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Sustained attention is effortful, demanding, and subject to limitations associated with age-related cognitive decline. Researchers have sought to examine whether attentional capacities can be enhanced through directed mental training, with a number of studies now offering evidence that meditation practice may facilitate generalized improvements in this domain. However, the extent to which attentional gains are maintained following periods of dedicated meditation training and how such improvements are moderated by processes of aging have yet to be characterized. In a prior report (Sahdra et al., Emotion 11, 299–312, 2011), we examined attentional performance on a sustained response inhibition task before, during, and after 3-months of full-time meditation. We now extend this prior investigation across additional follow-up assessments occurring up to 7 years after the conclusion of training. Performance improvements observed during periods of intensive practice were partially maintained several years later. Importantly, aging-related decrements in measures of response inhibition accuracy and reaction time variability were moderated by levels of continued meditation practice across the follow-up period. The present study is the first to offer evidence that intensive and continued meditation practice is associated with enduring improvements in sustained attention and response inhibition, with the potential to alter longitudinal trajectories of cognitive change across the lifespan.
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Cognitive Aging and Long-Term Maintenance of Attentional
Improvements Following Meditation Training
Anthony P. Zanesco
&Brandon G. King
&Katherine A. MacLean
&Clifford D. Saron
Received: 29 September 2017 / Accepted: 13 February 2018 / Published online: 28 March 2018
#The Author(s) 2018. This article is an open access publication
Sustained attention is effortful, demanding, and subject to limitations associated with age-related cognitive decline. Researchers
have sought to examine whether attentional capacities can be enhanced through directed mental training, with a number of studies
now offering evidence that meditation practice may facilitate generalized improvements in this domain. However, the extent to
which attentional gains are maintained following periods of dedicated meditation training and how such improvements are
moderated by processes of aging have yet to be characterized. In a prior report (Sahdra et al., Emotion 11, 299312, 2011),
we examined attentional performance on a sustained response inhibition task before, during, and after 3-months of full-time
meditation. We now extend this prior investigation across additional follow-up assessments occurring up to 7 years after the
conclusion of training. Performance improvements observed during periods of intensive practice were partially maintained
several years later. Importantly, aging-related decrements in measures of response inhibition accuracy and reaction time vari-
ability were moderated by levels of continued meditation practice across the follow-up period. The present study is the first to
offer evidence that intensive and continued meditation practice is associated with enduring improvements in sustained attention
and response inhibition, with the potential to alter longitudinal trajectories of cognitive change across the lifespan.
Keywords Aging .Meditation .Response Inhibition .Sustained Attention .Vigilan ce
The human capacity to sustain attention over time is limited
and effortful, and is prone to fatigue, lapses, and fluctuations
with prolonged engagement (Fortenbaugh et al. 2017;
Langner and Eickhoff 2013;Warmetal.2008). These limita-
tions are exacerbated by age-related cognitive decline
(Fortenbaugh et al. 2015; Lustig and Jantz 2015; Smittenaar
et al. 2015), and there is now considerable interest in identi-
fying training interventions that can offer effective remedia-
tion in aging populations and promote cognitive
improvements in healthy individuals at large (e.g., Anguera
et al. 2013; Bavelier and Davidson 2013). Increasingly, re-
searchers have emphasized meditation- and mindfulness-
based approaches for the training of attention. Meditation-
based trainings have been shown to temper transient lapses
in attention that disrupt ongoing task performance (Jha et al.
2013;vanVugtandJha2011; Zanesco et al. 2013,2016), and
improve individualsability to sustain attention over time
(MacLean et al. 2010;Sahdraetal.2011; Zanesco et al.
2013). However, the extent to which attentional improve-
ments endure after periods of dedicated training, and how
continued meditation practice is associated with cognitive
change across the lifespan remains unclear and understudied.
The limited, fluctuating, and effortful nature of attention
historically forms a central motivation for improving atten-
tional abilities through meditation among diverse Buddhist
contemplative traditions (e.g., Gunaratana 2011; Wallace
1999). From this perspective, meditation is conceptualized
as a detailed, formalized system of mental training through
which practitioners cultivate specific cognitive capacities over
time, including increased clarity, stability, and duration of
*Anthony P. Zanesco
Department of Psychology, University of Miami, Coral Gables, FL,
Department of Psychology, University of California, Davis,
Davis, CA, USA
Center for Mind and Brain, University of California, Davis,
Davis, CA, USA
The MIND Institute, University of California, Davis, Davis, CA,
Journal of Cognitive Enhancement (2018) 2:259275
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attentional focus (Wallace 1999). While acknowledging that
these traditions are shaped by a multitude of sociohistorical
and soteriological factors, contemporary neurocognitive
frameworks of mindfulness and meditation have endeavored
to characterize families of meditation practice in terms of
known features of attention and cognitive control (Dahl
et al. 2015; Lippelt et al. 2014;Lutzetal.2008,2015; Vago
and Silbersweig 2012), and theories of skill learning and plas-
ticity (Slagter et al. 2011). Yet, the enduring consequences of
continued meditation training have received sparse consider-
ation in this emerging literature. Longitudinal investigations
that track practitioners across periods of training and years of
practice are critical for understanding the durability of trait-
level cognitive changes associated with meditation, and for
broadly characterizing the influence of attentional training
on cognitive development across the lifespan.
Meditation techniques are commonly understood and dis-
seminated by contemplative practitioners, teachers, and
mindfulness-based clinicians as exercises for use in long-
term or life-long personal development. Nevertheless, few
studies have attempted to characterize how meditation-
related cognitive improvements develop over years of prac-
tice, or whether such improvements are maintained following
periods of formal training. Investigations detailing the devel-
opmental trajectory and maintenance of training-related im-
provements are vital to understanding the benefits and limita-
tions of mindfulness-based interventions as traditionally con-
ceptualized. Ideally, such studies would implement repeated
assessments spread across extended time intervals; attempt to
distinguish periods of intensive training from less-intensive
durations of practice; and track both the quality and amount
of time that practitioners dedicate to continued practice over
these extended intervals. It is plausible, for example, that the
benefits of acute periods of training are difficult to maintain
absent an ongoing commitment to meditation orother lifestyle
or behavioral changes that support continued engagement
with contemplative practice. There is a need to examine how
meditation-related improvements manifest in concert with de-
velopmental changes in cognition, and whether meditation
practice can moderate the effects of aging-related cognitive
Studies of cognitive aging offer compelling evidence that
the ability to sustain attention and inhibit prepotent response
tendencies is diminished in later life (e.g., Fortenbaugh et al.
2015; Smittenaar et al. 2015), and greater reaction time vari-
portant marker of age-related impairment in executive control
(MacDonald et al. 2006; Vasquez et al. 2014;Westetal.
2002). Age-related deficits in these domains have spurred
the development of targeted intervention strategies for im-
proving cognitive performance in older adults, including
computer-based cognitive training programs (e.g., Anguera
et al. 2013; Toril et al. 2014), general lifestyle interventions
(e.g., Park et al. 2014), and mindfulness-based approaches (for
reviews, see Gard et al. 2014; Malinowski and Shalamanova
2017; Kurth et al. 2017). Although several studies have re-
ported cross-sectional differences between meditation practi-
tioners and meditation-naïve controls in older adult samples
(e.g., Laneri et al. 2016; Sperduti et al. 2016; van Leeuwen
et al. 2009), relatively few studies have investigated medita-
tion training as a directed intervention for older populations
(e.g., Malinowski et al. 2017). Overall, research tentatively
supports the claim that meditation practice can protect against
age-related deficits in attention and executive function.
Notably, however, no studies have longitudinally tracked
meditation practitioners over years of continued practice to
examine the moderation of age-related decline.
In our ongoing work, we have employed resource-
demanding vigilance taskssuch as our sustained response
inhibition task (RIT)to assess skilled attentional perfor-
mance in cognitively healthy adults (MacLean et al. 2009;
Sahdra et al. 2011). In the RIT, participants are asked to dis-
criminate between rare target and frequent non-target stimuli
(small vertical lines) while inhibiting behavioral responses to
targets over the course of performance. Using this task, we
have demonstrated increases in response inhibition accuracy
and attenuation of the vigilance decrement across a 3-month
period of intensive training in focused attention meditation
(Sahdra et al. 2011), and replicated these results in an inde-
pendent 1-month training study incorporating arelated style of
practice (Zanesco et al. 2013). In addition to measures of
performance accuracy, reductions in reaction time variability
were also observed in this latter study. We now revisit our
previous data (Sahdra et al. 2011) in light of an extensive
long-term follow-up investigation. Our goal is to characterize
the maintenance of training-related improvements across an
extended post-training interval, and to examine the influence
of continued meditation practice on age-related cognitive de-
cline and longitudinal training trajectories.
In our prior report, training and wait-list control partici-
pants were assessed on the RIT at the beginning, middle,
and end of a 3-month intensive meditation training (Sahdra
et al. 2011). Follow-up assessments were conducted approxi-
mately 6 months, 1.5 years, and 7 years following the inter-
vention. During training, practitioners engaged in shamatha
meditation practices (Wallace 2006) that are thought to in-
crease the clarity, stability, and duration of an individuals
concentration and to reduce the felt cognitive effort required
to maintain attention in a sustained manner (Lutz et al. 2015).
From a neurocognitive perspective, the features of concentra-
tion targeted by shamatha practice share considerable concep-
tual overlap with measures of attention derived from vigilance
tasks such as our RIT. These tasks place substantial demand
on supporting cognitive systems, leading to a monotonic de-
cline in ones capacity to detect and appropriately respond to
target stimuli over time (i.e., vigilance decrement; Mackworth
260 J Cogn Enhanc (2018) 2:259275
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1948). Studies of vigilance, moreover, have demonstrated that
increased task discrimination difficulty can lead to a corre-
sponding increase in the magnitude of this performance dec-
rement and in the amount of subjective effort, distress, and
demand reported by an individual (see for review, Langner
and Eickhoff 2013; See et al. 1995;Warmetal.2008). In order
to minimize the potential influence of individual differences in
discrimination capacity on observed training effects, we im-
plemented a visual thresholding procedure designed to control
levels of task difficulty across participants and assessments.
Lapses in attentional performance may also result from
graded variation in attentional control on a moment-to-
moment basis (e.g., Adam et al. 2015), or from shifts in atten-
tion to task-unrelated thought (e.g., mind wandering;
Smallwood and Schooler 2015). Indeed, increased research
on mind wandering and related phenomena (e.g., Cheyne
et al. 2009;Selietal.2013; Smallwood and Schooler 2015),
and the behavioral consequences of variability in attention and
associated functional brain networks (e.g., Adam et al. 2015;
Bellgrove et al. 2004; Weissman et al. 2006), has motivated
attempts to reconcile accounts of the vigilance decrement with
these more transient attentional lapses and fluctuations that
occur during ongoing task performance (Langner and
Eickhoff 2013; Thomson et al. 2015). This work suggests that
variability of response times may partly reflect graded fluctu-
ations in attention or episodes of task-unrelated thought. We
therefore examined response time variability over the course
of performance to characterize how ongoing fluctuations in
attentional stability are influenced by longitudinal processes
of aging and continued practice.
