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Brief, daily meditation enhances attention, memory, mood, and emotional regulation in non-experienced meditators

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Meditation is an ancient practice that cultivates a calm yet focused mind; however, little is known about how short, practical meditation practices affect cognitive functioning in meditation-naïve populations. To address this question, we randomized subjects (ages of 18 to 45) who were non-experienced meditators into either a 13-minute daily guided meditation session or a 13-minute daily podcast listening session (control group) for a total duration of 8 weeks. We examined the effects of the daily meditation practice relative to podcast listening on mood, prefrontal and hippocampal functioning, baseline cortisol levels, and emotional regulation using the Trier Social Stress Test (TSST). Compared to our control group, we found that 8 but not 4 weeks of brief, daily meditation decreased negative mood state and enhanced attention, working memory, and recognition memory as well as decreased state anxiety scores on the TSST. Furthermore, we report that meditation-induced changes in emotional regulation are more strongly linked to improved affective state than improved cognition. This study not only suggests a lower limit for the duration of brief daily meditation needed to see significant benefits in non-experienced meditators, but suggests that even relatively short daily meditation practice can have similar behavioral effects as longer duration and higher-intensity mediation practices.
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Behavioural Brain Research
journal homepage: www.elsevier.com/locate/bbr
Research report
Brief, daily meditation enhances attention, memory, mood, and emotional
regulation in non-experienced meditators
Julia C. Basso
a,b,
, Alexandra McHale
a
, Victoria Ende
a
, Douglas J. Oberlin
a
, Wendy A. Suzuki
a,
a
New York University, Center for Neural Science, 4 Washington Place, Room 809, New York, NY 10003, United States
b
Virginia Tech Carilion Research Institute, Center for Transformative Research on Health Behaviors, 1 Riverside Circle, Suite 104G, Roanoke, VA 24016, United States
GRAPHICAL ABSTRACT
ARTICLE INFO
Keywords:
Mindfulness
Breathing
Cognition
Consciousness
Stress
Executive function
ABSTRACT
Meditation is an ancient practice that cultivates a calm yet focused mind; however, little is known about how
short, practical meditation practices aect cognitive functioning in meditation-naïve populations. To address
this question, we randomized subjects (ages of 1845) who were non-experienced meditators into either a 13-
min daily guided meditation session or a 13-min daily podcast listening session (control group) for a total
duration of 8 weeks. We examined the eects of the daily meditation practice relative to podcast listening on
mood, prefrontal and hippocampal functioning, baseline cortisol levels, and emotional regulation using the Trier
Social Stress Test (TSST). Compared to our control group, we found that 8 but not 4 weeks of brief, daily
meditation decreased negative mood state and enhanced attention, working memory, and recognition memory
as well as decreased state anxiety scores on the TSST. Furthermore, we report that meditation-induced changes
in emotional regulation are more strongly linked to improved aective state than improved cognition. This study
not only suggests a lower limit for the duration of brief daily meditation needed to see signicant benets in non-
experienced meditators, but suggests that even relatively short daily meditation practice can have similar be-
havioral eects as longer duration and higher-intensity mediation practices.
https://doi.org/10.1016/j.bbr.2018.08.023
Received 8 March 2018; Received in revised form 8 August 2018; Accepted 24 August 2018
Corresponding authors at: New York University, Center for Neural Science, 4 Washington Place, Room 809, New York, NY 10003, United States.
E-mail addresses: jbasso@vt.edu (J.C. Basso), ws21@nyu.edu (W.A. Suzuki).
Behavioural Brain Research 356 (2019) 208–220
Available online 25 August 2018
0166-4328/ Published by Elsevier B.V.
T
1. Introduction
Meditation is an ancient mindfulness practice that stems from
Buddhist and Hindu cultures, where the practitioner intentionally en-
gages the mind by bringing an increased awareness to thought and
feeling. Many dierent types of meditation practices exist. For example,
focused attention meditation encourages concentration on a single ob-
ject such as the breath, a part of the body, or an external object, while
open monitoring mediation encourages a non-judgmental and non-at-
tached monitoring of all things coming into our conscious awareness. In
parallel with the growing popularity of meditation, a growing body of
studies on the behavioral and neurophysiological eects of meditation
has begun to explore whether meditation can be used to improve mood,
decrease stress, and aect various cognitive functions in both normal
[1] and patient population groups [2].
While prominent early studies of the eects of meditation focused
on patterns of electroencephalography (EEG) signals in the brains of
highly experienced Tibetan Buddhist monks relative to inexperienced
meditators [3], many meditation studies to date have taken either a
cross-sectional approach in individuals completing intensive meditation
retreats [4,5], or performed randomized controlled experiments using
either experienced meditators or non-experienced meditators with
various mental health issues. These studies report a range of mind/body
benets with the most common being enhanced emotional regulation,
attention, and self-awareness [1]. In patients with mental health issues,
meditation has shown to be aective at decreasing levels of depression,
anxiety, pain, psychological stress, and substance abuse [2,6]. Other
benets reported include decreased blood pressure and inammation,
improved immune function and glucose and insulin resistance, and
increased telomerase activity [79]. Less information is available on the
eects of meditation practices that are both shorter in overall duration
and shorter in terms of individual meditation sessions, though the data
thus far suggests that shorter practices may oer some of the same
cognitive and functional benets as longer, intense meditation practices
[10,11]. Here we explore a range of cognitive and physiological
changes associated with brief, daily mediation practice as well as the
time course of these eects.
Scientists have theorized that meditation may produce these bene-
cial eects by enhancing emotional regulation or the ability to control
our emotional state. For example, meditation is associated with a de-
creased physiological response during the viewing of a stressful lm
[12], decreased emotional interference during the Emotional Inter-
ference Task [13], and decreased self-reported diculty in regulating
the emotional state [14]. In addition, meditation programs have been
shown to reduce symptoms of anxiety, panic, and depression in patients
with anxiety disorders, with these eects lasting for up to 3 years after
the initial meditation intervention [15,16].
The hypothalamic-pituitary-adrenal (HPA) axis is a major compo-
nent of the endocrine system that controls our reaction to stress and is
connected to a circuit of brain regions including the amygdala, hippo-
campus, and prefrontal cortex, all of which work in tandem to regulate
our behavioral and physiological response to stress [17]. Research in-
dicates that the benecial eects of meditation may be due to changes
in this stress circuitry. For example, meditation has been shown to in-
crease the volume of both the hippocampal and prefrontal cortical re-
gions [18]. Moreover, mediators show decreased activation of the
amygdala while viewing emotional images [19,20]. While many pre-
vious studies have reported improved functions associated with the
prefrontal cortex with increased meditation (e.g., attention and
working memory), many fewer studies have examined the eects on
meditation of the memory functions of the hippocampus/medial tem-
poral lobe [21]. We hypothesize that meditation will improve 1) af-
fective state, 2) executive functions such as attention, working memory,
response inhibition, and cognitive exibility, that have been linked
with the prefrontal cortex, and 3) recognition memory and behavioral
pattern separation, functions that have been linked with the
hippocampus. Furthermore, we predict that compared to controls,
meditators will demonstrate enhanced emotional regulation in response
to an acute psychosocial stressor. Importantly, and as a new addition to
the literature, we examined the relationship between meditation-in-
duced changes in the stress response and changes in both psychological
state and cognitive function. We predicted that those individuals who
show the greatest reductions in stress responsivity would show the
largest gains in mood and cognition.
To address these questions, we randomly assigned healthy adults
between the ages of 18 and 45 who did not have previous experience
with mediation to either a 13-min daily guided meditation program or a
13-min daily podcast listening session for a total duration of eight
weeks. Before, at the 4-week time point, and after this training, we
assessed cognitive functioning via a battery of neuropsychological tasks
and mood state via a battery of self-reported questionnaires. To de-
termine how meditation aected stress level at the physiological level,
baseline saliva cortisol samples were taken before the intervention, at
the 4-week time point, and after the intervention. In addition, to de-
termine how meditation aected the acute response to stress, after the
eight-week program, subjects were subjected to the Trier Social Stress
Test (TSST), and both behavioral measures of anxiety and cortisol levels
were assessed before and after this test. We asked if and when brief
daily meditation would have an eect on these cognitive and physio-
logical functions. We discuss how the eects of our brief daily medi-
tation intervention compare with the eects of more intense meditation
regimes examined in previous studies.
2. Methods
2.1. Recruitment and participants
For this study, we recruited healthy, non-smoking subjects between
the ages of 18 to 45 who were not experienced meditators. Subjects
were disqualied if they had a mediation practice of more than once per
week for the past three months or if they had a current or prior diag-
nosis of any neurological or mental health issue (e.g., depression, an-
xiety, schizophrenia, epilepsy, traumatic brain injury, etc.). Prior to the
start of the study, all subjects gave their informed consent. All proce-
dures were approved by the New York University Committee on
Activities Involving Human Subjects and were performed in accordance
with the relevant guidelines and regulations. Using these criteria, a
total of 76 subjects were recruited from the New York City area via yer
advertisements and online postings. Throughout the course of the
study, 34 subjects dropped out (n = 14) or were excluded (n = 20), for
a total subject number of 42 (15 males, 27 females).
High attrition rates are common amongst longitudinal studies,
which may lead to problems of research bias [2224]. In this study, we
report an attrition rate of 44.7% (dropout rate of 18.4%), similar to
other longitudinal studies [22]. Dropout or exclusion from the study
generally occurred prior to or early in the data collection period, and
subjects dropped out for a variety of reasons including 1) lack of cor-
respondence to emails; 2) logistical issues scheduling visits; 3) non-
completion of mood questionnaires within one week of visiting the
laboratory; 4) non-compliance listening to meditation or pod-cast ses-
sions; and 5) life responsibilities too demanding to continue with the
study. A Fishers Exact Test was conducted in order to determine
whether dropout/exclusion subjects diered from subjects who com-
pleted the study in terms of sex, race, ethnicity, education level, marital
status, number of children, and household income. Dropout/exclusion
subjects did not dier from study participants in any of these areas
(p > 0.05).
Sample size for a repeated-measures analysis of variance (ANOVA)
was determined using an a priori power analysis via G*Power 3.1
[25,26]. The power analysis was conducted using two groups with three
measurements, an alpha level of 0.05, a power of 0.80, a small to
medium eect size (f = 0.2), a correlation among repeated measures of
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
209
0.5, and a nonsphericity correction εof 1. Using these criteria, the
desired total sample size was 42 subjects.
2.2. Interventions
2.2.1. Meditation (experimental group)
This eight-week study consisted of three visits to the laboratory: pre-
intervention, mid-intervention (conducted at the four-week time point),
and post-intervention. All procedures conducted at each of these visits
were similar and as described below (see mood and neuropsychological
assessment). Prior to the start of the intervention, subjects were ran-
domly assigned to a meditation group or a podcast listening group.
Once the pre-intervention laboratory session was complete, subjects
were instructed to listen to thirteen minutes of either a meditation re-
cording or a podcast every day for eight weeks. While listening to the
meditation or podcast recordings, subjects were required to log into an
audio/video hosting website (https://wistia.com/) that allowed us to
track when subjects completed their daily sessions. Subjects were dis-
qualied if they listened to the guided meditations or podcasts less than
ve times per week for two consecutive weeks.
All subjects were nancially compensated a total of $60 for their
participation in the study. Additionally, in order to promote subject
retention, participants had the opportunity to receive small prizes if
they adhered to meditation or podcast listening at least six times per
week for two consecutive weeks.
Meditation subjects were given a 13-min recording of a guided
meditation called Journey Meditation. Journey meditation, developed
by Stephen Sokoler (http://www.journeymeditation.com/), is a simple,
step-by-step, guided meditation through a variety of breathing exercises
and full-body scans currently being used in corporate situations. The
meditation recording also included an intermittent time of silence
where subjects were able to breathe at their own pace. This length of
meditation is in accordance with other brief meditation practices that
have shown positive outcomes in a variety of variables including pain,
anxiety, attentional resources, and alcohol consumption using medita-
tion sessions from 10 to 20 min [2730]. Subjects listened to the same
meditation recording daily for eight consecutive weeks. During their
rst laboratory session, meditation subjects listened to a 17-min in-
troductory meditation recording provided by Journey Meditation.
2.2.2. Podcast listening (control group)
Podcast listening was used as a control for this study. All podcasts
were taken from www.radiolab.org and segmented into approximately
13-min sections in order to mimic the same time-duration of the med-
itation recording. Radio Lab is a podcast series that promotes scientic
understanding for the general public and discusses research and stories
in science and philosophy. Topics included narratives from biology,
sociology, astronomy, cultural trends, and economics, and were
screened to ensure that they did not discuss meditation practices.
Subjects listened to a dierent podcast daily for eight consecutive
weeks. During their rst laboratory session, control subjects listened to
a 15-min sample recording of a Radio Lab podcast.
