfer effect.
Restor Neurol Neurosci 27(5), 405-419.
Dewald, J. F., Meijer, A. M., Oort, F. J., Kerkhof, G. A., & Bögels, S. M. (2010). The influence of sleep quality, sleep duration and sleepiness on school
performance in children and adolescents: A meta-analytic review. Sleep
Medicine Reviews, 14(3), 179-189.
Feldman, A. (2003). Validity and Quality in Self-Study. Educational Researcher,
32(3), 26-28.
Fuster, J. M. (2002). Frontal obe and cognitive development. Neurocytol, 31(3-5), 373-385.
Gemeenten zien aantal 65-plussers tot 2040 toenemen. (2012, July 26). Retrieved May 18, 2016, from https://www.cbs.nl/nl-nl/achtergrond/2012/30/gemeenten-zien-aantal-65-plussers-tot-2040-toenemen
Hedden, T., & Gabrieli, J. D. (2004). Insights into the ageing mind: A view from cognitive neuroscience. Nature Reviews Neuroscience Nat Rev Neurosci,
5(2), 87-96.
Hess, T. M., Auman, C., Colcombe, S. J., & Rahhal, T. A. (2003). The impact of stereotype threat on age differences in memory performance. The Journals
of Gerontology Series B: Psychological Sciences and Social Sciences, 58(1)
3-11.
Jurado, M. B., & Rosselli, M. (2007). The Elusive Nature of Executive Functions: A Review of our Current Understanding. Neuropsychol Rev Neuropsychology
Review, 17(3), 213-233.
Kessels, R. P., Zandvoort, M. J., Postma, A., Kappelle, L. J., & Haan, E. H. (2000). The Corsi Block-Tapping Task: Standardization and Normative Data. Applied
Neuropsychology, 7(4), 252-258.
Klingberg, T. (2010). Training and Plasticity of Working Memory. Trends in
Cognitive Sciences, 14(7), 317-324.
Kramer, A. F., Hahn, S., & Gopher, D. (1999). Task coordination and aging: Explorations of executive control processes in the task switching paradigm.
Acta Psychologica, 101(2-3), 339-378.
Lehto, J. E., Juujärvi, P., Kooistra, L., & Pulkkinen, L. (2003). Dimensions of executive functioning: Evidence from children. British Journal of
Miyake, A., Friedman, N. P., Emerson, M. J., Witzki, A. H., Howerter, A., & Wager, T. D. (2000). The Unity and Diversity of Executive Functions and Their Contributions to Complex “Frontal Lobe” Tasks: A Latent Variable Analysis.
Cognitive Psychology, 41(1), 49-100.
Morrison, A. B., & Chein, J. M. (2010). Does working memory training work? The promise and challenges of enhancing cognition by training working memory.
Psychonomic Bulletin & Review Psychon Bull Rev, 18(1), 46-60.
Nebes, R. D., Buysse, D. J., Halligan, E. M., Houck, P. R., & Monk, T. H. (2009). Self-Reported Sleep Quality Predicts Poor Cognitive Performance in Healthy Older Adults. The Journals of Gerontology Series B: Psychological Sciences
and Social Sciences, 64B(2), 180-187.
Nouchi, R., Taki, Y., Takeuchi, H., Hashizume, H., Nozawa, T., Kambara, T., & Kawashima, R. (2013). Brain Training Game Boosts Executive Functions, Working Memory and Processing Speed in the Young Adults: A Randomized Controlled Trial. PLoS ONE, 8(2).
Ohayon M. M, & Vecchierini M. F. (2005). Normative sleep data, cognitive function and daily living activities in older adults in the community. Sleep 28, 981–989.
Park, D. C., Gutchess, A. H., Meade, M. L., & Stine-Morrow, E. A. (2007).
Improving Cognitive Function in Older Adults: Nontraditional Approaches.
The Journals of Gerontology Series B:Psychological Sciences and Social Sciences, 62(Special Issue 1), 45-52.
Raz, N. (2000). Aging of the brain and its impact on cognitive performance: Integration of structural and functional findings. In F. I. M. Craik & T. A. Salthouse (Eds.), Handbook of aging and cognition (2nd ed., pp. 1–90). Mahwah, NJ: Erlbaum.
Salthouse, T. A., Atkinson, T. M., & Berish, D. E. (2003). Executive Functioning as a Potential Mediator of Age-Related Cognitive Decline in Normal Adults.
Journal of Experimental Psychology: General, 132(4), 566-594.
Schmand, B., & Smeding, H.M.M. (2000). Dutch translation of the Shipley Institute of Living Scale. Unpublished measure, Academic Medical Center,
Amsterdam, the Netherlands.
Scovel, T. (2003). Learning new languages: A guide to second language acquisition. Boston, MA: Heinle & Heinle.
Verreyt, N., Woumans, E., Vandelanotte, D., Szmalec, A., & Duyck, W. (2015). The influence of language-switching experience on the bilingual executive control advantage. Bilingualism Bilingualism: Language and Cognition, 19(01), 181-190.
Walker, M. P., Liston, C., Hobson, J., & Stickgold, R. (2002). Cognitive flexibility across the sleep–wake cycle: REM-sleep enhancement of anagram problem solving. Cognitive Brain Research, 14(3), 317-324.