The primary study aims were to investigate the mainte-
nance of training-related changes in response inhibition, reac-
tion time variability, and vigilance over a 7-year period, and to
assess the moderating influences of aging-related declines in
performance and individual differences in continued medita-
tion practice. We hypothesized that practitioners would main-
tain some attentional benefits of training, and that continued
practice of meditation following training would be associated
with this maintenance. We also predicted an interaction be-
tween the amount of continued practice and age-related de-
clines in sustained attention and response inhibition. Older
practitioners who devoted greater time to meditation practice
in the years following training were expected to show reduced
effects of age-related decline, in contrast to individuals who
engaged in comparatively less continued practice.
Sixty experienced meditation practitioners were assigned to
either an initial training (N= 30) or wait-list control (N=30)
group through stratified random assignment; groups were
matched on age (M= 48.96 years at study assignment, range
=2269), gender, prior meditation experience, and baseline
personality variables (see MacLean et al. 2010;Sahdraetal.
2011, for full recruitment and matching criteria). During an
initial 3-month retreat (retreat 1), training participants resided
and practiced meditation at Shambhala Mountain Center
(SMC) in Red Feather Lakes, Colorado. During retreat 1,
wait-list control participants traveled to SMC for week-long
assessment periods but otherwise maintained their daily rou-
tines at home between assessments. Approximately 3 months
after retreat 1, these same wait-list control participants re-
ceived formally identical training during a second 3-month
residential retreat at SMC (retreat 2; n=29).
All participants
were invited to participate in three follow-up assessments con-
ducted approximately 6 months (M= 6.6 months, range =
4.711.9), 1.5 years (M= 17.9 months, range = 15.620.2),
and 7 years (M= 81.9 months, range = 73.393.9) following
the conclusion of their respective training periods. Follow-up
attrition was generally low (>70% retention at each assess-
ment; see Table 1for sample size at each assessment). All
participants were compensated $20 per hour of data
Meditation Training
Meditation training occurred under guidance of B. Alan
Wallace, a Buddhist teacher and contemplative scholar.
Training included shamatha techniques designed to foster
calm sustained attention on a chosen object, and complemen-
tary techniques, known as the Four Immeasurables (compas-
sion, loving-kindness, empathetic joy, and equanimity), aimed
at generating benevolent aspirations for the well-being of one-
self and others (Wallace 2006,2011). Primary practice in-
volved mindfulness of breathing, in which attention is drawn
to the tactile sensations of the breath. Participants also prac-
ticed attending to the arising of mental content (e.g., thoughts,
perceptions, sensations), a technique known as settling the
mind into its natural state, and focusing attention on the sense
of awareness itself, known as shamatha without a sign
(Wallace 2006,2011). Participants met twice daily for group
practice and discussion, devoted about 6 h of their remaining
day to solitary shamatha meditation, and about 45 min to Four
Immeasurables meditation. In addition to these formal practice
sessions, participants were encouraged to maintain mindful,
present-centered awareness throughout their day, and met with
Dr. Wallace privately once a week for guidance and advice.
Full details regarding the techniques employed and training
time dedicated to each practice can be found in Sahdra et al.
(2011) and Rosenberg et al. (2015).
One wait-list control participant withdrew prior to retreat 2 for reasons un-
related to the intervention.
JCognEnhanc(2018)2:259275 261
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At the 7-year follow-up assessment, participants were
asked to estimate the amount of time they spent meditating
outside of formal retreat settings (i.e., daily, non-intensive
practice) across the follow-up period. Participants estimated
their current weekly practice time, then adjusted these values
to estimate their total practice hours for the previous year,
before finally providing adjusted estimates for each preceding
year. Practice estimates were then summed over the entire
follow-up period (M= 3127.95 h, median = 1896, range =
24914,900). In addition, participants were asked to estimate
the total number of days they spent in formal retreat (i.e.,
intensive) practice across this period (M=293.19daysonre-
treat, range = 02125). Among participants with available
data (n= 40), all reported some form of continued meditation
practice across this follow-up interval; 85% attended at least
one meditation retreat; 55% reported that Dr. Wallace
remained one of their primary meditation teachers; and 60%
directly identified shamatha meditation or mindfulness of
breathing as one of their primary meditation practices.
Retreat 1 training participants were tested at the beginning
(preassessment), middle (midassessment), and end
(postassessment) of retreat 1. Wait-list control participants
were assessed at the beginning, middle, and end of both med-
itation retreats, first serving as control participants for retreat
1, then as active training participants for retreat 2. Finally,
participants in both groups were tested at each of the three
follow-up assessments (6-month, 1.5-year, and 7-year). See
Table 1for an overview of the assessment schedule and RIT
task parameters.
At each assessment, participants completed an initial dis-
crimination threshold procedure followed by the 32-min con-
tinuous RIT.
Participants responded to commonly occurring
non-target (long line) stimuli while withholding behavioral
responses to rare target (short line) stimuli. All procedures
were approved by the institutional review board of the
University of California, Davis, and all participants gave full
informed consent.
Threshold The discrimination threshold procedure (~ 10 min)
was designed to equate task demand across participants and to
calibrate individual task difficulty (see MacLean et al. 2009).
Participants maintained fixation on a small dot at the center of
the screen while single gray vertical lines appeared one at a
time against a black background. Each line stimulus was pre-
sented for 150 ms. Avisual mask pattern was presented before
and after the line stimulus for 100 ms. The mask was com-
prised of small lines (0.07° wide and 0.28° to 0.45° long)
positioned throughout a 5.0°× 1.0° space surrounding the fix-
ation point. The mask pattern varied randomly on each trial
and was not presented concurrently with line stimulus presen-
tation. The inter-stimulus interval varied randomly but was
The full RIT was administered at all assessments, excluding the 2-year fol-
low-up assessment for retreat 1 training participants (see Table 1and BFollow-
up Assessments^section in Method).
Table 1 Task parameters and descriptive statistics for RIT-dependent measures
Measure Training Follow-up
Pre Mid Post 6-Month 1.5-Year 7-Year
R1 Training group
N30 30 30 28 22 21
Age 50.25 (12.6) 50.34 (12.6) 50.44 (12.6) 50.35 (12.5) 50.69 (11.9) 56.19 (12.2)
Re-parameterized Yes Yes Yes Yes Yes Yes
Discrimination 3.77 (.39) 4.11 (.18) 4.14 (.27) 3.89 (.23) 4.10 (.44) 3.90 (.55)
Accuracy (A) 0.80 (.05) 0.88 (.06) 0.88 (.06) 0.88 (.07) 0.90 (.07)
RTCV 0.25 (.07) 0.24 (.06) 0.24 (.06) 0.26 (.06) 0.26 (.06)
R2 Training group
N29 29 29 27 22 23
Age 47.51 (15.5) 47.60 (15.5) 47.70 (15.5) 48.46 (14.9) 51.38 (14.9) 54.79 (15.4)
Re-parameterized Yes No No No No Yes
Discrimination 4.03 (.31) 4.08 (.22) 4.11 (.23) 4.15 (.24) 4.11 (.28) 3.96 (.43)
Accuracy (A) 0.88 (.05) 0.91 (.05) 0.92 (.05) 0.91 (.05) 0.92 (.05) 0.89 (.07)
RTCV 0.26 (.08) 0.22 (.06) 0.20 (.07) 0.25 (.06) 0.26 (.06) 0.27 (.07)
Note: means and standard deviations (in parentheses) are provided for participant age and RIT performance measures. The number (N) and mean age of
participants with complete data at each assessment are indicated for each group. Re-parameterized indicates whether the RIT target was pre-set (No) or
re-thresholded (Yes) at a given assessment. Discrimination is the achieved mean visual angle of the PEST procedure. Accuracy (perceptual sensitivity, A)
and RTCV (reaction time coefficient of variation) are computed across the full 32-min RIT
262 J Cogn Enhanc (2018) 2:259275
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constrained to a mean of 1850 ms and a range (rectangular
distribution) of 15502150 ms. Participants were asked to
respond as quickly and accurately as possible with the left
mouse button (right index finger) to frequent long lines
(70% of stimuli) and to withhold responses to rare short lines
(30% of stimuli). Sound feedback was provided for correct
and incorrect responses.
The length of the short-line target was adjusted according
to parameter estimation through sequential testing (PEST;
Taylor and Creelman 1967). This procedure was used to es-
tablish the target line length that can be correctly discriminated
at a pre-determined accuracy rate for a given participant,
which defined an individualsdiscrimination threshold in
units of visual angle. A larger threshold value indicates a lon-
ger short-line target, and thus better discrimination. PEST ac-
curacy was set to 85% at the retreat 1 preassessment; at all
other assessments, accuracy was set at 75%. This change in
procedure was implemented to ensure high task demand for
the remainder of assessments, after we failed to observe reli-
able vigilance decrements at 85% difficulty (Sahdra et al.
RIT Participants completed the 32-min RIT immediately fol-
lowing the PEST threshold procedure (960 trials in total).
Stimulus and response parameters were identical to the thresh-
old procedure except that (1) the length of the target line
remained constant throughout the task, (2) targets occurred
less frequently (10% of all stimuli totaling 96 target lines),
and (3) sound feedback was not present.
For each group and assessment, the short-line target was
individually determined based on a participants PEST dis-
crimination threshold using one of two target-setting manipu-
lations: either (1) difficulty was adjusted by re-parameterizing
the target stimulus to a participants current PEST discrimina-
tion threshold, or (2) difficulty was pre-set to a participants
previously measured discrimination threshold. When re-pa-
rameterized, the RIT target length was determined from the
PEST immediately preceding the RIT at that same assessment
point. This manipulation of target length across assessments
was informed by our observation (described in MacLean et al.
2010) that systematic improvements in discrimination thresh-
olds may have limited our ability to observe training-related
performance improvements in performance accuracy.
Response inhibition accuracy was quantified using the
non-parametric index of perceptual sensitivity, A(Zhang and
Mueller 2005). Hits were defined as correct inhibitions to
targets and false alarms as incorrect inhibitions to non-targets.