Podcast listening was explicitly chosen as an appropriate interven-
tion for our control group because of the following reasons: (1) podcast
listening was intended to be an active, learning experience similar to
the active engagement of meditation; (2) both meditation and podcast
listening could take place online and be conducted in the privacy of the
home setting; (3) podcast listening sessions could be structured to
mimic the exact time frame of the meditation sessions; (4) direct par-
ticipation in podcast listening and meditation could be monitored via
the same online system (i.e., wistia); and (5) podcast sessions did not
include mindfulness or mindfulness-related topics. Other active
learning control groups, such as the Health Enhancement Program,
have been validated for when meditation was used as the experimental
group [31]. In addition, other studies have successfully used podcast
listening as a control to demonstrate dierences in brain state signals
between meditators and controls [32,33].
2.3. Aective, cognitive, and physiological assessments
2.3.1. Mood assessment
Within 24 h after their visit to the laboratory, subjects completed a
variety of standardized, online questionnaires to assess mood, emotion,
and aective states. Subjects completed these questionnaires at home.
These included the Mindful Attention Awareness Scale, Prole of Mood
States, Quality of Life Scale, Subjective Happiness Scale, Rosenberg
Self-Esteem Scale, Pittsburgh Sleep Quality Index, Mindful Eating
Questionnaire, Fatigue Severity Scale, Rumination Scale, Perceived
Stress Scale, Beck Anxiety Inventory, Beck Depression Inventory, and
State-Trait Anxiety Inventory.
2.3.2. Neuropsychological assessment
Subjects completed a series of six tests that assessed functioning of
the prefrontal cortex and hippocampus. All methodological task details
were taken directly from previously published manuscripts. Tasks were
recreated in house using Unity, a cross-platform game engine and were
administered on a computer. These included tests of executive func-
tioning as well as recognition memory and pattern separation. Because
of study timing, all tasks needed to be completed in one visit to the
laboratory. To account for fatigue and/or interference eects, task
order was randomized between subjects; however, task order was
preserved for each subject at pre-, mid-, and post-intervention visits. All
tasks included embedded rest periods. In addition, subjects were al-
lowed to take breaks as needed. To account for learning eects, task
stimuli were changed between visits.
2.3.2.1. N-Back Task. This prefrontal cortex-dependent task tests the
capacity for short-term memory [34]. Subjects were serially presented
with letters and asked to determine via button press whether each letter
was a match or not for the letter presented n-items prior. Twelve sets of
0-, 1-, 2- and 3-back trials were presented randomly. Subjects were
shown 30+n random letters, each for 500 ms, and then had an
additional 2500 ms to respond. Subjects were given 30 s of rest in
between each trial and 2 min of rest in between each set. This task was
adapted for the computer from [35].
2.3.2.2. Reading Span Task. This dual-processing test, dependent on the
prefrontal cortex, assesses short-term memory [36,37]. Subjects were
presented with a series of three sets of sentences; each set consisted of
2-, 3-, 4-, 5-, and 6-sentence trials presented randomly. Each sentence
was followed by an unrelated word. Subjects were allowed to read the
sentence and word at their own pace and move on at their own
discretion. After each trial, subjects were asked to recall, in order, as
many words as they could. To test for task adherence, subjects were also
asked a comprehension question about the sentences. Subjects were
given 30 s of rest in between each set, except for the middle of the task
(i.e., in between sets 3 and 4) when subjects were given 2 min of rest.
This task was adapted for the computer from [38,39].
2.3.2.3. Wisconsin Card Sorting Task. This task, a traditional task that
has been shown to assess prefrontal cortex functioning and newly other
areas including the parietal lobe and even subcortical structures like the
basal ganglia, tests the capacity for cognitive exibility [4042].
Subjects were presented with a deck of 128 cards that varied in the
dimensions of color, shape, and number. They were then asked to sort
the deck by matching the cards to one of four "stimulus cards"; there
was no set time limit to respond. Subjects were then informed whether
their response was correct or incorrect. Once the subject matched 10
cards correctly, the sorting principle changed without notice. This
process continued until either the subject successfully sorted the cards
under the six dierent classication principles or all 128 trials
completed. This task was adapted from [43].
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
210
2.3.2.4. Stroop Color and Word Task. This test, which assesses both
attention and the inhibition of cognitive interference, is dependent on
the prefrontal cortex [44,45]. Subjects were serially presented with the
words RED,BLUE,”“GREENor YELLOWin either their congruent
(same) or incongruent (dierent) colors. Subjects were then asked to
indicate via button press the color, rather than the meaning, of the
word. Three sets of 48 trials were presented. A xation cross was rst
presented for 500 ms, followed by a colored word for 1500 ms, followed
by an inter-stimulus interval of 8501100 ms. Subjects were given 30 s
of rest in between each set. This task was adapted from [29].
2.3.2.5. Eriksen Flanker Task. This prefrontal cortex task tests attention
and response inhibition abilities [46,47]. Subjects were presented with
a string of seven letters comprised of a target stimulus in the center and
six ankers (i.e., three of the same letter on either side). The target
stimuli were associated with either a left or right button press. Subjects
were instructed to pay attention to the center letter and indicate
whether that letter was associated with a left or right direction. Three
sets of 144 trails were presented, with a response time of 1500 ms.
Subjects were allowed time to rest in between each set, but could move
on at their own discretion. This task was adapted from [48].
2.3.2.6. Mnemonic Similarity Task. This is a hippocampal-dependent
task that tests both recognition memory and pattern separation abilities
[49]. Subjects viewed 128 images and were asked to classify them as
indoor or outdoor items via button press. Subjects were given 30 s of
rest after the rst 64 images and 2 min of rest after the second 64
images. Later, in a surprise trial, subjects viewed another 192 images
and were asked whether they were old, similar, or new in comparison to
the previously presented objects. 64 of these images the subjects saw
previously (old/target), 64 were similar to images seen previously
(similar/lures), and 64 the subjects had not seen previously (new/foils).
Subjects were given 30 s of rest after every 64 images. Sets C and D
were utilized and all images were presented for 2000 ms followed by an
inter-stimulus interval of 500 ms. This task was adapted from [50].
2.3.3. Behavioral and physiological response to an acute stressor
To determine how meditation aected the behavioral and physio-
logical response to an acute stressor, the TSST was performed at the end
of the post-intervention testing session. Both behavioral and physiolo-
gical measurements were taken immediately prior to the TSST, im-
mediately after the TSST, and 10, 20, and 30 min after the TSST.
2.3.3.1. Trier social stress test (TSST). The TSST was used to assess the
eects of meditation on social stress responsiveness. For this task,
subjects were given ve minutes to prepare for a ve-minute interview
for their dream job. In front of two expressionless observers, they
were then asked to present a case for why they should receive the job.
They were misleadingly instructed that their responses would be
recorded and that a panel of judges trained in public speaking would
review their video-taped performance. After the interview, participants
were instructed to sequentially subtract 13 from 1,022 for ve minutes.
If a mistake was made, they were asked to start from the beginning. To
determine the behavioral response to the TSST, the state anxiety
portion of the State-Trait Anxiety Inventory (STAI) was administered
immediately before the TSST, immediately after the TSST, and 10, 20,
and 30 min after the TSST. After this 30-min period, participants were
given a debrieng form explaining the true goal and nature of the test
[51].
2.3.3.2. Salivary cortisol collection and analysis. Salivary cortisol was
collected using Sarstedts salivette with the blue cap, which contains a
biocompatible synthetic swab without preparation. Subjects were
instructed to place the swab in their mouths and gently chew for one
minute. To assess the eect of meditation on baseline cortisol levels,
saliva samples were taken at the beginning of the pre-, mid- and post-
intervention visits. Additionally, to assess the eects of meditation on
the physiological response to acute stress, saliva samples were taken
immediately before the TSST, immediately after the TSST, and 10, 20,
and 30 min after the TSST. All baseline saliva samples were taken at
approximately the same time of day (between 1:00 to 5:00 pm). This
protocol was followed in order to account for variability in the diurnal
cortisol level cycle [52]. Immediately after collection, all salivary
cortisol samples were frozen in a 20 °C freezer until later analysis.
Once all samples were collected, they were sent to the University of
Trier in Germany for analysis. Cortisol levels were measured using a
competitive solid phase time-resolved uorescence immunoassay with
ouromeric end point detection (DELFIA). After thawing, saliva sam-
ples were centrifuged at 2000 gfor 10 min; 100 μl of saliva were used
for duplicate analysis. 96-well-Maxisorb microtiterplates were coated
with polyclonal swine anti-rabbit immunoglobulin. After an incubation
period of 24 h at 4 °C, plates were washed three times with washbuer
(pH = 7.4). The plates were then coated with a rabbit anti-cortisol
antibody and incubated for 48 h at 4 °C. Synthetic saliva mixed with
cortisol in a range from 0 to 100 nmol/l served as standards. Standards,
controls (saliva pools), and samples were given in duplicate wells. 50 μl
of biotin-conjugated cortisol was added and after 30 min of incubation,
the non-binding cortisol/biotin-conjugated cortisol was removed by
washing (3x). 200 μl europium-streptavidin (Perkin Elmerc, Liefe sci-
ence Turku, Finnland) was added to each well and after 30 min and 6
times of washing, 200 μl enhancement solution was added (Pharmacia,
Freiburg, Germany). Within 15 min on a shaker, the enhancement so-
lution induced the uorescence, which can be detected with VICTOR
X4 Multilabel Plate Reader (Perkin Elmer, Massachusetts, USA). With a
computer-controlled program, a standard curve was generated and the
cortisol concentration of the samples was calculated. The intra-assay
coecient of variation was between 4.0% and 6.7%, and the corre-
sponding inter-assay coecients of variation were between 7.1% and
9.0%.
2.4. Statistical analyses
To analyze dierences in a variety of demographic variables be-
tween our drop out versus our study subjects, we utilized a Fishers
exact test. An independent-samples t-tests was used to assess dierences
in baseline measures for all mood questionnaires, cognitive tasks, and
cortisol levels. To account for the large number of dependent variables
within the experimental setup, a full omnibus model was conducted
prior to the individual statistical tests. A repeated measures multi-
variate analysis of variance (MANOVA) was run as an omnibus test to
account for possible co-variance among variables within the study,
while allowing for the inclusion of several cognitive and mood mea-
surements. The repeated measures MANOVA used group and time
points as the main eects (as well as an interaction) for 7 behavioral
measures. After the repeated measures MANOVA showed signicant
ndings, repeated measures analysis of variance (ANOVAs) were used
to examine the changes within the dierent test measures over time.
Additionally, an Analysis of Covariance (ANCOVA) using Pittsburgh
Sleep Quality Index (PSQI) change score was used when mentioned (see
Results section). Additionally, an ANCOVA was used to determine
whether the intervention aected acute stress response. In this case, the
within-subjects factor included two time points (i.e., immediately be-
fore and immediately or 10 min after the TSST), intervention type
served as the between-subjects factor, and the PSQI change score served
as the co-variate. When a signicant interaction eect was found,
paired-samples t-tests were conducted to determine the precise nature
of the statistical change. If the original test was performed using a co-
variate, post-hoc analyses were also conducted using the same co-
variate. To assess the relationship between the changes in mood, cog-
nition, and the response to acute stress, we tested whether a dierences
existed in mood (z score) or cognition (z score) between meditation and
control groups given dierences in the change in 1) cortisol after the
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
211
stress test, and 3) STAI score after the stress test using an ANCOVA
(mood = Group | TSST-induced cortisol change, and TSST-induced
STAI score change). To assess dierences in whether the groups listened
to the sessions at dierent times of day, we examined the signicance of
the dierence between two independent proportions. An alpha level of
0.05 was used to determine statistical signicance.
No outliers were present in the data, all data was normally dis-
tributed and met sphericity, and there was homogeneity of variances
and covariances for pre-, mid- and post-intervention values. In instances
where we evaluated more than two time points and sphericity was not
met, a Greenhouse-Geisser correction was made.
Two subjects did not complete the mid-intervention mood ques-
tionnaire and so statistical analyses for these results were conducted on
a total of 40 individuals (20 per group). For data analyses regarding the
Stroop and N-Back Tasks, one subject was removed because of non-
compliance with the tasks. For analyses regarding baseline cortisol le-
vels, one subject was removed from analysis because the data were
found to be outliers as assessed by inspection of boxplots (greater than
or equal to 1.5 times the interquartile range). For analyses regarding
the TSST data, four subjects were removed because their behavioral
and/or physiological data were found to be outliers. All data reported
are unadjusted mean values ± standard error of the mean (SEM).
3. Results
Baseline values for all mood questionnaires, cognitive tasks, and
cortisol measurements were equal across groups (all p > 0.05). On
average, the experimental group listened to the guided meditations 5.5
( ± 0.16) times per week, whereas controls listened to their podcasts
6.4 ( ± 0.15) times per week, which was signicantly dierent (t
(40) = 4.289, p < 0.001).
3.1. The eects of 4 weeks of meditation (midpoint assessment)
None of the measures examined at the midpoint assessment of 4
weeks were signicant, suggesting that 4 weeks of daily meditation
does not aect mood, cognitive function, or cortisol levels.