Aranges from 0 to 1, with 0.5 indicating chance performance
and 1 perfect performance. To compare accuracy from retreat
1 preassessment (set at 85% threshold level) to all remaining
assessments (set at 75% threshold level), levels of Aat the
initial assessment were adjusted to estimate performance at
75% [adjusted A= (original A× .75) / .85], an approach
consistent with the methods of our prior report (Sahdra et al.
2011). Reaction time variability was quantified as the reaction
time coefficient of variability (RTCV = standard deviation RT
/ mean RT) for non-target trials (864 trials), where lower
RTCV values indicate lower reaction time variability. For each
participant, perceptual sensitivity (A) and RTCV were calcu-
lated for the overall task and for each of eight 4-min contigu-
ous trial blocks (120 trials per block).
Training Assessments Retreat assessments were conducted in
darkened, sound-attenuated testing chambers located in the
dormitory where participants resided and practiced medita-
tion. Stimuli were delivered on an LCD monitor (Viewsonic
VX-922) while participants maintained a viewing distance of
57 cm from the screen. In retreat 1, the target stimulus was re-
parameterized at each assessment; in retreat 2, the target was
pre-set to each individuals retreat 2 preassessment PEST
threshold. Thus, target length was not re-parameterized at
the retreat 2 mid- or postassessments, but was instead held
constant to equate stimulus parameters across the second
Follow-up Assessments Each participant was provided a 14′′
IBM T-40 ThinkPad laptop, with detailed instructions for as-
sembling an in-home testing environment, setting dim ambi-
ent lighting, and maintaining a viewing distance of 57 cm. For
retreat 1 training participants, target length was again re-
parameterized at the 6-month and 7-year follow-up assess-
ments; these participants did not complete the RIT at the 1.5-
year follow-up assessment, instead completing only the
threshold procedure (see Table 1). For retreat 2 participants,
target length was again pre-set to each individualsretreat2
preassessment threshold for the 6-month and 1.5-year follow-
up assessments; at the 7-year assessment, however, target
length was re-parameterized. The decision to re-parameterize
the target length for both participant groupsat the final follow-
up was based on the supposition that visual acuity or executive
function may have changed substantially since the retreat 2
preassessment, thus making participantsprevious target line
length inordinately challenging.
For follow-up assessments
where targets were pre-set, stimuli sizes were scaled to main-
tain the same visual angle for both laptop and laboratory ver-
sions of the task.
Multi-level models implemented with SAS PROC MIXED
version 9.4 were used to analyze longitudinal changes in dis-
crimination, accuracy (perceptual sensitivity, A), and RTCV.
Target length at the 7-year assessment did not significantly differ from the
pre-set threshold used at all other assessments for retreat 2 participants, t(22) =
0.45, p=.658.
JCognEnhanc(2018)2:259275 263
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Significance of random effects was evaluated using log-
likelihood tests of change in model fit (2ΔLL), estimated
using restricted maximum likelihood. Reported models were
estimated using full maximum likelihood, and fixed effects
were evaluated using Satterthwaite approximated degrees of
freedom (reported to the nearest integer).
Growth curve models describe the mean trajectory of
change in terms of an intercept (i.e., starting point) and slope
(i.e., rate of change), with random effects representing
between-person variability in these parameters (Ferrer and
McArdle 2010; Hoffman 2015). Retreat measurements were
spaced at equal intervals, whereas the timing of follow-up
assessments varied both within and between individuals. To
characterize change during retreat, we modeled a slope across
fixed training assessments (pre- = 0, mid- = 1, and
postassessment = 2), with a statistically significant slope indi-
cating group-level change. To characterize change across fol-
low-up, we modeled a slope over years since retreat (YSR;
scaled in years), where YSR reflects the yearly change in
performance since end of retreat (postassessment = 0 years).
A statistically significant YSR slope indicates group-level
change (e.g., improvement or decline) across follow-up as-
sessments. For models including both retreat and follow-up
assessments, these parameters were included as piecewise
slopes representing separable components of change attribut-
able to training and YSR respectively (Hoffman 2015).
Random effects were included when significant to allow
for individual differences in the intercept, or slope of perfor-
mance across blocks, training, or YSR. The effect of block
(block 1 = 0) represents the linear rate of change (magnitude
of the vigilance decrement) across the eight 4-min segments of
the RIT. Age was centered such that 0 indicates a participant
who was 65 years old at the end of training (age at
postassessment=65 years). When included in models with
follow-up assessments, the effect of age represents between-
person effects of participant age, whereas YSR reflects within-
person change across years of follow-up (Hoffman 2015).
Visual inspection of age trends suggested quadratic trajecto-
ries in performance as participants aged. Quadratic effects are
reported where significant.
Summary statistics for perceptual discrimination, accuracy
(perceptual sensitivity, A), and reaction time variability across
all assessments are reported in Table 1.
Longitudinal Training and Maintenance in Retreat 1
We first analyzed longitudinal change across training (pre-,
mid-, and postassessment) and years of follow-up (6 month,
1.5 year, 7 year) for retreat 1 training participants. For each
measure, we fit an initial model describing change across
block, retreat, and YSR (reported in Table 2). For accuracy
and RTCV, we then examined interactions between block and
training, and block and YSR. Finally, we examined age as a
predictor of performance. Figure 1depicts mean Aand RTCV
for the retreat 1 training group across RIT blocks at each
assessment. Figure 2depicts observed changes in discrimina-
tion, A, and RTCV across YSR for each individual, with the
intercept indicating performance at postassessment (YSR = 0)
and the trajectory representing performance over YSR.
Discrimination The inclusion of a random slope for YSR (
2ΔLL(3) = 21.9, p< .001) significantly improved model fit.
There were significant linear, β= 0.545, p< .001, and qua-
dratic, β=0.201, p< .001, trajectories across retreat, but
no significant linear yearly change over YSR, β=0.019,
p= .184 (see Fig. 2a). Training participantsdiscrimination
threshold was estimated to increase (p< .001) by .344° of
visual angle from pre- to midassessment. This rate then
slowed over time such that participants increased (p<.001)
a total of .286° of visual angle from pre- to postassessment.
Finally, we included age as a model predictor. Age did not
significantly predict discrimination, β=0.0013, p= .689,
and there were no higher-order interactions of age with train-
ing or YSR.
Accuracy The inclusion of random slopes for block (
2ΔLL(2) = 20.8, p< .001), training (2ΔLL(3) = 34.8,
p<.001),YSR (2ΔLL(4) = 112.7, p< .001), and quadratic
training (2ΔLL(5) = 39.4, p< .001) significantly improved
model fit. We observed a significant vigilance decrement (i.e.,
effect of block) with an estimated decline (p<.001)of.0084
units of Aat each RIT block. Random effects confidence in-
tervals (CI) suggested that 95% of participants showed a dec-
rement between .017 and .0004 units of Afor each block. In
addition, we observed significant linear, β=0.126, p<.001,
and quadratic, β=0.045, p< .001, slopes across training
assessments, indicating significant increases in accuracy over
retreat. Compared to preassessment, participants increased
(p< .001) an estimated total of .081 units of Aby
midassessment, and an estimated total (p< .001) of .071 units
by postassessment.
There were, however, no significant linear changes in A
across YSR, β= 0.004, p= .119, 95% CI [.0012, .0097]
(see Fig. 2b). This non-significant change across YSR offers
no affirmative statistical evidence in support of maintenance.
We therefore further evaluated the estimated change across
YSR using TOST equivalence procedures (Lakens 2017).
Specifically, we examined the years for which the total accu-
mulated change was significantly smaller than a minimally
meaningful effect, defined as half the total increase in accura-
cy over retreat (Δ
=0.035, Δ
= 0.035). The accumulated
change across follow-up was practically equivalent to zero
264 J Cogn Enhanc (2018) 2:259275
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from the end of retreat to at least year 4, after which the 90%
CI of the remaining yearsestimates overlapped with the up-
per equivalence bound (see Fig. 3). Maintenance over years 5
to 7 was thus statistically undetermined.
We next examined whether the within-task performance
decrement changed across retreat assessments or YSR.
There was no significant interaction between block and linear,
β=0.004, p= .390, or quadratic training, β= 0.002,
p= .439, suggesting that the vigilance decrement was unaf-
fected by training in retreat 1. The effect of block, however,
was significantly attenuated across YSR, β= 0.0007,
p= .037. Finally, we examined the effects of aging on re-
sponse inhibition accuracy. Age did not significantly predict
A,β=0.0003, p= .611, and there were no higher-order inter-
actions between age, block, training, and YSR.
Reaction Time Variability Random slopes for block (
2ΔLL(2) = 42.9, p< .001), training (2ΔLL(3) = 53.4,
p<.001),linearYSR(2ΔLL(4) = 54.6, p< .001), and qua-
dratic YSR (2ΔLL(5) = 64.6, p< .001) all significantly im-
proved model fit. We observed a significant linear effect of
block, indicating an average increase (p< .001) of .006 units
of RTCV per block. Random effects CI suggested that 95% of
participants showed a per-block change in RTCV between
.005 and .017 units. We also observed a significant linear
effect of training, β=0.013, p= .003, indicating significant
Table 2 Growth models of
longitudinal training and
maintenance in retreat 1 training
Model effects Parameter estimate (SE)
Discrimination Accuracy RTCV
Fixed effects
Intercept 3.766 (.056)** 0.829 (.008)** 0.233 (.011)**
Linear block 0.008 (.001)** 0.006 (.001)**
Linear training 0.545 (.115)** 0.126 (.017)** 0.0125 (.004)**
Quadratic training
0.201 (.053)** 0.045 (.008)**
Linear YSR 0.019 (.014) 0.004 (.003) 0.056 (.018)**
Quadratic YSR
0.007 (.003)**
Random effects
Intercept variance 0.032 (.013)** 0.001 (.001)** 0.003 (.001)**
Block variance 0.00002 (.00001)* 0.00003 (.00001)**
Training variance 0.006 (.002)** 0.0003 (.0001)*
YSR variance 0.002 (.001)* 0.0001 (.0001)** 0.007 (.003)**
variance 0.002 (.001)**
variance 0.0001 (.0001)**
Intercept-block covariance 0.0001 (.0001)* 0.0001 (.0001)
Intercept-training covariance 0.0003 (.0008) 0.0006 (.0003)
Intercept-YSR covariance 0.005 (.003) 0.00002 (.0001) 0.002 (.001)
covariance 0.00005 (.0004)
covariance 0.0002 (.0002)
Block-training covariance 0.0002 (.0001) 0.0000004 (.00003)
Block-YSR covariance 0.00002 (.00002) 0.0002 (.0001)
covariance 0.0001 (.0001)*
covariance 0.00002 (.00002)
Training-YSR covariance 0.0001 (.0002) 0.0008 (.001)
covariance 0.003 (.001)*
covariance 0.0001 (.0001)
covariance 0.00004 (.0001)
covariance 0.001 (.0004)**
Residual variance 0.062 (.008)** 0.004 (.0002)** 0.002 (.0001)**
Fit statistics
2 Log-likelihood 69.5 2831.4 3522.6
Note: maximum likelihood estimates are reported for piecewise longitudinal analyses of RIT measures across
retreat and years since retreat (YSR). Standard errors are reported in parentheses
denotes a quadratic parameter
*p< .05; **p<.01
JCognEnhanc(2018)2:259275 265
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reductions in RTCV. Ninety-five percent of individuals had a
slope between 0.044 and .019 units of RTCV across retreat
assessments. Finally, we observed significant linear, β=
0.056, p= .006, and quadratic, β=0.007, p= .008, slopes
across YSR (see Fig. 2c), indicating that participants lost the
benefits of training in the years following retreat, but that this
rate of loss slowed and then reversed over time. One year after
postassessment (YSR = 1), participants were estimated to
have increased (p= .005) .048units of RTCV, whereas 7 years
later, the estimated total increase (p= .031) was .031 units.
No significant interaction between block and training,
β= 0.0012, p=.202,wasobservedwhenincludedinthe
model. There were significant interactions between block
and both the linear, β=0.009, p= .001, and quadratic,
β= 0.0012, p= .001, YSR trends, however, indicating that
the within-task increase in RTCV was significantly re-
duced in the years following training. Finally, age did
not significantly predict RTCV, β=0.0004, p= .556, in
retreat 1 participants. There were no higher-order interac-
tions between age, block, training, or YSR.
Fig. 1 Mean performance trajectories for accuracy (A) and reaction time variability (RTCV) across the eight contiguous 4-min blocks of the RIT. Retreat
1 and retreat 2 training participants are shown across training (black) and follow-up (red) assessments
266 J Cogn Enhanc (2018) 2:259275
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Summary Significant increases in accuracy were observed
across retreat 1 training assessments, which were then defini-
tively maintained for at least 4 years following retreat.
Improvements (i.e., reductions) in reaction time variability
were also observed across retreat, but were lost over the course
of follow-up. Interestingly, within-task decrements in perfor-
mance accuracy and RTCV were attenuated across years of
follow-up, but not during retreat, suggesting possible benefits
of long-term continued practice. No significant effects of ag-
ing were observed.
Fig. 2 Observed individual performance trajectories for discrimination
threshold (in units of visual angle), accuracy (perceptual sensitivity, A),
and reaction time variability (RTCV) across years since retreat (YSR).
The intercept represents performance at retreat postassessment (YSR = 0)
and the model-estimated group trajectory is indicated in red
JCognEnhanc(2018)2:259275 267
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Longitudinal Training and Maintenance in Retreat 2
We next examined longitudinal change across blocks, training,
and YSR in retreat 2 training participants. Parameter estimates
arereportedinTable3,andFig.1depicts mean Aand RTCV
across blocks at each assessment. In retreat 2, the RIT target was
pre-set to each participants preassessment discrimination thresh-
old for all remaining assessments, excluding the 7-year follow up
assessment, for which target length was re-parameterized (see
Tab le 1).
Discrimination Model fit was significantly improved by inclu-
sion of a random slope for YSR (2ΔLL(3) = 31.8, p<.001)
only. We observed a significant linear increase in discrimina-
tion across training, β= 0.060, p= .002, and a significant
yearly decrease over YSR, β=0.027, p= .029 (see Fig.
2d), suggesting training-related improvements in discrimina-
tion capacity that were then lost over years of follow-up. There
were no significant effects of age on discrimination threshold,
β=0.004, p=.101.
Accuracy Inclusion of random slopes for block (2ΔLL(2) =
23.9, p<.001), and YSR (2ΔLL(4) = 139.5, p<.001), sig-
nificantly improved model fit; the random effect of training (
2ΔLL(3) = 5.1, p= 0.139), however, did not improve fit, sug-
gesting minimal influence of individual differences on change
in accuracy across training. The fixed effect of block was
significant, β=0.008, p< .001, indicating an average per-
block reduction of .008 units of A. The random effects CI
suggested that 95% of participants had a vigilance decrement
between .016 and .0005 units of A. In addition, we ob-
served significant linear, β=0.045, p< .001, and quadratic,
β=0.012, p=.012, trends across training, such that partic-
ipants improved in accuracy during retreat, but that the rate of
improvement slowed across assessments. Compared to
preassessment, participants increased (p< .001) an estimated
total of .033 units of Aby midassessment, and an estimated
total (p< .001) of .043 units by postassessment.
Although no overall significant yearly changes in Awere
observed following retreat, β=0.004, p=.128, 95% CI[
0.0094, 0.0013] (see Fig. 2e), we observed significant indi-
vidual differences in rates of yearly change: 95% of individ-
uals demonstrated changes ranging from 0.028 to .020 units
of Aper each year of follow-up. To formally evaluate mainte-
nance, TOST equivalence procedures were used to examine
the years for which the total accumulated change in accuracy
over YSR was significantly smaller than half the total increase
accrued over retreat (Δ
=0.022, Δ
= 0.022).
Accumulated change was equivalent to zero until at least the
second year following retreat, after which maintenance was
statistically undetermined (see Fig. 3).
We next investigated whether within-task decrements in A
changed across retreat assessments or YSR. There was a sig-
nificant interaction between block and the linear effect of
training, β=0.0022, p= .030, suggesting that the magnitude
of the vigilance decrement was attenuated across training.
Specifically, the performance decrement over blocks (β=
0.008) was estimated to diminish by.002 units at each assess-
ment. The interaction between block and the quadratic effect
of training was not significant, β= 0.0009, p=.644,andthere
was no change in the vigilance decrement over YSR, β=
0.0006, p=.118,95% CI [0.0013, 0.00015]. These patterns
suggest that meditation training improved performance and
moderated the vigilance decrement, and that these benefits
did not change over years of the follow-up.
Finally, we examined age as a predictor of response inhi-
bition accuracy. There was a significant main effect of age on
A,β= 0.0007, p= .048. We next explored interactions be-
tween age and other model effects. Age was unrelated to block
Fig. 3 Model estimated change in accuracy (perceptual sensitivity, A)
based on the linear slope across years since retreat (YSR) for aretreat 1
and bretreat 2.Ninety and 95% confidence intervals are displayed around
each yearly estimate with a thick line and thin line respectively.
Horizontal black dotted lines indicate the lower (Δ
) and upper (Δ
equivalence bounds for a meaningful effect, defined as half the total
increase in accuracy accrued during training for retreat 1 (Δ
= 0.035) and retreat 2 (Δ
=0.022, Δ
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or to the rate of improvement across training, but was a sig-
nificant moderator of change after retreat, β=.0004,
p= .026. Specifically, older participants declined at a greater
rate across years of follow-up than did younger participants.
Moreover, although retreat 2 participants retained training im-
provements across the follow-up on average, yearly losses
were estimated to occur specifically in older (i.e., age = 65)
participants, β=0.009, p= .036. Figure 4adepicts
Table 3 Growth models of
longitudinal training and
maintenance in retreat 2 training
Model effects Parameter estimate (SE)
Discrimination Accuracy RTCV
Fixed effects
Intercept 4.023 (.045)** 0.900 (.007)** 0.248 (.013)**
Block 0.008 (.001)** 0.004 (.001)**
Linear training 0.060 (.019)** 0.045 (.010)** 0.067 (.011)**
Quadratic training
0.012 (.005)* 0.019 (.005)**
Linear YSR 0.027 (.012)* 0.004 (.003) 0.045 (.009)**
Quadratic YSR
0.006 (.001)**
Random effects
Intercept variance 0.035 (.011)** 0.001 (.0003)** 0.004 (.001)**
Block variance 0.00002 (.00001)*
Training variance 0.0006 (.0002)**
YSR variance 0.002 (.001)** 0.0002 (.0001)** 0.002 (.001)**
variance 0.00004 (.00001)**
Intercept-block covariance 0.0001 (.00004)**
Intercept-training covariance 0.001 (.0004)*
Intercept-YSR covariance 0.0008 (.002) 0.0002 (.0001) 0.0001 (.001)
covariance 0.00003 (.0001)
Block-YSR covariance 0.00001 (.00001)
Training-YSR covariance 0.0004 (.0003)
covariance 0.00005 (.00004)
covariance 0.0002 (.0001)**
Residual variance 0.027 (.004)** 0.004 (.0002)** 0.003 (.0001)**
Fit statistics
2 Log-likelihood 29.6 3403.4 3473.5
Note: maximum likelihood estimates are reported for piecewise longitudinal analyses of RIT measures across
retreat and years since retreat (YSR). Standard errors are reported in parentheses
denotes a quadratic parameter
*p< .05; **p<.01
Fig. 4 Observed individual
performance trajectories for
accuracy (A) and reaction time
variability (RTCV) as a function
of age for retreat 2 follow-up
assessments. The model-
estimated aging slope of best fit is
indicated in red
JCognEnhanc(2018)2:259275 269
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individual subject trajectories of Aat each follow-up assess-
ment as a function of age.
Reaction Time Variability Random effects for the linear slope
of training (2ΔLL(3) = 55.2, p< .001), and both linear (
2ΔLL(4) = 78.5, p< .001) and quadratic slopes of YSR (
2ΔLL(6) = 50.5, p< .001), significantly improved model fit.
We observed a significant within-task increase of .004 RTCV
units across blocks, β=0.004,p< .001. There were also sig-
nificant linear, β=0.067, p< .001, and quadratic, β=0.019,
p< .001, decreases in RTCV across retreat assessments. The
quadratic trend indicates that RTCV was reduced across train-
ing, but that the rate of decrease slowed across assessments. At
midassessment, participants showed an estimated .048
(p< .001) unit reduction in RTCV compared to
preassessment, while the estimated reduction (p< .001) from
pre- to postassessment was .058 units. Significant linear,
β= 0.045, p< .001, and quadratic, β=0.006, p< .001,
trends in YSR (see Fig. 2f) were also observed. Although
participants gradually lost the benefits of training over fol-
low-up, the rate of loss slowed over time: 1 year after
postassessment, participants showed an estimated increase
(p< .001) of .039 units of RTCV, whereas 7 years later the
estimated increase (p= .025) was .044 units.
We observed no significant interactions between block and
any other linear or quadratic trajectories, indicating that the
per-block increase in RTCV was unaffected by training or
YSR. Finally, although there was no significant linear effect
of age, β=0.003,p= .145, we observed a significant quadrat-
ic, β=0.00012,p= .026, effect of age on RTCV. The relation-
ship between RTCVand age was -shaped, such that RTCV
was reduced in middle age and increased in older age.