3.2. The eects of 8 weeks of meditation on aect and cognition
3.2.1. The overall model
The repeated measures MANOVA showed signicant eects within
our model (Λ= 0.554, F = 4.558, p = 0.002) for group * time * test
(described in Section 3.2.).
3.2.2. The eect of meditation on sleep quality
3.2.2.1. Pittsburgh sleep quality index (PSQI). A signicant interaction
was found in overall sleep quality (time * group F(1,40) = 8.729,
p = 0.005, partial η
2
= 0.179) as measured by the PSQI (Fig. 1A;
Meditation 4.905 ± 0.497 / 5.619 ± 0.741; Control 5.000 ± 0.473 /
3.619 ± 0.455. This eect was in the opposite direction as expected,
with controls showing a signicant improvement in sleep quality (t
(20) = 3.408, p = 0.003) and m editators s howing no change over time (t
(20) = 1.227, p = 0.234). This eect was driven by poorer sleep
eciency (time * group F(1,40) = 7.191, p = 0.011, partial η
2
= 0.152;
Meditation 0.095 ± 0.066 / 1.000 ± 0.293; Control 0.238 ± 0.118 /
0.238 ± 0.153), with meditators showing worse sleep eciency (t
(20) = 3.189, p = 0.005) and controls showing no change between
the two t ime points (t(20) = 0.000, p = 1.000). At post-intervention,
controls had a total PSQI score of 3.60 ( ± 0.46) whereas meditators had
a total PSQI score of 5.62 ( ± 0.74), which qualies on the PSQI as an
index of poor sleep quality. We hypothesize that this eect may be due to
the timing of meditation versus podcast listening. Compared to controls
(42.4%), meditators listened to signicantly more sessions (48.8%) before
bedtime (dened as the hours of 8 P.M. to 3 A.M.) (Fig. 1B; z = 2.632,
p = 0.009). As we hypothesized that this eect might inuence the
outcome of meditation on a variety of mood, stress, and cognitive
variables, all proceeding statistics were assessed both with and without
the use of the PSQI change score (total PSQI post-intervention minus total
PSQI pre-intervention) as a co-variate.
3.2.3. The eect of meditation on mood
3.2.3.1. Prole of mood states (POMS).The POMSis a scale that
measures overall total mood disturbance, which is comprised of several
subscales including tension/anxiety, depression/dejection, anger/hostility,
fatigue/inertia, confusion/bewilderment, and vigor/activity (subtracted
from the total of other combined scales). After adjusting for PSQI change
score, a signicant interaction eect was seen for the total mood
disturbance score on the POMS (time * group F(1,39) = 4.822,
p = 0.034, partial η
2
= 0.110) (Fig. 2A; Meditation 33.333 ± 5.795 /
19.095 ± 8.719; Control 23.238 ± 6.530 / 22.190 ± 6.169).
Meditators showed a signicant decrease (time F(1,19) = 5.324,
p = 0.032, partial η
2
= 0.219) for total mood disturbance score whereas
controls showed no change (time F(1,19) = 2.11, p = 0.651, partial
η
2
=0.011). This eect was driven by both anger/hostility (time *
group F(1,39) = 4.529, p = 0.040, partial η
2
= 0.104; Meditation
7.190 ± 1.808 / 5.381 ± 2.097; Control 5.000 ± 1.366 / 6.667 ±
1.482) and confusion/bewilderment (time * group F(1,39) = 4.458,
p = 0.041, partial η
2
= 0.103; Meditation 8.238 ± 1.040 / 5.905 ±
Fig. 1. (A) Data are presented as averages ( ± SEM) for the meditation and control groups both before and after the intervention. Eight weeks of meditation
signicantly impaired sleep quality as assessed by the Pittsburgh Sleep Quality Inventory (* represents a signicant time x group interaction, F(1,40) = 8.729,
p = 0.005, partial η
2
= 0.179). (B) Percentage of time spent listening to meditation or podcast sessions between the hours of 123 AM, 47 AM, 811 AM, 123 PM,
47 PM, and 811 PM. Compared to controls, meditators listened to signicantly more sessions during the before bedtime hours (8 PM to 3 AM) (z = 2.632,
p = 0.009).
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
212
1.108; Control 7.095 ± 1.019 / 7.000 ± 0.831) measurements.
3.2.3.2. Beck anxiety inventory (BAI). On this measure of anxiety, a
signicant interaction eect was seen for the BAI score (time * group F
(1,40) = 4.584, p = 0.038, partial η
2
= 0.103) (Fig. 2B; Meditation
11.238 ± 1.906 / 8.619 ± 2.028; Control 9.429 ± 1.788 / 12.048 ±
2.128). Meditators showed a non-signicant decrease in anxiety (t
(20) = 1.633, p = 0.118) whereas controls showed a non-signicant
increase in anxiety (t(20)=-1.418, p = 0.172).
3.2.3.3. Fatigue severity scale (FSS). After adjusting for PSQI change
score, a signicant interaction eect was seen for scores on the FSS (time
* group F(1,39) = 7.023, p = 0.012, partial η
2
= 0.153) (Fig. 2C;
Meditation 32.714 ± 2.468 / 28.810 ± 2.640; Control 29.619 ±
2.996 / 30.714 ± 3.022). Eight weeks of meditation caused a
signicant decrease in total fatigue severity (time F(1,19) = 7.460,
p = 0.013, p artial η
2
= 0.282); however, no change was found for the
control group (time F(1,19) = 1.480, p = 0.239, partial η
2
= 0.072).
No signicant eects were found for any of the other mood ques-
tionnaires utilized.
3.2.4. The eect of meditation on cognitive functioning
3.2.4.1. Stroop Color and Word Task. Compared to podcast listening,
meditation improved performance on this task. Specically, a
signicant interaction eect was found for the percentage of
congruent trials answered correctly (time * group F(1,39) = 5.449,
p = 0.025, partial η
2
= 0.123) (Fig. 3; Meditation 97.23 ± 0.76 /
98.55 ± 0.36; Control 98.08 ± 0.48 / 97.41 ± 0.65). Meditators
showed a near signicant improvement (t(20)=-2.024, p = 0.057)
whereas controls showed no change (t(19) = 1.218, p = 0.238). No
signicant interactions were found for percentage of incongruent trials
answered correctly, reaction times on congruent or incongruent trials,
or the interference score (reaction times on incongruent minus
congruent trials).
3.2.4.2. N-Back Task. Compared to podcast listening, meditation
improved performance on this test of short-term memory. Specically,
asignicant interaction eect was found for the average percentage of
trials answered correctly for all trials combined (0-, 1-, 2- and 3-back)
(time * group F(1,39) = 4.943, p = 0.032, partial η
2
= 0.112) (Fig. 4;
Meditation 62.35 ± 3.56 / 73.47 ± 3.70; Control 71.63 ± 2.53 /
73.49 ± 4.31). Eight weeks of meditation signicantly improved short-
term memory performance (t(20)=-3.602, p = 0.002), whereas con trols
showed no change over time ( t(19)=-0.604, p = 0.553).
3.2.4.3. Mnemonic Similarity Task. Compared to podcast listening,
meditation improved performance on traditional recognition memory,
a process linked to the medial temporal lobe along with other regions of
the frontal and parietal cortex [53]. Specically, an interaction eect
was found for the recognition memory score (time * group F
(1,40) = 4.261, p = 0.046, partial η
2
= 0.096) (Fig. 5; Meditation
0.622 ± 0.050 / 0.661 ± 0.047; Control 0.655 ± 0.069 /
0.580 ± 0.059). Meditators showed a non-signicant improvement
in recognition memory (t(20)=-1.227, p = 0.234) whereas controls
showed a non-signicant detriment in recognition memory (t
(20) = 1.661, p = 0.112). Primarily, this eect was driven by an
increased capacity to identify previously viewed images (i.e., targets)
as old (time * group F(1,40) = 7.558, p = 0.009, partial η
2
= 0.159;
Meditation 42.095 ± 2.844 / 44.857 ± 2.785; Control
47.857 ± 2.618 / 42.857 ± 3.247). No signicant interactions were
found for the behavioral pattern separation score or for measures
identifying similar images (i.e., lures) as similar or new images (i.e.,
foils) as new.
No signicant eects were found for the Reading Span Task,
Wisconsin Card Sorting Task, or Eriksen Flanker Task.
Fig. 2. Data are presented as averages ( ± SEM) for the meditation and control groups both before and after the intervention. Eight weeks of meditation (A)
signicantly decreased total mood disturbance as assessed by the Prole of Mood States (* represents a signicant time eect, F(1,19) = 5.324, p = 0.032, partial
η
2
= 0.219), (B) signicantly decreased anxiety as measured by the Beck Anxiety Inventory (* represents a signicant time x group interaction, F(1,40) = 4.584,
p = 0.038, partial η
2
= 0.103), and (C) signicantly decreased fatigue as measured by the Fatigue Severity Scale (* represents a signicant time eect, F
(1,19) = 7.460, p = 0.013, partial η
2
= 0.282).
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
213
3.3. The eect of meditation on baseline measures of stress and the response
to acute stress
3.3.1. Baseline cortisol measures
No signicant interaction eect was found for baseline cortisol va-
lues (time*group F(1,39) = 0.194, p = 0.662, partial η
2
= 0.005;
Meditation 4.457 ± 0.686 / 3.924 ± 0.504; Control 4.493 ± 0.646 /
4.305 ± 0.523), indicating no change in baseline cortisol values over
time.
3.3.2. Acute stress response
All TSST-related analyses were conducted using the PSQI change
score as a co-variate. The TSST, a laboratory test that serves as a psy-
chosocial stressor, increased state anxiety levels (state component score
of the STAI) as measured from immediately before to immediately after
the test (time F(1,35) = 33.439, p < 0.001, partial η
2
= 0.489).
Additionally, a signicant interaction eect was found for the state
anxiety score between these two time points (time*group F
(1,35) = 4.128, p = 0.050, partial η
2
= 0.105; Meditation 33.550 ±
2.271 / 39.200 ± 2.973; Control 35.444 ± 2.058 / 46.222 ± 3.190),
with eight weeks of meditation signicantly reducing the behavioral
stress response to the TSST (Fig. 6A). State anxiety levels then con-
tinued to decrease for both groups through the nal time point of
testing (i.e., 30 min after the TSST). The TSST also increased saliva
cortisol levels, with peak cortisol levels occurring at 10 min after
completion of the TSST (time F(1,35) = 16.589, p < 0.000, partial
η
2
= 0.322). Despite behavioral dierences, no signicant interaction
eect was found for cortisol levels between time points immediately
before the test to immediately after (time*group F(1,35) = 2.323,
p = 0.144, partial η
2
= 0.060; Meditation 2.248 ± 0.265 / 2.273 ±
0.318; Control 2.912 ± 0.340 / 3.176 ± 0.360) or 10 min after the
TSST (time*group F(1,35) = 2.835, p = 0.101, partial η
2
= 0.075;
Meditation 2.248 ± 0.265 / 4.198 ± 0.619; Control 2.912 ± 0.340 /
3.944 ± 0.413) (Fig. 6B). Cortisol levels then continued to decrease for
both groups through the nal time point of testing.
3.4. The relationship between meditation-induced changes in the acute stress
response, mood, and cognition
After determining that meditation enhanced mood (i.e., total mood
disturbance, anxiety, and fatigue), cognition (i.e., attention, working
memory, and recognition memory), and the response to acute stress, we
sought to determine the relationship between these meditation-induced
changes. To do this, we tested whether a dierences existed in mood (z
score) between meditation and control groups given dierences in both
the behavioral (i.e., TSST-induced changes in STAI score) and physio-
logical (i.e., TSST-induced changes in saliva cortisol) measure of acute
stress. The model (adj. R
2
= 0.27) showed a signicant dierence in
mood change between meditators and control subjects (F = 5.24,
p = 0.028). However, no signicant relationship existed between the
change in STAI score and mood (F = 2.39, p = 0.131), nor was the
change in cortisol signicantly associated with mood (F = 2.41,
p = 0.130). Because this nding was surprising, the relationships of
STAI and cortisol were further explored by regressing mood on STAI
score and cortisol using the enter method. A signicant overall corre-
lation was found (adj. R
2
= 0.181, F = 5.09, p = 0.011), but only STAI
score was a signicantly correlated coecient (β=0.33,
t=2.080, p = 0.045) with mood, compared to cortisol (β= 0.248,
t = 1.565, p = 0.127) (Fig. 7A). Therefore, the ANCOVA model was
reduced to group given STAI score, which was signicant (adj.
R2 = 0.24) with a signicant group dierence (F = 5.37, p = 0.026),
and a signicant eect of STAI score (F = 4.44, p = 0.042).
In addition to testing mood dierences, cognition (z score) was
assessed using the same original ANCOVA model (cognition =
group|ΔSTAI*ΔCortisol). This model (adj. R
2
= 0.114) showed sig-
nicant dierences between groups (F = 7.42, p = 0.010); however, no
signicant eects were found for either STAI (F = 0.99, p = 0.326) or
cortisol change (F = 0.33, p = 0.568). When cognition was regressed
on STAI score and cortisol, no signicant eect was found for the
overall model (adj. R
2
=0.053, F = 0.09, p = 0.911), and no sig-
nicant eects were found for either STAI score (β= 0.048, t = 0.267,
p = 0.791) or cortisol (β=0.042, t = 0.234, p = 0.816) (Fig. 7B).
Therefore, we removed the covariates, and the one-way ANOVA for the
change in cognition demonstrated statistical signicance (F = 8.44,
p = 0.006). In addition, no correlation existed between mood (z-score)
and cognition (z-score).
Fig. 3. Data are presented as averages ( ± SEM) for the meditation and control
groups both before and after the intervention. Eight weeks of meditation sig-
nicantly enhanced attention as assessed by accuracy (percent correct) on
congruent trials of the Stroop Color and Word Task (* represents a signicant
time x group interaction, F(1,39) = 5.449, p = 0.025, partial η
2
= 0.123).
Fig. 4. Data are presented as averages ( ± SEM) for the meditation and control
groups both before and after the intervention. Eight weeks of meditation sig-
nicantly enhanced working memory as assessed by accuracy (percent correct)
on 0-, 1-, 2-, and 3-back trials of the N-Back Task (* represents a signicant
dierence using a paired samples t test, t(20) = 3.602, p = 0.002).
Fig. 5. Data are presented as averages ( ± SEM) for the meditation and control
groups both before and after the intervention. Eight weeks of meditation sig-
nicantly enhanced recognition memory as assessed by the Mnemonic
Similarity Task (* represents a signicant time x group interaction, F
(1,40) = 4.261, p = 0.046, partial η
2
= 0.096).
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
214
4. Discussion
Here we report that relative to a podcast-listening control group, 8
but not 4 weeks of a daily 13-min meditation resulted in decreased
negative mood states including decreases in mood disturbance, anxiety,
and fatigue scores, enhanced attention (as measured by the Stroop
Task), working memory (as measured by the N-Back Task) and re-
cognition memory (as measured by the recognition component of the
Mnemonic Similarity Task), a decrease in the behavioral anxiety re-
sponse to the TSST and surprisingly, a reduction in overall sleep quality.
We also showed that those individuals who were best able to emo-
tionally regulate in response to an acute stressor showed the largest
decreases in negative mood states from the intervention. Finally, we
found that meditation-related emotional regulation is more strongly
linked to the benets in aective state than cognitive function. These
results add to the growing body of studies (e.g., [10,11,30,54]) showing
that even short duration meditation sessions in naïve meditators exhibit
a similar range of cognitive benets as the eects previously reported
following longer duration, more intense meditation training in both
normal and clinical populations.
4.1. Meditation-induced changes in mood
Our nding that 8 weeks of brief daily meditation relieves feelings
of negativity by decreasing levels of mood disturbance and anxiety are
consistent with other studies showing that similar duration meditation
programs provide decreased negative aect [4,55] and increased po-
sitive aect [5]. Similar ndings have been reported for intense month-
long meditation retreats [56], as well as in individuals with years of
meditation experience [57], suggesting that a wide range of meditation
intensity and durations have an overall positive eect on mood.
4.2. Meditation-induced changes in the stress response
We also showed that brief daily meditation enhanced emotional
regulation by decreasing the behavioral response to an acute psycho-
social stressor. While previous studies reported similar ndings in ex-
perienced meditators [58] as well as with intensive long-term medita-
tion programs [59] or intense, acute meditation interventions (3 days)
[60,61], ours is the rst to show these eects with a brief daily med-
iation practice. Furthermore, this is the rst study to identify a sig-
nicant correlation between the behavioral response to acute stress and
changes in mood. Other studies have shown that meditation enhances
emotional regulation by decreasing self-reported diculty in emotional
regulation [14], reducing emotional interference while viewing un-
pleasant pictures [13], and decreasing physiological reactivity while
viewing a stressful lm [1,62].
Previous studies have suggested that meditation may induce bene-
cial eects on emotional regulation through circuit-level changes in-
volving the amygdala and prefrontal cortex. Using fMRI, researchers
Fig. 6. Data are presented as averages ( ± SEM) for the time points immediately before, immediately after (0), and 10-, 20-, and 30-min after the Trier Social Stress
Test, which served as a psychosocial stressor. Eight weeks of meditation (A) signicantly decreased the behavioral response (as measured by the state component of
the State-Trait Anxiety Inventory) to the TSST (* represents a signicant time x group interaction, F(1,35) = 4.128, p = 0.050, partial η
2
= 0.105). (B) Cortisol
values (nmol/l) in response to the TSST were similar between the two groups.
Fig. 7. These data graphs represent the relationship between changes in (A) mood state (z score including total mood disturbance, anxiety, and fatigue) or (B)
cognition (z score including attention, working memory, and recognition memory) over the eight weeks of the intervention (post-intervention minus pre-inter-
vention) and the behavioral response to the TSST (immediately after minus immediately before) for both meditation and control groups. Meditation-related changes
in emotional regulation are more strongly related to benets in mood than cognition. Those individuals who showed the largest improvements in mood displayed the
lowest levels of anxiety in response to the TSST (* represents a signicant correlation, (A) r(38) = 0.414, p = 0.010, (B) r(38) =0.062, p = 0.716).
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
215
found that while viewing emotionally charged images, novice medita-
tors show a decrease in activation in the amygdala but an increase in
activation of the prefrontal cortex [19]. This increase in prefrontal
cortex activation was also shown in novice meditators during an af-
fective Stroop Task [63]. This indicates that novice meditators may
engage both bottom-up and top-down processes simultaneously to ac-
tively control stress and regulate their emotional state. On the other
hand, expert meditators viewing emotional images show a decreased
activation across a range of default mode network nodes including the
medial prefrontal and posterior cingulate cortices [20]. This suggests
that long-term meditative practices may lead to a state of emotional
stability, whichis regulated by higher-order cognitive regions.
4.3. Meditation-induced changes in cognitive function
In addition to changes in mood and the stress response, eight weeks
of brief daily mediation also improved performance on a range of
cognitive tasks including accuracy on the congruent trials of the Stroop
Task. That is, meditation enhances the ability to identify the color name
when the color of the word matches the word presented, referred to as
the Stroop facilitation eect. Researchers have hypothesized that this
occurs because when the brain processes congruent (rather than in-
congruent) color and word information simultaneously, it can do so at a
faster speed [64,65]. Facilitation is considered to be a measure of at-
tention distinct from the Stroop interference eect [64], and like in-
terference, is a process that relies on the anterior cingulate cortex [66].
Research has shown that individuals with better inhibitory control (as
measured by reaction time on the stop-signal task) perform better on
the congruent trials of the Stroop Task [67]. Though other studies have
found that meditation enhances the Stroop interference eect [63,68],
this is the rst study to nd that a brief meditation practice enhances
facilitation. One other study found that meditation did not enhance the
Stroop facilitation eect, but changes were assessed after only one
20 min-bout of meditation [69]. Other studies are consistent with our
nding by showing that meditation enhances attentional awareness,
especially in the area of conict monitoring, through tasks such as the
attention network test and the attentional blink test [10,70]. Electro-
physiological studies suggest that meditation may be enhancing atten-
tion through neural mechanisms involving the error-related negativity
signal, an event related potential that signals error detection and is
associated with the anterior cingulate cortex and dorsolateral prefrontal
cortex [71]. Future studies will need to assess the neural correlates
underlying the meditation-induced improvements in facilitation.
Eight weeks of daily meditation also enhanced both working
memory (as measured by the N-Back Task) and recognition memory (as
measured by the recognition component of the Mnemonic Similarity
Task). Consistent with our ndings, previous studies have reported that
meditation enhances performance on the N-Back Task [30] as well as
the digit and operation span tasks, other tasks of working memory
[4,30,7274]. One previous study showed that increased meditation
practice resulted in increased levels of grey matter volume in the frontal
cortex, especially in the areas of the anterior cingulate cortex and
medial frontal gyrus, suggesting a possible morphological correlate of
these working memory improvements [75]. Fewer studies have in-
vestigated the eects of meditation on recognition memory. One study
reported that approximately 10 min of meditation done both before
encoding and before retrieval of a Remember-Know Task increased the
ability to recognize previously seen images [21]. This study also
showed that 10 min of meditation prior to reading a passage of text
increased free recall memory of this text [21]. However, to our
knowledge, ours is the only study to report that 8 weeks of brief daily
meditation results in improved recognition memory. Previous studies
have reported that meditators show greater gray matter concentration
in the hippocampus and parahippocampal cortex as well as white
matter tracts between the hippocampus and other brain regions
[7680]; however, these studies were conducted on long-term
meditation practitioners (5 years or more of experience).
Other studies suggest that the improvements in attention, working
memory and recognition memory performance observed here may be
mediated at least in part by changes in resting state brain activity. For
example, a number of studies have reported that a long-term meditation
practice enhances resting state alpha and theta power [81,82]. These
oscillatory brain states have been linked to both relaxation as well as
cognitive functions, including attention, information processing, and
learning and memory; collectively, enhancements in alpha and theta
may lead to the relaxed alertnessexperienced after a meditation
practice. Additionally, a resting state fMRI study showed that 5 h of
meditation training over a period of 2 weeks enhanced resting state
functional connectivity in a diuse network of brain regions including
the bilateral superior/middle occipital gyrus, bilateral frontal oper-
culum, bilateral superior temporal gyrus, right superior temporal pole,
bilateral insula, caudate, and cerebellum [11].
4.4. Meditation-related emotional regulation is more strongly linked to
benets in aective state than cognitive function
Though previous studies have found that brief mindfulness training
enhances mood, cognition, and the response to acute stress, few studies
have explored the interconnected nature behind these phenomena
[30,8386]. We found that meditation-induced changes in the response
to acute stress are related to changes in aective state. That is, a
heightened capacity for emotional regulation predicts the mood bene-
ts from meditation. Furthermore, regardless of equivalent stress-in-
duced increases in cortisol between the groups, meditators reported
lower levels of anxiety in response to the TSST. This suggests that
meditation may cause specic changes in the brain that modulate how
we interpret and respond to physiological stress signals. One could
imagine that the consistent positive behavioral responses to real life
acute stressors conferred by meditation may help lead to overall more
positive mood states. The relationship described above was not true for
cognition, nor was the meditation-induced improvements in mood re-
lated to the improvements in cognition. These additional ndings
suggest that the cognitive benets from meditation may have a dierent
underlying mechanism than the mood benets.
Previous research in this area has shown an association between
self-reported mindfulness and aective state [87]. Specically, high
levels of mindfulness are associated with high levels of positive aect
and low levels of negative aect, perceived stress, and depressive
symptom severity [88]. Additionally, one randomized controlled trial
study found that 8 weeks of Mindfulness-Based Stress Reduction
training reduced perceived stress and vital exhaustion while enhancing
positive aect, quality of life, and mindfulness [89]. Further, they found
that mindfulness partially mediated the benecial eects of meditation
[89]. Our study adds to this research by showing that the larger the
meditation-induced gains in the ability to cope with acute stress, the
larger the benets in aective state.
4.5. The neural correlates of meditation
Our behavioral ndings, along with other functional, physiological,
and morphological studies noted here, suggest that the practice of
meditation may change brain regions that regulate mood, stress, and
cognitive processes. One meta-analysis provided insight into the brain
areas active during meditation [90]. Using activation likelihood esti-
mation (ALE), the authors concluded that three key brain regions
subserve the meditative state; namely, the basal ganglia (caudate), the
entorhinal cortex (parahippocampal region), and the medial prefrontal
cortex. These regions play a role in a variety of cognitive processes that
are relevant for the meditative state including attentional awareness,
response inhibition, emotional regulation, learning and memory, ima-
gination, monitoring of thoughts, and self-referential thinking. These
authors suggested that during the meditative state, the basal ganglia
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
216
contributes to the inhibition of irrelevant thoughts, the entorhinal
cortex contributes to the control of the mental state, and the mPFC
contributes to the enhanced sense of self-awareness [90]. It would be of
interest to image these brain areas both before and after our 8 weeks of
brief daily meditation to see if the specic brain regions or activation
patterns change with improved performance.