Figure 4b depicts individual subject trajectories of RTCV at
each follow-up assessment as a function of age.
Summary Training participants demonstrated overall im-
provements in discrimination and performance accuracy dur-
ing retreat 2, and significant attenuation of the vigilance dec-
rement. No statistically significant changes in overall accuracy
and vigilance were observed over years of follow-up, with
equivalence testing suggesting that changes in accuracy were
maintained below half the level of total retreat gains for ap-
proximately 2 years. However, when pooled across both re-
treats, total change in accuracy across YSR was closer to zero,
such that the weighted estimate (β= 0.0004, 90% CI [
0.021,0.021]) remained within the equivalence bounds up to
7 years following retreat. Thus, the true degree of maintenance
was likely underestimated across individual retreats. As in
retreat 1, RTCV was reduced during training in retreat 2, but
improvements were then lost following retreat. Age was a
significant predictor of RTCV, and interacted with rate of
change over YSR such that losses in performance accuracy
were estimated to occur specifically in older participants.
Meditation Practice Moderates Age-Related Decline
in Performance
In a final set of analyses, we examined whether the observed
age-related declines in performance among retreat 2 partici-
pants were moderated by meditation practice across the
follow-up period. Estimates of continued practice (M=
2834.2 h, range = 40611,900) and intensive retreat participa-
tion (M= 176.7 days on retreat, range = 01460) were avail-
able for 19 participants. These variables were entered sepa-
rately into models for Aand RTCV across YSR, after remov-
ing participants for whom no practice estimates were avail-
able. Hours of practice were rescaled to aid interpretation of
model parameters (1 unit represents 100 h).
We first included estimates of continued practice (in hours)
over follow-up as a predictor of performance accuracy.
Parameter estimates from this model are reported in Table 4.
We observed a significant interaction between hours and YSR,
β= 0.001, p= .029, and a significant three-way interaction
between age, hours, and YSR, β= 0.00004, p= .018.
Figure 5depicts model-estimated simple slopes across YSR
Table 4 Effects of aging and practice hours across follow-up on retreat
2 performance accuracy
Model effects Parameter estimate (SE)
Fixed effects
Intercept 0.999 (.047)**
Linear block 0.010 (.002)**
Linear YSR 0.033 (.011)*
Age 0.002 (.002)
Hours of practice 0.003 (.002)
Age-YSR interaction 0.001 (.0004)*
Age-hours interaction 0.0001 (.0001)
YSR-hours interaction 0.001 (.001)*
YSR-age-hours interaction 0.00004 (.00002)*
Random effects
Intercept variance 0.001 (.001)
Block variance 0.00003 (.00002)
YSR variance 0.0001 (.00004)*
Intercept-block covariance 0.0002 (.0001)
Intercept-YSR covariance 0.0003 (.0001)
Block-YSR covariance 0.00002 (.00002)
Residual variance 0.004 (.0003)**
Fit statistics
2 Log-likelihood 1014.5
Note: maximum likelihood estimates are reported for RIT accuracy (A)
across years since retreat (YSR) in retreat 2 training (n= 19) participants.
Age is centered to postassessment and 65 years. Hours of practice are
scaled to 100 h per unit. Standard errors are reported in parentheses
*p<.05; **p<.01
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at low (1250 h), medium (2000 h), and high (2750 h) values of
continued practice for middle-aged (45 years) and older indi-
viduals (65 years). As can be seen in Fig. 5, older individuals
who engaged in a relativelysmaller amount of continued prac-
tice over YSR were predicted to experience greater losses of
training-related benefits in A. Middle-aged individuals did not
experience training losses over YSR, irrespective of their con-
tinued practice acrossthis interval. For older individuals, how-
ever, there was a marginally significant slope across YSR at
lower practice estimates (1250 h), β=0.052, p= .099, that
reached statistical significance at approximately 750 h of es-
timated practice.
We next examined whether continued practice moderat-
ed the effects of aging on RTCV (see Table 5for
parameter estimates). We observed significant linear, β=
0.017, p< .001, and quadratic, β=0.0004, p< .001, trends
across age, a significant effect of total practice hours, β=
0.008, p< .001, and a significant interaction between
hours and the linear, β=0.0004, p=.004, and quadratic
age parameters, β=.000007, p= .019, for RTCV. Thus,
in contrast to performance accuracy, continued meditation
practice appeared to directly moderate age-related declines
in reaction time variability. Figure 6illustrates model-
estimated simple slopes for low (1250 h), medium
(2000 h), and high (2750 h) values of practice across
continuous age. As shown in Fig. 6, individuals who en-
gaged in relatively fewer hours of practice over YSR dem-
onstrated greater age-related impairments in RTCV.
Finally, intensive retreat practice (in days) over the follow-
up period was examined as a predictor of Aand RTCV.
Although there were no significant effects on performance
accuracy, more reported days on retreat over follow-up was
a marginally significant predictor of lower overall RTCV, β=
.00007, p= .058. There were no significant interactions.
The present study represents the most extensive longitudinal
examination of meditation training-related improvements in
sustained attention to date. Using a sustained response inhibi-
tion task, performance was examined across six assessment
waves over more than a 7-year training and follow-up interval.
Table 5 Effects of aging and practice hours across follow-up on retreat
Model effects Parameter estimate (SE)
Fixed effects
Intercept 0.401 (.029)**
Linear block 0.004 (.002)**
Linear YSR 0.003 (.003)
Linear age 0.017 (.003)**
Quadratic age
0.0004 (.0001)**
Hours of practice 0.008 (.001)**
Age-hours interaction 0.0004 (.0001)**
-hours interaction 0.000007 (.000003)*
Random effects
Intercept variance 0.003 (.001)**
YSR variance 0.0001 (.0001)**
Intercept-YSR covariance 0.0006 (.0003)*
Residual variance 0.005 (.0003)**
Fit statistics
2 Log-likelihood 1004.6
Note: maximum likelihood estimates are reported for RIT RTCV across
years since retreat (YSR) in retreat 2 training (n= 19) participants. Age is
centered to postassessment and 65 years. Hours of practice are scaled to
100 h per unit. Standard errors are reported in parentheses
denotes a quadratic parameter
*p<.05; **p<.01
Fig. 5 Model estimates of linear change in accuracy (A) across years
since retreat for retreat 2 training participants at low (1250 h), medium
(2000 h), and high (2750 h) levels of practice hours for middle-aged
(45 years) and older individuals (65 years)
Fig. 6 Model estimates of reaction time variability (RTCV)atlow
(1250 h), medium (2000 h), and high (2750 h) levels of practice hours
as a function of age for retreat 2 training group participants
JCognEnhanc(2018)2:259275 271
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We observed robust improvements in perceptual discrimina-
tion, response inhibition, vigilance, and RTCV across medita-
tion retreat assessments, and extended our prior investigation
(Sahdra et al. 2011) to examine the long-term maintenance of
training-related improvements. We observed no significant
changes in response inhibition accuracy across the 7-year fol-
low-up interval, and improvements were maintained above
half the level of overall training gains for several years follow-
ing the end of retreat. Furthermore, aging-related performance
deficits were moderated by continued meditation practice:
older participants who reported engaging in more meditation
practice following formal training demonstrated attenuated
aging-related performance deficits.
Our previous report (Sahdra et al. 2011) detailed relations
between increases in performance accuracy on retreat and
growth in self-reported adaptive psychological functioning. In
the present study, we incorporated reaction time variability as
an additional outcome of training, reporting significant reduc-
tions in RTCVacross both intensive retreat interventions. These
findings appear to generalize to other training styles and pe-
riods of intensive training (i.e., 1-month training; Zanesco et al.
2013), and provide additional support to the growing body of
evidence that meditation training influences the stability of
goal-directed attention. Increased stability of attention is a cen-
tral organizing feature of the benefits of many meditation train-
ing regimens (Lutz et al. 2015). Measures of attentional stabil-
ity, including reaction time variability, therefore hold promise
for informing emerging models of the distinctive phenomeno-
logical qualities and neurocognitive processes that characterize
meditation-related development of cognitive capacities.
Attempts to sustain attention over time can impose system-
wide cognitive consequences on processes underlying perfor-
mance on tasks like the RIT, including discrimination of percep-
tually challenging stimuli, inhibition of competing response ten-
dencies, and maintenance of attention in an ongoing and stable
manner. Consistent with theories of resource depletion (Langner
and Eickhoff 2013), our findings support the well-characterized
decline in perceptual sensitivity (i.e., performance accuracy) ob-
served in tasks of sustained attention, and further suggest that
increases in reaction time variability across task duration are a
measurable behavioral consequence of sustaining attention
(Wang et al. 2014; Zanesco et al. 2013). This increased variabil-
ity may reflect graded variation in participantsability to main-
tain attention and regulate behavior over time, or increases in the
frequency or disruptiveness of task-unrelated thought (Seli et al.
2013). Importantly, however, training was associated with atten-
uated within-task performance decrements for accuracy only.
Data characterizing the long-term maintenance of
meditation-related improvements are critical for understand-
ing the generalized benefits of contemplative or mindfulness-
based approaches to cognitive training. We employed growth
curve models to examine separable sources of change across
an extensive longitudinal duration: changes over the course of
retreat, changes over years since retreat, and changes associ-
ated with aging. Using this approach, we observed distinct
patterns of maintenance across dependent measures. No sig-
nificant changes in response inhibition accuracy were ob-
served over the 7-year follow-up period for either retreat in-
tervention. Moreover, equivalence tests supported the asser-
tion that performance accuracy was definitively maintained
for several years following retreat; the accumulated change
in accuracy was significantly smaller than any meaningful
amount (or half the total improvement accrued during retreat)
up to 5 years later, demonstrating the durability of training
effects well beyond the intervention itself.
The vigilance decrement and the within-task increase in
RTCV were attenuated across years of follow-up for retreat
1, whereas we observed no significant changes in vigilance
across follow-up for retreat 2. Improvements in perceptual
discrimination, however, were lost at a gradual rate over years
of follow-up, while improvements in RTCV observed in both
retreats were lost shortly following the end of training. It is
possible that measures of accuracy and vigilance reflect com-
ponents of sustained attention that are more robust to long-
term maintenance than reaction time variability. Once im-
proved through training, cognitive capacities relating to the
global control of attention, target detection, stimulus process-
ing, and response execution may endure to a greater degree
than those supporting reductions in ongoing attentional and
behavioral fluctuations. It is also presently unclear how factors
relating to the training intervention itself, such as individual
differences in duration and intensity of practice during the
retreat, may have supported long-term maintenance. Clearly,
more research is needed to better clarify the relative suscepti-
bility of attentional markers to training interventions.