4.6. Meditation and sleep quality
A surprising nding reported here was that brief daily meditation
impairs sleep quality relative to control subjects. By contrast, other
studies have reported that meditation improves sleep quality, especially
in individuals with sleep disturbance issues [9193]. This nding could
be due to the fact that many of our study subjects completed their
meditation sessions before bedtime. This may have caused them di-
culty in falling asleep and aected their sleep eciency, calculating by
dividing the total number of hours slept by the total number of hours
spent in bed. Many external factors inuence sleep including stress,
sleep environment, light (e.g., using the computer or watching televi-
sion), medication intake, and food, caeine, or alcohol consumption
[94,95]. The majority of subjects completed their meditation sessions
from 8 to 11 p.m., with some individuals completing their sessions from
12 to 3 a.m. Considering that subjects completed their sessions so late in
the day and prior to bedtime, we hypothesize that they may have been
performing other tasks late at night including completing homework,
watching television, eating, drinking, or consuming alcohol, which may
have aected their overall sleep quality. Despite our nding that
meditators reported worse sleep quality, 8 weeks of meditation de-
creased levels of fatigue. Other studies of similar design have found
benecial eects of meditation on feelings of fatigue, but these have
been primarily in patient populations [92,9698]. This is one of the rst
studies to report that brief meditation training results in lower fatigue
levels in non-patient populations.
4.7. Negative ndings
Though our ndings reveal a variety of meditation-induced im-
provements (i.e., decreased mood disturbance, anxiety, fatigue, and
emotional response to a psychosocial stressor, as well as improved at-
tention, working memory, and recognition memory), some of the
neuropsychological tasks we assessed revealed no meditation-induced
eect.
For example, meditation did not alter baseline levels of cortisol.
Others have found that meditation signicantly decreases baseline le-
vels of cortisol [99101]. Reasons for this may be methodological in
nature. Cortisol levels are notoriously dicult to measure because of
their circadian rhythm. Cortisol levels peak after waking and wane
throughout the day until the onset of sleep, and then slowly rise again
throughout the night. Because of the lengthy laboratory sessions and
the varying subject schedules, cortisol collection times ranged from
11:00 A.M. to 8:00 P.M. For each individual subject, cortisol was col-
lected at approximately the same time at each visit; however, in some
instances collection time was not consistent. Because of this, SEMs were
large and overlapped between the groups. Future studies should ensure
a more constrained cortisol collection time period.
In addition, meditation did not alter the cortisol response to a
psychosocial stressor, though self-reported measures of anxiety were
decreased in the meditation compared to the control group. The TSST is
a known psychosocial stressor that has been shown to reliably increase
levels of saliva cortisol two to four times above baseline levels, with
peak cortisol levels occurring from 15 to 20 min post-test [51,102].
Studies have shown that meditation has varying eects on the cortisol
response to the TSST, ranging from a decrease [103], no change [103],
or even an increase [61]; these dierences appear to be dependent on
the type of meditation and have been shown to occur in spite of a de-
crease in the perceived stress level, similar to the results of our study.
Another possible reason for lack of between group dierences may be
due to the range of inter-individual dierences to psychosocial stress
[104], which again may have led to large SEMs and overlap between
the groups. A few variables mediating these inter-individual dierences
include age, sex, sex steroid levels, genetic factors, diet, and caeine
and alcohol consumption [104]. In regards to the lack of relationship
between the psychosocial stressor-induced changes in cortisol and
changes in anxiety, a meta-analysis revealed that signicant positive
correlations between cortisol responses and perceived emotional stress
was only found in 25% of studies [105]. They report that a variety of
factors inuence the relationship between the physiological and emo-
tional outcomes of psychosocial response including sex, menstrual
phase, brain morphology, hypothalamic-pituitary-adrenal axis and au-
tonomic nervous system baseline characteristics, and personality traits
such as social desirability, motivation for task engagement, emotion
regulation and processing, and appraisal processes [105]. Others sug-
gest that assessing levels of cortisol and self-reported measures of
emotion during the TSST may be a more accurate or informative marker
of the stress response than measures taken before or after the test [106].
The present study did not obtain measures during the test and future
studies should think about incorporating an additional measurement
during the test.
Finally, not all cognitive tasks showed an improvement with med-
itation. Specically, meditation did not improve performance on the
Reading Span Task, Wisconsin Card Sorting Task, Eriksen Flanker Task,
or pattern separation component of the Mnemonic Similarity Task. In
contrast to the tasks that show meditation-induced improvements (i.e.,
N-Back Task, Stroop Task, and recognition memory component of the
Mnemonic Similarity Task), this highlights the idea that some neu-
ropsychological tasks may be more sensitive than others in identifying
cognitive improvements as they relate to meditation. A meta-analysis of
163 meditation studies revealed that the benecial eects of meditation
are strongest in areas of emotion (medium to large eect size), weaker
in measures of attention (medium eect size), and weakest in other
areas of cognitive functioning (small to medium eect size) [107].
Other reviews have noted that the most sensitive areas of cognitive
function aected by meditation include attention, memory, verbal
uency, and cognitive exibility, and suggest that meditation may be a
good intervention for prevention of cognitive decline in the elderly
[108]. A lack of eect may be seen in the above tasks for several rea-
sons. First, the impact of meditation on these cognitive areas varies
with the type of meditation practice (e.g., transcendental meditation or
mindfulness meditation) along with the practitioners previous medi-
tation experience [107]. Second, some of our tasks such as the Eriksen
Flanker Task were being performed at ceiling level (95% percent
correct); task diculty may need to be increased in order to see an
eect. Third, a longer, more intensive meditation period may be needed
to see a functional change in specic tasks; that is, some tasks may be
more sensitive at revealing meditation-induced cognitive changes than
others. Finally, and specically when we look at the Mnemonic Simi-
larity Task, the nding that meditation improved recognition memory
but not behavioral pattern separation may indicate that meditation may
eect the brain in a region-specic manner (i.e., meditation may benet
a diverse network of brain regions supporting recognition memory such
as the medial temporal, frontal, and parietal lobes along with the hip-
pocampus [53], but not others such as the dentate gyrus subregion of
the hippocampus that supports behavioral pattern separation [109].
4.8. Limitations
Mindfulness and meditation research is still in its infancy, only
having begun in the 1970s; researchers in this eld have suggested that
this body of work suers from methodological issues [110]. The current
study is not without its limitations. First, individuals who choose to
participate in meditation studies may be fundamentally dierent from
those who do not choose to participate in these types of mindfulness
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
217
practices. Second, the high dropout rate may have biased the study
results; however, analyses revealed that subjects in both groups did not
dier on a variety of demographic variables including sex, race, eth-
nicity, education level, marital status, number of children, and house-
hold income. Third, the small sample size was not ideal, though an a
priori power analysis conrmed that a sample size of 42 subjects was
sucient to nd a statistically signicant dierence if one existed. A
fourth limitation regards the self-reported measures collected to assess
aective state; self-reported measures may not fully capture multi-
faceted psychological phenomenon and often do not align with in-
formation derived from implicit measures [111]. To limit this, we
performed these self-reported measures in collaboration with neu-
ropsychological assessment, psychosocial stress testing, and physiolo-
gical measures (i.e., cortisol). Fifth, the fact that subjects logged into
wistia to register their completion of the meditation or podcast listening
sessions does not guarantee that they actually adhered to the protocol
and engaged with the material. However, home training sessions are
common in mindfulness research, and a recent meta-analysis across 43
studies (N = 1,427) revealed that on average, subjects completed 64%
of their meditation sessions [112]. In our study, adherence for the
meditation group was 78.6%, whereas adherence for the control group
was 91.4%; values that are much higher than those in [112]. We predict
that adherence would have been much lower if we required subjects to
come into the laboratory to listen to their daily meditation or podcast
sessions. Finally, this work utilizes one type of meditative practice,
which is in the broader context of a range of mindfulness practices.
Future research will be needed to expand and highlight the types of
meditative practices that are most benecial for enhancing psycholo-
gical processes such as mood, stress regulation, and cognitive func-
tioning.
4.9. Conclusions
Taken together, our results contribute to the establishment of the
minimum doseof meditation that results in signicant mood and
cognitive benets. Namely, we show that 8, but not 4, weeks of brief
daily meditation is benecial not only for decreasing negative mood
state but for stress reduction, as well as the ability to pay attention to
and remember information in the environment. Importantly, our study
shows that 8 weeks of brief daily mediation in healthy adults can have a
similar range of cognitive and mood benets as has been seen in other
studies using longer and/or more intense meditation training in naïve
meditators, experienced meditators, or patient populations with de-
pression or anxiety [113,114]. Moreover, these ndings and others
suggest a major target for the eects of meditation on the brain areas
associated with and strongly inuenced by the HPA axis, though the
specic mechanisms by which meditation is working remain to be
elucidated.
Competing interests
The authors declare that there is no potential conict of interest.
Declaration of interest
None.
Acknowledgements
The authors thank Catherine E. OBrien, Christen Crosta, Julia
Canick, and Paula Tefera for their help in organization and analysis of
the data. The authors thank Zachary Psaras, Andrei Marks, and Michael
T. Astolfor their help in designing the computer-based versions of the
neuropsychological asessments. This research was supported by a
Deans Undergraduate Research Fund grant at New York University and
by Stephen Sokoler, founder and CEO, of Journey Meditation. The
funders had no role in study design, data collection and analysis, de-
cision to publish, or preparation of the manuscript.
References
[1] Y.Y. Tang, B.K. Holzel, M.I. Posner, The neuroscience of mindfulness meditation,
Nat. Rev. Neurosci. 16 (4) (2015) 213225.
[2] M. Goyal, et al., Meditation programs for psychological stress and well-being: a
systematic review and meta-analysis, JAMA Intern. Med. 174 (3) (2014) 357368.
[3] R.J. Davidson, A. Lutz, Buddhas brain: neuroplasticity and meditation, IEEE
Signal Process. Mag. 25 (1) (2008) 174176.
[4] R. Chambers, B.C.Y. Lo, N.B. Allen, The impact of intensive mindfulness training
on attentional control, cognitive style, and aect, Cognit. Ther. Res. 32 (3) (2008)
303322.
[5] S. Jain, et al., A randomized controlled trial of mindfulness meditation versus
relaxation training: eects on distress, positive states of mind, rumination, and
distraction, Ann. Behav. Med. 33 (1) (2007) 1121.
[6] A. Chiesa, A. Serretti, A systematic review of neurobiological and clinical features
of mindfulness meditations, Psychol. Med. 40 (8) (2010) 12391252.
[7] N.S. Schutte, J.M. Malou, A meta-analytic review of the eects of mindfulness
meditation on telomerase activity, Psychoneuroendocrinology 42 (2014) 4548.
[8] D. Muehsam, et al., The embodied mind: a review on functional genomic and
neurological correlates of mind-body therapies, Neurosci. Biobehav. Rev. 73
(2017) 165181.
[9] M.K. Koike, R. Cardoso, Meditation can produce benecial eects to prevent
cardiovascular disease, Horm. Mol. Biol. Clin. Investig. 18 (3) (2014) 137143.
[10] Y.Y. Tang, et al., Short-term meditation training improves attention and self-reg-
ulation, Proc. Natl. Acad. Sci. U. S. A. 104 (43) (2007) 1715217156.
[11] Y.Y. Tang, et al., Brief mental training reorganizes large-scale brain networks,
Front. Syst. Neurosci. 11 (2017) 6.
[12] D.J. Goleman, G.E. Schwartz, Meditation as an intervention in stress reactivity, J.
Consult. Clin. Psychol. 44 (3) (1976) 456466.
[13] C.N.M. Ortner, S.J. Kilner, P.D. Zelazo, Mindfulness meditation and reduced
emotional interference on a cognitive task, Motiv. Emot. 31 (4) (2007) 271283.
[14] C.J. Robins, et al., Eects of mindfulness-based stress reduction on emotional
experience and expression: a randomized controlled trial, J. Clin. Psychol. 68 (1)
(2012) 117131.
[15] J. Kabat-Zinn, et al., Eectiveness of a meditation-based stress reduction program
in the treatment of anxiety disorders, Am. J. Psychiatry 149 (7) (1992) 936943.
[16] J.J. Miller, K. Fletcher, J. Kabat-Zinn, Three-year follow-up and clinical implica-
tions of a mindfulness meditation-based stress reduction intervention in the
treatment of anxiety disorders, Gen. Hosp. Psychiatry 17 (3) (1995) 192200.
[17] H.O. Besedovsky, A. del Rey, Neuroimmune Biology, Volume 7 The
Hypothalamus-Pituitary-Adrenal Axis Foreword, Hypothalamus-Pituitary-Adrenal
Axis 7 (2008) 1315.
[18] K.C. Fox, et al., Is meditation associated with altered brain structure? A systematic
review and meta-analysis of morphometric neuroimaging in meditation practi-
tioners, Neurosci. Biobehav. Rev. 43 (2014) 4873.
[19] J. Lutz, et al., Mindfulness and emotion regulationan fMRI study, Soc. Cogn.
Aect. Neurosci. 9 (6) (2014) 776785.
[20] V.A. Taylor, et al., Impact of mindfulness on the neural responses to emotional
pictures in experienced and beginner meditators, Neuroimage 57 (4) (2011)
15241533.
[21] K.W. Brown, et al., Mindfulness enhances episodic memory performance: evidence
from a multimethod investigation, PLoS One 11 (4) (2016) p. e0153309.
[22] K. Gustavson, et al., Attrition and generalizability in longitudinal studies: ndings
from a 15-year population-based study and a Monte Carlo simulation study, BMC
Public Health 12 (2012) 918.
[23] J.W. Hogan, J. Roy, C. Korkontzelou, Handling drop-out in longitudinal studies,
Stat. Med. 23 (9) (2004) 14551497.
[24] D. Wolke, et al., Selective drop-out in longitudinal studies and non-biased pre-
diction of behaviour disorders, Br. J. Psychiatry 195 (3) (2009) 249256.
[25] F. Faul, et al., Statistical power analyses using G*Power 3.1: tests for correlation
and regression analyses, Behav. Res. Methods 41 (4) (2009) 11491160.
[26] F. Faul, et al., G*Power 3: a exible statistical power analysis program for the
social, behavioral, and biomedical sciences, Behav. Res. Methods 39 (2) (2007)
175191.
[27] E.L. Garland, et al., Randomized controlled trial of brief mindfulness training and
hypnotic suggestion for acute pain relief in the hospital setting, J. Gen. Intern.
Med. 32 (10) (2017) 11061113.
[28] S.K. Kamboj, et al., Ultra-brief mindfulness training reduces alcohol consumption
in at-risk drinkers: a randomized double-blind active-controlled experiment, Int. J.
Neuropsychopharmacol. 20 (11) (2017) 936947.
[29] A. Moore, et al., Regular, brief mindfulness meditation practice improves elec-
trophysiological markers of attentional control, Front. Hum. Neurosci. 6
(2012) 18.
[30] F. Zeidan, et al., Mindfulness meditation improves cognition: evidence of brief
mental training, Conscious. Cogn. 19 (2) (2010) 597605.
[31] D.G. MacCoon, et al., The validation of an active control intervention for
Mindfulness based Stress Reduction (MBSR), Behav. Res. Ther. 50 (1) (2012) 312.
[32] A. Ahani, et al., Change in physiological signals during mindfulness meditation,
Int. IEEE. EMBS Conf. Neural Eng. (2013) 13811738.
[33] A. Ahani, et al., Quantitative change of EEG and respiration signals during
mindfulness meditation, J. Neuroeng. Rehabil. 11 (2014) 87.
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
218
[34] A.M. Owen, et al., N-back working memory paradigm: a meta-analysis of nor-
mative functional neuroimaging studies, Hum. Brain Mapp. 25 (1) (2005) 4659.
[35] T.S. Braver, et al., A parametric study of prefrontal cortex involvement in human
working memory, Neuroimage 5 (1) (1997) 4962.
[36] A.R. Conway, et al., Working memory span tasks: a methodological review and
users guide, Psychon. Bull. Rev. 12 (5) (2005) 769786.
[37] M.J. Kane, R.W. Engle, The role of prefrontal cortex in working-memory capacity,
executive attention, and general uid intelligence: an individual-dierences per-
spective, Psychon. Bull. Rev. 9 (4) (2002) 637671.
[38] R.W. Engle, et al., Working memory, short-term memory, and general uid in-
telligence: a latent-variable approach, J. Exp. Psychol. Gen. 128 (3) (1999)
309331.
[39] M. Daneman, P.A. Carpenter, Individual dierences in working memory and
reading, J. Verbal Learn. Verbal Behav. 19 (1980) 450466.
[40] B.R. Buchsbaum, et al., Meta-analysis of neuroimaging studies of the Wisconsin
card-sorting task and component processes, Hum. Brain Mapp. 25 (1) (2005)
3545.
[41] E. Nyhus, F. Barcelo, The Wisconsin Card sorting Test and the cognitive assessment
of prefrontal executive functions: a critical update, Brain Cogn. 71 (3) (2009)
437451.
[42] S. Sumitani, et al., Activation of the prefrontal cortex during the Wisconsin Card
sorting Test as measured by multichannel near-infrared spectroscopy,
Neuropsychobiology 53 (2) (2006) 7076.
[43] A.Y. Tien, et al., Computerized wisconsin card sorting test: comparison with
manual administration, Kaohsiung J. Med. Sci. 12 (8) (1996) 479485.
[44] F. Scarpina, S. Tagini, The stroop color and word test, Front. Psychol. 8 (2017)
557.
[45] P. Vendrell, et al., The role of prefrontal regions in the Stroop task,
Neuropsychologia 33 (3) (1995) 341352.
[46] V. van Veen, C.S. Carter, The anterior cingulate as a conict monitor: fMRI and
ERP studies, Physiol. Behav. 77 (4-5) (2002) 477482.
[47] V. van Veen, et al., Anterior cingulate cortex, conict monitoring, and levels of
processing, Neuroimage 14 (6) (2001) 13021308.
[48] C.H. Hillman, E.M. Snook, G.J. Jerome, Acute cardiovascular exercise and ex-
ecutive control function, Int. J. Psychophysiol. 48 (3) (2003) 307314.
[49] S.M. Stark, et al., A task to assess behavioral pattern separation (BPS) in humans:
data from healthy aging and mild cognitive impairment, Neuropsychologia 51
(12) (2013) 24422449.
[50] J.W. Lacy, et al., Distinct pattern separation related transfer functions in human
CA3/dentate and CA1 revealed using high-resolution fMRI and variable mnemonic
similarity, Learn. Mem. 18 (1) (2011) 1518.
[51] M.A. Birkett, The trier social stress test protocol for inducing psychological stress,
J. Vis. Exp. 56 (2011).
[52] E. Van Cauter, R. Leproult, D.J. Kupfer, Eects of gender and age on the levels and
circadian rhythmicity of plasma cortisol, J. Clin. Endocrinol. Metab. 81 (7) (1996)
24682473.
[53] A.P. Yonelinas, et al., Separating the brain regions involved in recollection and
familiarity in recognition memory, J. Neurosci. 25 (11) (2005) 30023008.
[54] H. Lavretsky, et al., A pilot study of yogic meditation for family dementia care-
givers with depressive symptoms: eects on mental health, cognition, and telo-
merase activity, Int. J. Geriatr. Psychiatry 28 (1) (2013) 5765.
[55] X. Ding, et al., Improving creativity performance by short-term meditation, Behav.
Brain Funct. 10 (2014) 9.
[56] J. Montero-Marin, et al., Psychological eects of a 1-Month meditation retreat on
experienced meditators: the role of non-attachment, Front. Psychol. 7 (2016)
1935.
[57] E.L.B. Lykins, R.A. Baer, Psychological functioning in a sample of long-term
practitioners of mindfulness meditation, J. Cogn. Psychother. 23 (3) (2009)
226241.
[58] M.A. Rosenkranz, et al., Reduced stress and inammatory responsiveness in ex-
perienced meditators compared to a matched healthy control group,
Psychoneuroendocrinology 68 (2016) 117125.
[59] M.E. Kemeny, et al., Contemplative/emotion training reduces negative emotional
behavior and promotes prosocial responses, Emotion 12 (2) (2012) 338350.
[60] J.J. Arch, et al., Self-compassion training modulates alpha-amylase, heart rate
variability, and subjective responses to social evaluative threat in women,
Psychoneuroendocrinology 42 (2014) 4958.
[61] J.D. Creswell, et al., Brief mindfulness meditation training alters psychological and
neuroendocrine responses to social evaluative stress, Psychoneuroendocrinology
44 (2014) 112.
[62] S. Guendelman, S. Medeiros, H. Rampes, Mindfulness and emotion regulation:
insights from neurobiological, psychological, and clinical studies, Front. Psychol. 8
(2017) 220.
[63] M. Allen, et al., Cognitive-aective neural plasticity following active-controlled
mindfulness intervention, J. Neurosci. 32 (44) (2012) 1560115610.
[64] D.S. Lindsay, L.L. Jacoby, Stroop process dissociations: the relationship between
facilitation and interference, J. Exp. Psychol. Hum. Percept. Perform. 20 (2)
(1994) 219234.
[65] C.M. MacLeod, P.A. MacDonald, Interdimensional interference in the Stroop ef-
fect: uncovering the cognitive and neural anatomy of attention, Trends Cogn. Sci.
(Regul. Ed.) 4 (10) (2000) 383391.
[66] C.S. Carter, M. Mintun, J.D. Cohen, Interference and facilitation eects during
selective attention: an H215O PET study of Stroop task performance, Neuroimage
2 (4) (1995) 264272.
[67] E. Kalanthro, A. Henik, Individual but not fragile: individual dierences in task
control predict Stroop facilitation, Conscious. Cogn. 22 (2) (2013) 413419.
[68] A. Moore, P. Malinowski, Meditation, mindfulness and cognitive exibility,
Conscious. Cogn. 18 (1) (2009) 176186.
[69] H. Wenk-Sormaz, Meditation can reduce habitual responding, Altern. Ther. Health
Med. 11 (2) (2005) 4258.
[70] A. Chiesa, R. Calati, A. Serretti, Does mindfulness training improve cognitive
abilities? A systematic review of neuropsychological ndings, Clin. Psychol. Rev.
31 (3) (2011) 449464.
[71] R. Teper, M. Inzlicht, Meditation, mindfulness and executive control: the im-
portance of emotional acceptance and brain-based performance monitoring, Soc.
Cogn. Aect. Neurosci. 8 (1) (2013) 8592.
[72] A.P. Jha, et al., Examining the protective eects of mindfulness training on
working memory capacity and aective experience, Emotion 10 (1) (2010) 5464.
[73] M.D. Mrazek, et al., Mindfulness training improves working memory capacity and
GRE performance while reducing mind wandering, Psychol. Sci. 24 (5) (2013)
776781.
[74] D. Quach, K.E.J. Mano, K. Alexander, A randomized controlled trial examining the
eect of mindfulness meditation on working memory capacity in adolescents, J.
Adolesc. Health 58 (5) (2016) 489496.
[75] M. Boccia, L. Piccardi, P. Guariglia, The meditative mind: a comprehensive meta-
analysis of MRI studies, Biomed Res. Int. 2015 (2015) p. 419808.
[76] B.K. Holzel, et al., Investigation of mindfulness meditation practitioners with
voxel-based morphometry, Soc. Cogn. Aect. Neurosci. 3 (1) (2008) 5561.
[77] M.K. Leung, et al., Increased gray matter volume in the right angular and posterior
parahippocampal gyri in loving-kindness meditators, Soc. Cogn. Aect. Neurosci.
8 (1) (2013) 3439.
[78] E. Luders, et al., Meditation eects within the hippocampal complex revealed by
voxel-based morphometry and cytoarchitectonic probabilistic mapping, Front.
Psychol. 4 (2013) 398.
[79] E. Luders, et al., The underlying anatomical correlates of long-term meditation:
larger hippocampal and frontal volumes of gray matter, Neuroimage 45 (3) (2009)
672678.
[80] H. Murakami, et al., The structure of mindful brain, PLoS One 7 (9) (2012) p
e46377.
[81] J. Fell, N. Axmacher, S. Haupt, From alpha to gamma: electrophysiological cor-
relates of meditation-related states of consciousness, Med. Hypotheses 75 (2)
(2010) 218224.
[82] T. Lomas, I. Ivtzan, C.H. Fu, A systematic review of the neurophysiology of
mindfulness on EEG oscillations, Neurosci. Biobehav. Rev. 57 (2015) 401410.
[83] B.S. Oken, et al., Meditation in stressed older adults: improvements in self-rated
mental health not paralleled by improvements in cognitive function or physiolo-
gical measures, Mindfulness (N Y) 8 (3) (2017) 627638.
[84] Y. Singh, R. Sharma, A. Talwar, Immediate and long-term eects of meditation on
acute stress reactivity, cognitive functions, and intelligence, Altern. Ther. Health
Med. 18 (6) (2012) 4653.
[85] K.C. Spadaro, D.F. Hunker, Exploring the eects of an online asynchronous
mindfulness meditation intervention with nursing students on stress, mood, and
cognition: a descriptive study, Nurse Educ. Today 39 (2016) 163169.
[86] M. Speca, et al., A randomized, wait-list controlled clinical trial: the eect of a
mindfulness meditation-based stress reduction program on mood and symptoms of
stress in cancer outpatients, Psychosom. Med. 62 (5) (2000) 613622.
[87] K.W. Brown, R.M. Ryan, The benets of being present: mindfulness and its role in
psychological well-being, J. Pers. Soc. Psychol. 84 (4) (2003) 822848.
[88] A.J. Waters, et al., Associations between mindfulness and implicit cognition and
self-reported aect, Subst. Abus. 30 (4) (2009) 328337.
[89] I. Nyklicek, K.F. Kuijpers, Eects of mindfulness-based stress reduction interven-
tion on psychological well-being and quality of life: is increased mindfulness in-
deed the mechanism? Ann. Behav. Med. 35 (3) (2008) 331340.
[90] M. Sperduti, P. Martinelli, P. Piolino, A neurocognitive model of meditation based
on activation likelihood estimation (ALE) meta-analysis, Conscious. Cogn. 21 (1)
(2012) 269276.