Growth curve models are characterized by higher levels of
statistical power than more traditional analyses (e.g., mean
comparisons between assessment waves; Muthén and
Curran 1997), and offer analytic advantages when measure-
ment intervals vary between assessments or individuals, or
when individuals lack complete data across measurement oc-
casions. Nevertheless, limited sample variability may have
reduced our ability to detect significant changes in some pa-
rameters over the course of the 7-year follow-up, or to observe
direct associations between maintenance of training improve-
ments and continued meditation practice. For example, it is
possible that additional assessment waves or greater sampling
density may have increased our ability to statistically detect
longitudinal changes in accuracy over the follow-up.
Moreover, our sample was comprised of experienced medita-
tors who all engaged in considerable amounts of ongoing
practice. Future studies should therefore investigate associa-
tions between performance and practice hours using samples
with greater variability in practice times, or with designs that
encourage practitioners to engage in different amounts or
styles of practice after periods of formal training to better
272 J Cogn Enhanc (2018) 2:259275
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explore the association between continued practice and main-
tenance. Finally, procedurally altering the stimulus parameter-
ization at the 7-year follow-up for the retreat 2 group may
have partially confounded longitudinal estimates. However,
while there was a noticeable drop in performance accuracy
between the 1.5- and 7-year assessments, levels of accuracy
at 1.5 years were nearly identical to those at the conclusion of
Consistent with prior research (e.g., Fortenbaugh et al. 2015),
we observed curvilinear age-related deficits in RTCV, such that
reaction time variability improved through middle-age then de-
clined in later life. In contrast, no age-related declines were found
for performance accuracy overall. These findings are in line with
cross-sectional evidence noting a relative lack of negative asso-
ciation between age and cognition in meditation practitioners
(Gard et al. 2014). Indeed, continued meditation practice ap-
peared to moderate aging effects in performance accuracy and
RTCV in our sample. Although older individuals failed to main-
tain training-related accuracy improvements on average, older
practitioners reporting larger amounts of continued practice
maintained improvements over the follow-up. These findings
provide initial, yet provocative, evidence that continued medita-
tion practice may be associated with a moderation of age-related
decline in attentional components known to be sensitive to aging
(Fortenbaugh et al. 2015; MacDonald et al. 2006; Smittenaar
et al. 2015).
Taken together, the procedural differences in threshold pa-
rameterization across our interventions highlight an interest-
ing dichotomy between corrective approaches for ameliorat-
ing aging-related cognitive deficits. One approach is to tailor
demanding tasks to match individualscognitive capabilities,
thereby countering or offsetting losses attributable to age-
related decline; an alternative approach might attempt targeted
improvement of cognitive deficits through cognitive training,
meditation, or related interventions. The present findings offer
tentative evidence that age-related influences on response in-
hibition accuracy and reaction time variability may be buff-
ered through both of these mechanisms, at least among expe-
rienced practitioners: in retreat 1, we observed no age-related
decline in training participants when the resource demands of
the task were adaptively adjusted across assessments to an
individuals performance threshold; in retreat 2when exter-
nal demands were held constantwe observed a typical pat-
tern of age-related decline, which was moderated by levels of
continued meditation practice.
It is possible that other aspects of participantslifestyle or
personality might have contributed to the observed modera-
tion of age-related deficits by continued meditation practice.
Although groups were matched on multiple demographic and
personality factors prior to study onset (see MacLean et al.
2010), our sample presumably differed from the general pop-
ulation on various attributes relevant to ongoing cognitive
health. Indeed, socio-economic status and other lifestyle
factors have long been thought to influence the rate of cogni-
tive decline across the lifespan, motivating researchers to in-
vestigate these factors as potential targets for intervention. Yet
recent work has suggested otherwise (e.g., Early et al. 2013;
Salthouse 2014), in that lifestyle factors may primarily influ-
ence individualsbaseline scores, rather than rates of cognitive
decline. Nevertheless, causation cannot be attributed to the
moderation of aging-related decline with continued medita-
tion practice in our sample. It is therefore critical that more
research is conducted before advocating meditation practice as
an intervention for cognitive aging.
Indirectly, our findings also present a sobering appraisal of
the viability of short-term or non-intensive mindfulness inter-
ventions for improving sustained attention in a lasting manner.
The participants in our sample were experienced practitioners
who engaged in amounts of practice across the 7-year follow-
up far in excess of standardized mindfulness-based interven-
tions (Creswell 2017), which are clearly not feasible for the
wide application of interventions targeting cognitive aging.
Although participants reported engaging in periods of inten-
sive retreat practiceas well as non-intensive daily practice
across the 7-year follow-up interval, systematic group-level
improvements were largely constrained to the targeted 3-
month intervention. These findings support the principle that
continued practice over long-term intervals (even large
amounts of regular practice across 7 yearstime as in our
sample) may not be sufficient to improve sustained attention
in experienced practitioners. Instead, periods of intensive
training, coupled with well-timed assessments, may be neces-
sary to produce and reveal robust and lasting cognitive im-
provements. In contrast to these group-wide patterns, we ob-
served significant individual differences in the rates of change
across the 7-year follow-up, indicating that performance im-
proved over time for some individuals. Future research should
continue to investigate the factors that underlie long-term
maintenance and cognitive change.
In conclusion, the present study suggests that intensive and
continued meditation is associated with enduring improve-
ments in sustained attention, supporting the notion that the
cognitive benefits of dedicated mental training may persist
over the long-term when promoted by a regimen of continued
practice. Although participants did not generally improve over
years of daily meditation practice, continued meditation ap-
pears to benefit practitioners by preserving gains accrued dur-
ing periods of intensive formal training and by altering trajec-
tories of age-related cognitive decline. Continued meditation
practice seems to be associated with substantial experiential
and developmental influences on practitionersattentional ca-
pacities over the lifespan. These findings have broad implica-
tions for meditation and mindfulness-based approaches to
cognitive training and raise important questions regarding
the limits of meditation practice on the plasticity of human
JCognEnhanc(2018)2:259275 273
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
Acknowledgements We thank Jennifer Pokorny, Stephen Aichele, Tonya
Jacobs, David Bridwell, Quinn Conklin, and Sarah Huffman for their help
in collecting a portion of these follow-up data. Major support for original
data collection and follow-up analyses were provided by Fetzer Institute
Grant #2191 and John Templeton Foundation Grant #39970 to C.D.S.,
gifts from the Hershey Family, Baumann, Tan Teo, Yoga Science, and
Mental Insight Foundations, anonymous and other donors all to C.D.S.,
and the Santa Barbara Institute for Consciousness Studies.
Compliance with Ethical Standards
Conflict of Interest The authors declare that they have no conflict of
Open Access This article is distributed under the terms of the Creative
Commons Attribution 4.0 International License (http://, which permits unrestricted use,
distribution, and reproduction in any medium, provided you give appro-
priate credit to the original author(s) and the source, provide a link to the
Creative Commons license, and indicate if changes were made.
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... According to previous studies, long-term meditation practice does have beneficial effects on the aging process [52,53]. For instance, studies on the impact of meditation on cognition in aging have found a positive effect of meditation training on cognitive functions, especially on attention and memory, known to be particularly sensitive to aging [54,55]. In conclusion, in terms of the technical aspect, the present study has once again demonstrated that long-term meditation played an important role in slowing down the aging process. ...
Full-text available
The aging process is always accompanied by a decline in cognitive and emotional functions. Although previous studies have identified the positive effects of different meditative practices on emotional and cognitive functions, few studies have investigated the most primitive Chinese meditation—Shaolin Zen meditation. In particular, data are extremely limited regarding the brain mechanism of the effects of Shaolin Zen meditation on cognitive and emotional functions during aging. The current study aimed to explore the effects of long-term Shaolin Zen meditation practice on event-related potentials (ERPs) during facial emotion recognition in aging. ERPs were recorded from 16 monks with long-term meditation experience and 20 controls without meditation experience. The significant age-related degenerative changes in the early ERP components did not present in the meditators but only in the controls without meditation experience. Additionally, we found no group differences in the late P3 component. These findings suggest that long-term Shaolin Zen meditation practice can counteract the age-related cognitive decline in the “down-top” automatic processing of emotional stimuli.
... First, they were instructed to focus their attention on their breathing by counting the number of breath and restart if distracted. This exercise aimed at training the participant to avoid distractions and redirect their awareness to the present moment in a non-reactive and non-elaborative manner (Bishop et al., 2004;Malinowski, 2013;Lutz et al., 2015;Lymeus et al., 2018;Zanesco et al., 2018). Then, the participant was invited to extend their attentional focus to their environment (sensations, background noises, emotions) by mentally putting a word on what they were noticing (for example "noise" when hearing something). ...
Full-text available
Introduction: Mindfulness meditation (MM) involves and benefits cognitive functioning, especially attention and inhibition processes, which are also implicated in the control of complex motor skills, such as bimanual coordination. Thus, MM practice could potentially enhance bimanual coordination control through its cognitive benefits. Accordingly, in this study, we investigated the acute effects of a brief MM session on bimanual coordination dynamics, attention, and inhibition abilities, as well as the mediation link between MM’s cognitive and motor improvements. Methods: Healthy meditation-naïve (novices, n = 29) and meditation-experienced participants (meditators, n = 26) were randomly assigned to either an active control intervention (attentive listening to a documentary podcast) or a MM intervention (breathing and open monitoring exercise), both lasting 15 min. In the motor domain, pre- and post-tests assessed participants’ ability to intentionally maintain the anti-phase coordination pattern at maximal movement frequency and resist the spontaneous transition to the in-phase pattern. In the cognitive domain, the participants’ attentional, perceptual inhibition and motor inhibition abilities were assessed. Results: Following both interventions, meditators and novices improved the stability of their anti-phase coordination pattern (p = 0.034, ηp2 = 0.10) and their attentional performance (p’s < 0.001, ηp2 > 0.40). Only following the MM intervention, meditators and novices improved their ability to intentionally maintain the anti-phase pattern by delaying or even suppressing the spontaneous transition to in-phase (p’s < 0.05, ηp2 ≥ 0.11), and improved concomitantly their motor inhibition scores (p = 0.011, ηp2 = 0.13). No effects were found on perceptual inhibition. The increase in motor inhibition capacities did not however statistically mediate the observed acute effects of MM on bimanual coordination control. Conclusion: We showed that a single MM session may have acute benefits in the motor domain regardless of the familiarity with MM practice. Although these benefits were concomitant to enhanced attentional and motor inhibition abilities, no formal mediation link could be established between the observed motor and cognitive benefits. This study paves the way for the investigation of the mechanisms underlying MM effects on motor control, as well as longer-term benefits.