[91] E. Adler, et al., Impact of a mindfulness-based weight-loss intervention on sleep
quality among adults with obesity: data from the SHINE randomized controlled
trial, J. Altern. Complement. Med. 23 (3) (2017) 188195.
[92] D.S. Black, et al., Mindfulness meditation and improvement in sleep quality and
daytime impairment among older adults with sleep disturbances a randomized
clinical trial, JAMA Intern. Med. 175 (4) (2015) 494501.
[93] C.R. Gross, et al., Mindfulness-based stress reduction versus pharmacotherapy for
chronic primary insomnia: a randomized controlled clinical trial, Explore-J. Sci.
Heal. 7 (2) (2011) 7687.
[94] D.J. Buysse, et al., The Pittsburgh Sleep Quality Index: a new instrument for
psychiatric practice and research, Psychiatry Res. 28 (2) (1989) 193213.
[95] T. Mollayeva, et al., The Pittsburgh sleep quality index as a screening tool for sleep
dysfunction in clinical and non-clinical samples: a systematic review and meta-
analysis, Sleep Med. Rev. 25 (2016) 5273.
[96] S.A. Johns, et al., Randomized controlled pilot study of mindfulness-based stress
reduction for persistently fatigued cancer survivors, Psychooncology 24 (8) (2015)
885893.
[97] A.S. Moss, et al., Eects of an 8-week meditation program on mood and anxiety in
patients with memory loss, J. Altern. Complement. Med. 18 (1) (2012) 4853.
[98] K.A. Rimes, J. Wingrove, Mindfulness-based cognitive therapy for people with
chronic fatigue syndrome still experiencing excessive fatigue after cognitive be-
haviour therapy: a pilot randomized study, Clin. Psychol. Psychother. 20 (2)
(2013) 107117.
[99] A. Bansal, A. Mittal, V. Seth, Osho dynamic meditationseect on serum cortisol
level, J. Clin. Diagn. Res. 10 (11) (2016) CC05CC08.
[100] Y. Fan, Y.Y. Tang, M.I. Posner, Cortisol level modulated by integrative meditation
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
219
in a dose-dependent fashion, Stress Health 30 (1) (2014) 6570.
[101] W. Turakitwanakan, C. Mekseepralard, P. Busarakumtragul, Eects of mindfulness
meditation on serum cortisol of medical students, J. Med. Assoc. Thai. 96 (Suppl.
1) (2013) S90S95.
[102] C. Kirschbaum, K.M. Pirke, D.H. Hellhammer, TheTrier Social Stress Test’–a tool
for investigating psychobiological stress responses in a laboratory setting,
Neuropsychobiology 28 (1-2) (1993) 7681.
[103] V. Engert, et al., Specic reduction in cortisol stress reactivity after social but not
attention-based mental training, Sci. Adv. 3 (10) (2017) p. e1700495.
[104] B.M. Kudielka, D.H. Hellhammer, S. Wust, Why do we respond so dierently?
Reviewing determinants of human salivary cortisol responses to challenge,
Psychoneuroendocrinology 34 (1) (2009) 218.
[105] J. Campbell, U. Ehlert, Acute psychosocial stress: does the emotional stress re-
sponse correspond with physiological responses? Psychoneuroendocrinology 37
(8) (2012) 11111134.
[106] J. Hellhammer, M. Schubert, The physiological response to Trier Social Stress Test
relates to subjective measures of stress during but not before or after the test,
Psychoneuroendocrinology 37 (1) (2012) 119124.
[107] P. Sedlmeier, et al., The psychological eects of meditation: a meta-analysis,
Psychol. Bull. 138 (6) (2012) 11391171.
[108] R. Marciniak, et al., Eect of meditation on cognitive functions in context of aging
and neurodegenerative diseases, Front. Behav. Neurosci. 8 (2014) 17.
[109] C.B. Kirwan, C.E. Stark, Overcoming interference: an fMRI investigation of pattern
separation in the medial temporal lobe, Learn. Mem. 14 (9) (2007) 625633.
[110] N.T. Van Dam, et al., Reiterated concerns and further challenges for mindfulness
and meditation research: a reply to Davidson and dahl, Perspect. Psychol. Sci. 13
(1) (2018) 6669.
[111] I.B. Mauss, M.D. Robinson, Measures of emotion: a review, Cogn. Emot. 23 (2)
(2009) 209237.
[112] C.E. Parsons, et al., Home practice in mindfulness-based cognitive therapy and
mindfulness-based stress reduction: a systematic review and meta-analysis of
participantsmindfulness practice and its association with outcomes, Behav. Res.
Ther. 95 (2017) 2941.
[113] N.A. Farb, A.K. Anderson, Z.V. Segal, The mindful brain and emotion regulation in
mood disorders, Can. J. Psychiatry 57 (2) (2012) 7077.
[114] S.G. Hofmann, et al., The eect of mindfulness-based therapy on anxiety and
depression: a meta-analytic review, J. Consult. Clin. Psychol. 78 (2) (2010)
169183.
J.C. Basso et al. Behavioural Brain Research 356 (2019) 208–220
220
... Most studies on mindfulness are based on adult samples and support beneficial effects of mindfulness in a variety of outcomes: Regarding psychological symptoms, current research shows the most promising results of mindfulnessbased interventions (MBIs) in reducing symptoms of depression and anxiety (Basso et al., 2019;Blanck et al., 2018;Goldberg et al., 2018;Hilton et al., 2017;Hofmann & Gomez, 2017;Khoury et al., 2013;Wielgosz et al., 2019). This was further supported by a recent review of meta-analyses by Goldberg et al. (2022). ...
... This was further supported by a recent review of meta-analyses by Goldberg et al. (2022). Furthermore, MBIs may ameliorate cognitive functions (Basso et al., 2019), schizophrenia spectrum disorder (Jansen et al., 2020), quality of life, and pain management (Hilton et al., 2017). The application of MBIs has also been researched in different settings, reaching from group programs (e.g., MBCT;Segal et al., 2002) to individual therapy (Mander et al., 2019), as well as stand-alone interventions (Blanck et al., 2018). ...
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Objectives Based on the current literature, mindfulness seems to have positive effects on mental and physical health not only in adults but also in children and adolescents. Research should further investigate these findings and needs properly validated measures. Therefore, the aim of the present study is to validate a German version of the Child and Adolescent Mindfulness Measure (CAMM). Methods A sample of 248 children and adolescents (10–19 years, M = 14.85, SD = 2.55, 58.87% females) filled in the CAMM, measures of self-compassion, internalizing (depression and anxiety) and externalizing (destructiveness and boundary violations) symptoms, and quality of life. A confirmatory factor analysis was conducted to test the original factor structure. Also, internal consistency, convergent validity, and possible gender and age group differences were examined. Results Results did not support the original one-factor structure of the CAMM with ten items but indicated a one-factor structure with seven items for the German version of the CAMM. Internal consistency was good with Cronbach’s α = .83 and McDonald’s ω = .85. Convergent validity of the seven-item scale was indicated by moderate correlations in expected directions with self-compassion, internalizing and externalizing symptoms, and quality of life. Conclusions The German seven-item version of the CAMM seems to be a promising tool to measure mindfulness in German-speaking children and adolescents.
... Most of the time, meditation is considered to have a positive effect on mood. Specifically, daily meditation does help to reduce negative mood state and stress (Basso et al., 2019). Such a reference gives the research a basic understanding of meditation effects, especially on moods. ...
... The benefits of meditation on working memory have been reported in one recent meta-analytic study of cognitively healthy and impaired older adults aged 60 years or above (Chan et al., 2019), suggesting the potential benefits of mindfulness training for improving working memory capacity in older adults. Additionally, the beneficial effects of meditation on episodic memory have been observed (Van Vugt et al., 2012;Basso et al., 2019;Nyhus et al., 2019), suggesting the potential benefits of meditation for improving episodic memory capacity. ...
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Background Aging is associated with cognitive decline, increased risk for dementia, and deterioration of brain function. Modifiable lifestyle factors (e.g., exercise, meditation, and social interaction) have been proposed to benefit memory and brain function. However, previous studies have focused on a single exercise modality or a single lifestyle factor. Consequently, the effect of a more comprehensive exercise program that combines multiple exercise modalities and lifestyle factors, as well as examines potential mediators and moderators, on cognitive function and brain health in late middle-aged and older adults remains understudied. This study's primary aim is to examine the effect of a multi-domain exercise intervention on memory and brain function in cognitively healthy late middle-aged and older adults. In addition, we will examine whether apolipoprotein E ( ApoE ) genotypes, physical fitness (i.e., cardiovascular fitness, body composition, muscular fitness, flexibility, balance, and power), and brain-derived neurotrophic factor (BDNF) moderate and mediate the exercise intervention effects on memory and brain function. Methods The Western-Eastern Brain Fitness Integration Training (WE-BFit) is a single-blinded, double-arm, 6-month randomized controlled trial. One hundred cognitively healthy adults, aged 45–70 years, with different risks for Alzheimer's disease (i.e., ApoE genotype) will be recruited and randomized into either a multi-domain exercise group or an online educational course control group. The exercise intervention consists of one 90-min on-site and several online sessions up to 60 min per week for 6 months. Working memory, episodic memory, physical fitness, and BDNF will be assessed before and after the 6-month intervention. The effects of the WE-BFit on memory and brain function will be described and analyzed. We will further examine how ApoE genotype and changes in physical fitness and BDNF affect the effects of the intervention. Discussion WE-BFit is designed to improve memory and brain function using a multi-domain exercise intervention. The results will provide insight into the implementation of an exercise intervention with multiple domains to preserve memory and brain function in adults with genetic risk levels for Alzheimer's disease. Clinical trial registration ClinicalTrials.gov , identifier: NCT05068271.
... As such, smoking cessation interventions may need to incorporate cognitive-behavioral strategies to help youth identify and apply alternate stress-reducing tools [45]. Mindfulness-based practices show promise for enhancing smoking cessation via response inhibition, improved mood/affect, and emotion regulation [46][47][48][49]. However, more research is needed to understand the impact of mindfulness-based practices on smoking cessation, including the mechanisms through which these approaches may be effective, and for whom. ...
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Objectives In the United States, up to 70% of youth experiencing homelessness smoke cigarettes. Many are interested in quitting; however, little is known about psychosocial factors influencing smoking relapse in this population. This study, part of a larger project to develop an optimized smoking cessation intervention for youth experiencing homelessness, aimed to describe how psychosocial factors influence smoking relapse in this group. Methods This study describes the smoking relapse experiences of 26 youth tobacco users, aged 14–24 years, who were recruited from a homeless drop-in center in Ohio. We conducted semi-structured interviews to understand how stress, opportunity, and coping contribute to smoking relapse. Results Five themes emerged from the data: (1) smoking as a lapse in emotional self-regulation in response to stress; (2) smoking as active emotional self-regulation in response to stress; (3) social opportunities facilitate smoking in the context of emotion-focused stress coping; (4) problem-focused stress coping; and (5) opportunity facilitates smoking relapse. Conclusions Stress was a primary driver of smoking relapse among youth experiencing homelessness, yet social and environmental opportunities to smoke also precipitated relapse. Interventions to improve abstinence among this population should target foundational stressors, coping skills, social supports, and nicotine dependence.
... These meta-analyses mostly review long-term meditation intervention and longterm mindfulness-based interventions, and the consensus is that an ideal long-term meditation intervention for finding effects on common psychological constructs is an 8week program (Basso et al., 2019). Short-term meditation interventions have been studied too. ...
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This was an experimental between-subjects design utilizing single-session mindfulness meditation to assess effects on sustained attention and self-concept. Electroencephalogram was incorporated to further test how EEG power spectral density in decibels differed between groups when sustaining attention during the Psychomotor Vigilance Task and a task in which participants focused on sustaining the Troxler effect optical illusion (compared to resting baseline). Overall, this study aimed to test the underlying theoretical proposition of Graziano's Attention Schema Theory of Consciousness, and results do not provide support. Although there were null findings, there were some limitations that should be acknowledged when taking this study into account.
... 26 Düzenli yapılan meditasyon ile duygu durum bozuklukları ve anksiyete düzeylerinin azaldığı gösterilmiştir. 29 Bunun yanı sıra meditasyonun ağrı yönetimi, fibromiyalji, gerilim tipi baş ağrısı, irritabl bağırsak sendromu, ülser, uykusuzluk, premenstrüel sendrom, infertilite, ilaç bağımlılığı ve yaşam beklentisi üzerine de olumlu etkisi olduğu bilinmektedir. 26 Asanalar: Sanskritçe bir kelime olan "asana" kelimesi "yoga duruşu/pozu" demektir. ...