... The MM recording consisted in a guided fundamental breathing exercise inspired by fundamental Mindfulness Based Stress Reduction programs. In this type of exercise, attention is focused on the sensation of the breath to avoid distractions and redirect awareness in a nonreactive and non-elaborative manner to the present moment [3,[33][34][35][36]. Participants were asked to listen attentively to the recording and follow, as closely as possible, the given guiding instructions. ...
Full-text available
The present study investigated acute cognitive effects of mindfulness meditation (MM) compared to an active control intervention in meditators (n = 22) and novices (n = 20) using a within-subject design. We analyzed reaction times in a digitized Stroop task at baseline, after a 10-minute MM session with a fundamental breathing exercise, and after a 10-minute attentive listening intervention. Interventions order was randomized and a 10 min delay was respected before testing. Relative to baseline, meditators and novices showed faster reaction times after both interventions, but more so after MM for the congruent and incongruent Stroop task conditions that are associated with attention, inhibition and cognitive flexibility. Although the two interventions showed cognitive effects independent of previous meditation experience, MM appeared to induce larger benefits. Our findings are encouraging and support MM's potential as a means to enhance cognitive performance on the short-term without the need of any previous practice.
... Of particular interest to us in the current work are findings of increased sustained and selective attention [MacLean et al., 2010, Slagter et al., 2007, Lutz et al., 2009, response inhibition [Sahdra et al., 2011], executive control [Zanesco et al., 2013, Shields et al., 2020 and emotional regulation [Rosenberg et al., 2015], but decreased mind-wandering [Zanesco et al., 2016] during and following intensive retreats. Importantly, authors from the Shamatha project found that some of their initial effects (sustained attention and response inhibition) were partially maintained seven years later, and that this maintenance was modulated by the continuity of meditation practice after the retreats [Zanesco et al., 2018]. ...
Full-text available
The idea of meditation as a scientific tool to understand the “embodied mind” was initially suggested by neuroscientist Francisco Varela and his collaborators in a ground-breaking publication in 1991. Thirty years later, a growing amount of scientific evidence confirms that meditation can have beneficial impacts on the body and mind. Despite encouraging physiological and psychological models, a general understanding of the mechanisms at play during meditative practices, grounded in neurosciences, is still lacking. Additionally, the comprehension of human cognition based on the predictive processing theory, and its cerebral implementation, could offer a unifying explanation for processes as diverse as perception, attention, learning, and action. Founded on Bayesian statistics, this theory models the brain as an “inference organ” which simultaneously predicts and constrains, proactively, the sensations the organism receives from both its own body and the outer world, with the main purpose of maintaining itself in a viable state. The primary objective of this PhD was to elucidate, within this theoretical framework, some of the neuronal and computational mechanisms of different meditative practices. Our general hypothesis is that the regulation of attention and emotions by meditation is associated with an adjustment of the brain's predictive processes. The degrees of confidence in the validity of predictions and sensations, among other factors, would be differently altered, leading to more malleable and adaptive cognitive priors. This transformation of the way of approaching mental experience as well as external influences, may explain the proven psychotherapeutic effects of mindfulness meditation to cope with depressive relapse, anxiety, chronic pain or addictions. Keywords: meditation, mindfulness, meditation retreat, embodied cognition, predictive processing, predictive coding, Bayesian inference, perceptual inference, active inference, electroencephalography, event-related potentials, mismatch negativity, Bayesian modeling, computational modeling, pain, pain catastrophization, cognitive defusion
... Repeated practice reduces mind wandering and the simple practice of meditating regularly has significant, lasting effects on attention and even clinical disorders. Contemplative practice, such as Zen and mindfulness, promotes lasting changes to the brain (Hölzel et al., 2011;Raffone et al., 2019;Young et al., 2018) and promotes cognitive performance (Zanesco et al., 2018). ...
Full-text available
While the initial research on the wandering mind usually saw it as a problem, recent research tends to have a more positive view of its adaptive functions. This has also influenced our understanding of meditative practice. While mindfulness techniques have often been argued to reduce mind wandering, it has been suggested that nondirective meditation facilitates mind wandering and default mode network activity. This chapter explores the implications of this for emotional processing. It is based on an fMRI study suggesting that nondirective meditation activates the default mode network and in particular brain areas associated with emotional processing.KeywordsMind-wanderingEmotional processingNondirective meditationDefault mode network
Mindfulness, understood as present‐centered thinking, has positive effects on cognition. Cognitive abilities fluctuate on a daily basis in older adulthood. Awareness of age‐related change (AARC) focuses on an individual's perception of life changes as a result of growing older and includes dimensions of both gains and losses. AARC losses are negative age‐related changes that are attributed to growing older, and have been linked to fluctuations in cognition. Utilizing Holas and Jankowski's cognitive model of mindfulness as a framework, we investigated the potential mediation effect of AARC losses as a type of perceived change in internal experiences. We used multilevel models to analyze daily diary data from 116 older adults (aged 60–90, M = 64.71, SD = 4.98). Participants provided baseline information on Day 1 and then completed parallel versions of inductive reasoning tests each day along with reports of daily mindfulness and AARC on Days 2–9. In line with the cognitive model of mindfulness, within‐person increases in daily mindfulness were associated with increases in inductive reasoning performance. Our results also extend the cognitive model of mindfulness because we found through multilevel mediation that increases in mindfulness were associated with decreases in AARC losses, which were then associated with increases in inductive reasoning performance. AARC losses significantly mediated the within‐person relationship between mindfulness and cognition. Efforts aimed at reducing perceived AARC losses might assist older adults in taking full advantage of the positive benefits of mindfulness on their daily cognitive abilities.
With much academic attention to experiential learning in on-site tourism experiences, the benefits of Zen meditation tourism on Generation Z after their re-entry into daily secular life remains largely unexplored. Drawing on experiential learning theory, this study explores the benefits experienced by participants after Zen meditation tourism in three stages including reflection, learning results, and active experimentation. Employing phenomenology-based ethnography, six consecutive rounds of online face-to-face interviews were conducted with 12 informants who were continuously traced after attending a Zen camp. The study findings revealed long-term positive benefits in three aspects of this generational cohort. First, Zen practices tend to be fading yet abiding after the Zen camp which continues sporadically into daily life. Second, socialisation is continuously progressive; but self-growth is complicated and unstable. Theoretical and practical implications of these novel findings are discussed.
Contemplative traditions have long affirmed that compassion and kindness are trainable skills. While research on meditation practice has recently flourished, the mechanisms that might engender such changes are still poorly understood. Here, we present a motivational framework to explain why meditation training should increase concern for others and modulate empathic engagement with human suffering over time. Meditation practices are conceived as tools for enacting cognitive and emotion regulatory goals that are conditioned by the underlying ethical motivation of the training-to reduce and alleviate suffering. In support of this account, we present data from a randomized, wait-list-controlled study of intensive meditation. In Study 1, we use a novel cardiovascular index to show that 3 months of meditation training can increase the motivational salience of others' suffering, as compared to the salience of threats to oneself. In Study 2, we demonstrate that training-related changes in the ability to orient attention to suffering are mediated by the dynamic regulation of distress-related physiological arousal. Finally, in Study 3, we provide exploratory evidence suggesting that meditation training may influence how human suffering is encoded in memory, leaving lasting imprints on the recollection of emotional experience. Together, our findings suggest that meditation training can strengthen the motivational relevance of others' suffering, prompting a shift from self-focused to other-focused evaluative processing. Considering meditation training from a motivational standpoint offers an important perspective for understanding how compassion can be cultivated through intentional practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).
In this chapter, perspectives on mind wandering will be explored from the point of view of contemplative practices, such as meditation and mindfulness.To the contemplative practitioner, mind wandering directs attention toward mental constructions, such as imagined futures, which are considered central to human suffering (Bartok J, Roemer L (2017) Remembering-and-receiving: mindfulness and acceptance in Zen. In: Masuda A, O’Donohue WT (eds) Handbook of zen, mindfulness, and behavioral health. Springer, p 237-250; Hazlett-Stevens H (2017) Zen, mindfulness, and cognitive-behavior therapy. In: Masuda A, O’Donohue WT (eds) Handbook of Zen, mindfulness, and behavioral health. Springer, p 255-270; Im S (2017) What is measured by self-report measures of mindfulness?: Conceptual and measurement issues. In: Masuda A, O’Donohue WT (eds) Handbook of Zen, mindfulness, and behavioral health. Springer, p 215-235; Kabat-Zinn, Mindfulness 7:277-278, 2016). When attention is diverted away from what is happening here and now in favor of past events or prospective futures, a sense of dissatisfaction, or dukkha, is created (Hazlett-Stevens H (2017) Zen, mindfulness, and cognitive-behavior therapy. In: Masuda A, O’Donohue WT (eds) Handbook of Zen, mindfulness, and behavioral health. Springer, p 255-270; Kabat-Zinn, Mindfulness 7:277-278, 2016; Li P, Ramirez DR (2017) Zen and psychotherapy. In: Masuda A, O’Donohue WT (eds) Handbook of Zen, mindfulness, and behavioral health. Springer, p 169-194; Rosch,E (2015) The Emperor’s clothes: A look behind the Western mindfulness mystique. In: Ostafin BD, Robinson MD, Meier BP (eds) Handbook of mindfulness and self-regulation. Springer, p 271-292) which the contemplative practitioner regards as something to wake up from.Mind wandering describes thoughts and feelings that deviate from the present task of the here and now (Smallwood and Schooler, Psychological Bulletin 132(6):946-958, 2006). Mind wandering can occur involuntary while engaged in various tasks, drawing attentional resources away by thinking of something, or sometime, else (Mason et al., Science 315(5810):393-395, 2007). For instance, task-unrelated thinking, or mind wandering, during reading or other academic activities can affect reading comprehension and cause a decrease in academic performance (Mooneyham and Schooler. Canadian Journal of Experimental Psychology/Revue Canadienne de Psychologie Expérimentale 67(1):11-18, 2013; Smallwood et al., Consciousness and Cognition 12(3):452-484, 2003; Smallwood et al., Psychonomic Bulletin & Review 14(2):230-236, 2007; Smallwood et al., Memory & Cognition 36(6):1144-1150, 2008). Mind wandering can take the form of rumination or worry, key factors underlining mental disorders such as depression and anxiety. Mind wandering has also been described as a deficit in attentional control and memory (McVay & Kane, 2009; Unsworth & McMillan, 2014) and is a predictor of performance errors and negative mood and correlates with depression (Smallwood et al., Memory & Cognition 36(6):1144-1150, 2008; Smallwood and O’Connor. Cognition & Emotion 25(8):1481-1490, 2011; Smallwood and Schooler, Psychological Bulletin 132(6):946-958, 2006).The use of contemplative practice to alleviate some of the negative effects of mind wandering is presented. How mind wandering is seen from a contemplative point of view will be presented along with application of contemplative practice in mental health professional and educational settings. Mind wandering also plays a role in self-identity. The contemplative perspective on this is that the sense of self is, in part, a result of mind wandering.KeywordsContemplative practiceDefault mode networkMeditationMindfulnessMBSRMBCTMind wandering
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Aging is known to be associated with a decline in cognitive performance and ability. However, it has been shown that programs geared towards training cognitive processes can amend or even reverse age-related cognitive decline, at least partly. Engaging the brain in intense mental processes, such as those occurring during meditation, might constitute a form of cognitive training. Thus, if practiced regularly, with a certain level of intensity, and over longer periods of time, meditation may be a means to counteract the normal effects of aging on cognition. Although systematic research is still sparse, existing studies seem to provide initial data suggesting that meditation improves cognition overall (independent of aging) and, perhaps even more importantly, reduces age-related cognitive decline. This review integrates the existing literature on cognitive changes due to aging as well as induced (or enhanced) by meditation, while identifying critical links still missing to unambiguously ascertain whether meditation can significantly contribute to optimizing and delaying brain aging.
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Scientists should be able to provide support for the absence of a meaningful effect. Currently, researchers often incorrectly conclude an effect is absent based a nonsignificant result. A widely recommended approach within a frequentist framework is to test for equivalence. In equivalence tests, such as the two one-sided tests (TOST) procedure discussed in this article, an upper and lower equivalence bound is specified based on the smallest effect size of interest. The TOST procedure can be used to statistically reject the presence of effects large enough to be considered worthwhile. This practical primer with accompanying spreadsheet and R package enables psychologists to easily perform equivalence tests (and power analyses) by setting equivalence bounds based on standardized effect sizes and provides recommendations to prespecify equivalence bounds. Extending your statistical tool kit with equivalence tests is an easy way to improve your statistical and theoretical inferences.
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Mindfulness-related meditation practices engage various cognitive skills including the ability to focus and sustain attention, which in itself requires several interacting attentional subfunctions. There is increasing behavioural and neuroscientific evidence that mindfulness meditation improves these functions and associated neural processes. More so than other cognitive training programmes, the effects of meditation appear to generalise to other cognitive tasks, thus demonstrating far transfer effects. As these attentional functions have been linked to age-related cognitive decline, there is growing interest in the question whether meditation can slowdown or even prevent such decline. The cognitive reserve hypothesis builds on evidence that various lifestyle factors can lead to better cognitive performance in older age than would be predicted by the existing degree of brain pathology. We argue that mindfulness meditation, as a combination of brain network and brain state training, may increase cognitive reserve capacity and may mitigate age-related declines in cognitive functions. We consider available direct and indirect evidence from the perspective of cognitive reserve theory. The limited available evidence suggests that MM may enhance cognitive reserve capacity directly through the repeated activation of attentional functions and of the multiple demand system and indirectly through the improvement of physiological mechanisms associated with stress and immune function. The article concludes with outlining research strategies for addressing underlying empirical questions in more substantial ways.
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Models of attention often distinguish among attention subtypes, with classic models separating orienting, switching, and sustaining functions. Compared with other forms of attention, the neurophysiological basis of sustaining attention has received far less notice, yet it is known that momentary failures of sustained attention can have far-ranging negative effects in healthy individuals, and lasting sustained attention deficits are pervasive in clinical populations. In recent years, however, there has been increased interest in characterizing moment-to-moment fluctuations in sustained attention, in addition to the overall vigilance decrement, and understanding how these neurocognitive systems change over the life span and across various clinical populations. The use of novel neuroimaging paradigms and statistical approaches has allowed for better characterization of the neural networks supporting sustained attention and has highlighted dynamic interactions within and across multiple distributed networks that predict behavioral performance. These advances have also provided potential biomarkers to identify individuals with sustained attention deficits. These findings have led to new theoretical models explaining why sustaining focused attention is a challenge for individuals and form the basis for the next generation of sustained attention research, which seeks to accurately diagnose and develop theoretically driven treatments for sustained attention deficits that affect a variety of clinical populations.
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It is challenging for individuals to maintain their attention on ongoing cognitive tasks without being distracted by task-unrelated thought. The wandering mind is thus a considerable obstacle when attention must be maintained over time. Mental training through meditation has been proposed as an effective method of attenuating the ebb and flow of attention to thoughts and feelings that distract from one’s foremost present goals. We provide evidence from 2 longitudinal studies that intensive meditation training in focused attention and monitoring meditation is associated with attenuated lapses of attention while reading. Across 2 studies, participants completed a reading task requiring ongoing error monitoring to detect episodes of semantic inconsistency. In a preliminary study, training participants were assessed at the beginning and end of a 3-month shamatha meditation retreat and again 7 years later. In a second study, training and experience-matched control participants were assessed at the beginning and end of a 1-month insight meditation retreat. Across both studies, training participants engaged in less mind wandering and less mindless reading following meditation training. Intensive meditation training may promote reductions in mind wandering among practitioners when required to maintain attention during a complex cognitive task.
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Life expectancy is constantly increasing. However, a longer life not always corresponds to a healthier life. Indeed, even normal aging is associated with a decline in different cognitive functions. It has been proposed that a central mechanism that could contribute to this widespread cognitive decline is an ineffective inhibitory attentional control. Meditation, to the other hand, has been associated, in young adults, to enhancement of several attentional processes. Nevertheless, attention is not a unitary construct. An influent model proposed the distinction of three subsystems: the alerting (the ability to reach and maintain a vigilance state), the orienting (the capacity of focusing attention on a subset of stimuli), and the conflict resolution or executive component (the ability to resolve conflict or allocate limited resources between competing stimuli). Here, we investigated, employing the Attentional Network Task (ANT), the specific impact of age on these three subcomponents, and the protective role of long-term meditation testing a group of older adults naïve to meditation, a group of age-matched adults with long-term practice of meditation, and a group of young adults with no previous meditation experience. We reported a specific decline of the efficiency of the executive component in elderly that was not observed in age-matched meditators. Our results are encouraging for the investigation of the potential beneficial impact of meditation on other cognitive processes that decline in aging such as memory. Moreover, they could inform geriatric healthcare prevention and intervention strategies, proposing a new approach for cognitive remediation in elderly populations.
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Although research on the effects of mindfulness meditation (MM) is increasing, still very little has been done to address its influence on the white matter (WM) of the brain. We hypothesized that the practice of MM might affect the WM microstructure adjacent to five brain regions of interest associated with mindfulness. Diffusion tensor imaging was employed on samples of meditators and non-meditators (n = 64) in order to investigate the effects of MM on group difference and aging. Tract-Based Spatial Statistics was used to estimate the fractional anisotrophy of the WM connected to the thalamus, insula, amygdala, hippocampus, and anterior cingulate cortex. The subsequent generalized linear model analysis revealed group differences and a group-by-age interaction in all five selected regions. These data provide preliminary indications that the practice of MM might result in WM connectivity change and might provide evidence on its ability to help diminish age-related WM degeneration in key regions which participate in processes of mindfulness.
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There is growing interest in the potential benefits of mindfulness meditation practices in terms of counteracting some of the cognitive effects associated with aging. Pursuing this question, the aim of the present study was to investigate the influence of mindfulness training on executive control and emotion regulation in older adults, by means of studying behavioral and electrophysiological changes. Participants, 55 to 75 years of age, were randomly allocated to an 8-week mindful breath awareness training group or an active control group engaging in brain training exercises. Before and after the training period, participants completed an emotional-counting Stroop task, designed to measure attentional control and emotion regulation processes. Concurrently, their brain activity was measured by means of 64-channel electroencephalography. The results show that engaging in just over 10 min of mindfulness practice five times per week resulted in significant improvements in behavioral (response latency) and electrophysiological (N2 event-related potential) measures related to general task performance. Analyses of the underlying cortical sources (Variable Resolution Electromagnetic Tomography, VARETA) indicate that this N2-related effect is primarily associated with changes in the right angular gyrus and other areas of the dorsal attention network. However, the study did not find the expected specific improvements in executive control and emotion regulation, which may be due to the training instructions or the relative brevity of the intervention. Overall, the results indicate that engaging in mindfulness meditation training improves the maintenance of goal-directed visuospatial attention and may be a useful strategy for counteracting cognitive decline associated with aging. Electronic supplementary material The online version of this article (doi:10.1007/s12671-015-0482-8) contains supplementary material, which is available to authorized users.
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One expression of executive control involves proactive preparation for future events, and this contrasts with stimulus driven reactive control exerted in response to events. Here we describe findings from a response inhibition task, delivered using a smartphone-based platform, that allowed us to index proactive and reactive inhibitory self-control in a large community sample (n = 12,496). Change in stop-signal reaction time (SSRT) when participants are provided with advance information about an upcoming trial, compared to when they are not, provides a measure of proactive control while SSRT in the absence of advance information provides a measure of reactive control. Both forms of control rely on overlapping frontostriatal pathways known to deteriorate in healthy aging, an age-related decline that occurs at an accelerated rate in men compared to women. Here we ask whether these patterns of age-related decline are reflected in similar changes in proactive and reactive inhibitory control across the lifespan. As predicted, we observed a decline in reactive control with natural aging, with a greater rate of decline in men compared to women (~10 ms versus ~8 ms per decade of adult life). Surprisingly, the benefit of preparation, i.e. proactive control, did not change over the lifespan and women showed superior proactive control at all ages compared to men. Our results suggest that reactive and proactive inhibitory control partially rely on distinct neural substrates that are differentially sensitive to age-related change.
Mindfulness interventions aim to foster greater attention to and awareness of present moment experience. There has been a dramatic increase in randomized controlled trials (RCTs) of mindfulness interventions over the past two decades. This article evaluates the growing evidence of mindfulness intervention RCTs by reviewing and discussing: (a) the effects of mindfulness interventions on health, cognitive, affective, and interpersonal outcomes; (b) evidence-based applications of mindfulness interventions to new settings and populations (e.g., the workplace, military, schools); (c) psychological and neurobiological mechanisms of mindfulness interventions; (d) mindfulness intervention dosing considerations; and (e) potential risks of mindfulness interventions. Methodologically rigorous RCTs have demonstrated that mindfulness interventions improve outcomes in multiple domains (e.g., chronic pain, depression relapse, addiction). Discussion focuses on opportunities and challenges for mindfulness intervention research and on community applications. Expected final online publication date for the Annual Review of Psychology Volume 68 is January 03, 2017. Please see for revised estimates.