Article
Acupuncture stimulation can protect the brain against caffeine-induced sleep disruption. This study investigated whether electroacupuncture stimulation acupuncture point HT7 alleviates sleep disruption by regulating mBDNF and ER stress in the medial septum. Acute exposure to caffeine (15 mg/kg, i.p.) increased the wake time and decreased REM sleep, which HT7 stimulation alleviated. HT7 stimulation ameliorated the acute caffeine exposure-induced increase in the expression of BiP, an endoplasmic reticulum stress response protein, in the rat medial septum. Interestingly, HT7 stimulation induced the expression of mBDNF and pTrkB in the medial septum. The next experiment investigated whether TrkB phosphorylated by HT7 stimulation induced BiP expression in the rat medial septum. Before electroacupuncture stimulation at HT7, ANA-12 was administered to caffeine-treated rats. In rats administered ANA-12 in the medial septum, HT7 stimulation did not reduce BiP expression. These findings suggest that HT7 stimulation improves wake time and REM sleep dysfunction by regulating the BDNF-mediated endoplasmic reticulum stress response in the medial septum. These results indicate that the alleviation of endoplasmic reticulum stress in the medial septum by HT7 stimulation and the subsequent amelioration of insomnia may depend on phosphorylated TrkB activation.
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Precis: 63% of glaucoma patients agreed to 45-60 minutes of daily meditation. Predictors of accepting meditation included previous meditation practice, a diagnosis of glaucoma <1 year, and having a marital status of "single". Purpose: To explore patients' acceptance and barriers towards 45-60 minutes daily meditation for glaucoma management and to identify glaucoma patients with higher perceived stress levels who may benefit more from meditation practice. Methods: Glaucoma patients attending the Royal Victorian Eye and Ear Hospital, Melbourne, Australia outpatient department were invited to complete a patient survey. This explored if patients would agree to 45-60 minutes of daily meditation and included the Determinants of Meditation Practice Inventory and Perceived Stress Scale questionnaires. Questionnaire scores were compared across participants' clinical and demographic characteristics using student's T-Test, ANOVA, and multiple-linear-regression analysis. Results: Of the 123 eligible patients screened, one hundred completed the survey (81.3%). Sixty-three (63%) patients would agree to 45-60 minutes of daily meditation if advised by their doctor. Univariate analysis showed increased acceptance of meditation (lower Determinants of Meditation Practice Inventory scores) to be associated with agreeing to meditate 45-60 minutes daily (P=0.002), currently or previously practicing meditation (P=0.006 and P=0.0004 respectively), and having a marital status of "single" (P=0.02). Multi variate regression analysis showed previous meditation practice and a glaucoma diagnosis of <1 year to be predictive of accepting meditation (P=0.01 and P=0.03 respectively). There were no predictive factors of Perceived Stress Scale scores. Conclusion: Given the high acceptance rate of 45-60 minutes daily meditation (63% of glaucoma patients sampled), this may be recommended for benefit of patients. Patients who have previously meditated, have a relatively new diagnosis of glaucoma, and are single (marital status) were more accepting of meditation practice.
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Background Meditation is a conscious mental discipline, that has been implicated in the relaxation response. The mechanism behind such a relaxing effect is psychoneuroimmunology (PNI), based on the interaction between mind, physical health, and self-healing; that conceptualizes that stress and an individual’s emotional state led to predisposition to diseases. Research to date suggests that meditation may play an active role in remodeling the imbalance between mind and body by modulating the psychoneuroimmunological effects of stress. However, to date, the multi-dimensional psychoneuroimmune aspects of meditation together have not been completely explicated. An evidence-based mechanism has been framed for the first time in India to explain the psychoneuroimmunology of regular and long-term meditation practice. Summary Present evidence-based mechanism confirms prefrontal cortex (PFC) acts as a ‘Functional Connectome’ where psycho-neuro-immune aspects of meditation function simultaneously to exert positive benefits in the regulation of cognitive and emotional behavior. Also, this mechanism will help us to understand how human augmentation with lifestyle modification fosters brain plasticity to overcome various neuropsychiatric illnesses. Key Message Meditation is a scientific tool against neuro-psychiatric illnesses.
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Background There have been mixed reports on the beneficial effects of meditation in cardiovascular disease (CVD), which is widely considered the leading cause of death worldwide. Methods To clarify the role of meditation in modulating the heart-brain axis, we implemented an extreme phenotype strategy, i.e., Tibetan monks (BMI > 30) who practised 19.20 ± 7.82 years of meditation on average and their strictly matched non-meditative Tibetan controls. Hypothesis-free advanced proteomics strategies (Data Independent Acquisition and Targeted Parallel Reaction Monitoring) were jointly applied to systematically investigate and target the plasma proteome underlying meditation. Total cholesterol, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (Apo B) and lipoprotein (a) [Lp(a)] as the potential cardiovascular risk factors were evaluated. Heart rate variability (HRV) was assessed by electrocardiogram. Findings Obesity, hypertension, and reduced HRV is offset by long-term meditation. Notably, meditative monks have blood pressure and HRV comparable to their matched Tibetan controls. Meditative monks have a protective plasma proteome, related to decreased atherosclerosis, enhanced glycolysis, and oxygen release, that confers resilience to the development of CVD. In addition, clinical risk factors in plasma were significantly decreased in monks compared with controls, including total cholesterol, LDL-C, Apo B, and Lp(a). Interpretation To our knowledge, this work is the first well-controlled proteomics investigation of long-term meditation, which opens up a window for individuals characterized by a sedentary lifestyle to improve their cardiovascular health with an accessible method practised for more than two millennia. Funding See the Acknowledgements section.
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In response to our article, Davidson and Dahl offer commentary and advice regarding additional topics crucial to a comprehensive prescriptive agenda for future research on mindfulness and meditation. Their commentary raises further challenges and provides an important complement to our article. More consideration of these issues is especially welcome because limited space precluded us from addressing all relevant topics. While we agree with many of Davidson and Dahl’s suggestions, the present reply (a) highlights reasons why the concerns we expressed are still especially germane to mindfulness and meditation research (even though those concerns may not be entirely unique) and (b) gives more context to other issues posed by them. We discuss special characteristics of individuals who participate in mindfulness and meditation research and focus on the vulnerability of this field inherent in its relative youthfulness compared to other more mature scientific disciplines. Moreover, our reply highlights the serious consequences of adverse experiences suffered by a significant subset of individuals during mindfulness and other contemplative practices. We also scrutinize common contemporary applications of mindfulness and meditation to illness, and some caveats are introduced regarding mobile technologies for guidance of contemplative practices.
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Psychosocial stress is a public health burden in modern societies. Chronic stress–induced disease processes are, in large part, mediated via the activation of the hypothalamic-pituitary-adrenal (HPA) axis and the sympathetic-adrenal-medullary system. We asked whether the contemplative mental training of different practice types targeting attentional, socio-affective (for example, compassion), or socio-cognitive abilities (for example, perspective-taking) in the context of a 9-month longitudinal training study offers an effective means for psychosocial stress reduction. Using a multimethod approach including subjective, endocrine, autonomic, and immune markers and testing 313 participants in a standardized psychosocial laboratory stressor, we show that all three practice types markedly reduced self-reported stress reactivity in healthy participants. However, only the training of intersubjective skills via socio-affective and socio-cognitive routes attenuated the physiological stress response, specifically the secretion of the HPA axis end-product cortisol, by up to 51%. The assessed autonomic and innate immune markers were not influenced by any practice type. Mental training focused on present-moment attention and interoceptive awareness as implemented in many mindfulness-based intervention programs was thus limited to stress reduction on the level of self-report. However, its effectiveness was equal to that of intersubjective practice types in boosting the association between subjective and endocrine stress markers. Our results reveal a broadly accessible low-cost approach to acquiring psychosocial stress resilience. Short daily intersubjective practice may be a promising method for minimizing the incidence of chronic social stress–related disease, thereby reducing individual suffering and relieving a substantial financial burden on society.
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Background: Like other complex psychosocial interventions, mindfulness-based treatments comprise various modality specific components as well as nonspecific therapeutic ingredients that collectively contribute to efficacy. Consequently, the isolated effects of mindfulness strategies per se remain unclear. Methods: Using a randomized double-blind design, we compared the isolated effects of 11-minutes of “supervised” mindfulness instruction against a closely matched active control (relaxation) on subjective, physiological, and behavioral indices of maladaptive alcohol responding in drinkers at risk of harm from alcohol use (n = 68). Simple follow-up instructions on strategy use were provided, but practice was unsupervised and not formally monitored. Results: Both groups showed acute reductions in craving after training, although a trend group x time interaction (P = .056) suggested that this reduction was greater in the relaxation group (d = 0.722 P < .001) compared with the mindfulness group (d= 0.317, P = .004). Furthermore, upregulation of parasympathetic activity was found after relaxation (d = 0.562; P < .001) but not mindfulness instructions (d = 0.08; P > .1; group x time interaction: P = .009). By contrast, only the mindfulness group showed a reduction in past-week alcohol consumption at 7-day follow-up (-9.31 units, d = 0.593, P < .001), whereas no significant reduction was seen in the relaxation group (-3.00 units, d = 0.268, P > .1; group x time interaction: P = .026). Conclusion: Very brief mindfulness practice can significantly reduce alcohol consumption among at-risk drinkers, even with minimal encouragement to use this strategy outside of the experimental context. The effects on consumption may therefore represent a lower bound of efficacy of “ultra-brief” mindfulness instructions in hazardous drinkers, at least at short follow-up intervals.
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Mindfulness-Based Cognitive Therapy (MBCT) and Mindfulness-Based Stress Reduction (MBSR) emphasize the importance of mindfulness practice at home as an integral part of the program. However, the extent to which participants complete their assigned practice is not yet clear, nor is it clear whether this practice is associated with positive outcomes. For this systematic review and meta-analysis, searches were performed using Scopus and PubMed for studies published through to the end of 2015, reporting on formal home practice of mindfulness by MBSR or MBCT participants. Across 43 studies (N = 1427), the pooled estimate for participants' home practice was 64% of the assigned amount, equating to about 30 minutes per day, six days per week [95% CI 60–69%]. There was substantial heterogeneity associated with this estimate. Across 28 studies (N = 898), there was a small but significant association between participants’ self-reported home practice and intervention outcomes (r = 0·26, 95% CI 0·19,–0·34). MBSR and MBCT participants report completing substantial formal mindfulness practice at home over the eight-week intervention, albeit less than assigned amounts. There is a small but significant association between the extent of formal practice and positive intervention outcomes for a wide range of participants.
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The Stroop Colour and Word Test (SCWT) is a neuropsychological test extensively used to assess the ability to inhibit cognitive interference that occurs when the processing of a specific stimulus feature impedes the simultaneous processing of a second stimulus attribute, well-known as the Stroop Effect. The aim of the present work is to verify the theoretical adequacy of the various scoring methods used to measure the Stroop effect. We present a systematic review of studies that have provided normative data for the SCWT. We referred to both electronic databases (i.e. PubMed, Scopus, Google Scholar) and citations. Our findings show that while several scoring methods have been reported in literature, none of the reviewed methods enables us to fully assess the Stroop effect. Furthermore, we discuss several normative scoring methods from the Italian panorama as reported in literature. We claim for an alternative scoring method which takes into consideration both speed and accuracy of the response. Finally, we underline the importance of assessing the performance in all Stroop Test conditions (word reading, colour naming, named colour-word).
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There is increasing interest in the beneficial clinical effects of mindfulness-based interventions (MBIs). Research has demonstrated their efficacy in a wide range of psychological conditions characterized by emotion dysregulation. Neuroimaging studies have evidenced functional and structural changes in a myriad of brain regions mainly involved in attention systems, emotion regulation, and self-referential processing. In this article we review studies on psychological and neurobiological correlates across different empirically derived models of research, including dispositional mindfulness, mindfulness induction, MBIs, and expert meditators in relation to emotion regulation. From the perspective of recent findings in the neuroscience of emotion regulation, we discuss the interplay of top-down and bottom-up emotion regulation mechanisms associated with different mindfulness models. From a phenomenological and cognitive perspective, authors have argued that mindfulness elicits a “mindful emotion regulation” strategy; however, from a clinical perspective, this construct has not been properly differentiated from other strategies and interventions within MBIs. In this context we propose the distinction between top-down and bottom-up mindfulness based emotion regulation strategies. Furthermore, we propose an embodied emotion regulation framework as a multilevel approach for understanding psychobiological changes due to mindfulness meditation regarding its effect on emotion regulation. Finally, based on clinical neuroscientific evidence on mindfulness, we open perspectives and dialogues regarding commonalities and differences between MBIs and other psychotherapeutic strategies for emotion regulation.
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Emerging evidences have shown that one form of mental training—mindfulness meditation, can improve attention, emotion regulation and cognitive performance through changing brain activity and structural connectivity. However, whether and how the short-term mindfulness meditation alters large-scale brain networks are not well understood. Here, we applied a novel data-driven technique, the multivariate pattern analysis (MVPA) to resting-state fMRI (rsfMRI) data to identify changes in brain activity patterns and assess the neural mechanisms induced by a brief mindfulness training—integrative body–mind training (IBMT), which was previously reported in our series of randomized studies. Whole brain rsfMRI was performed on an undergraduate group who received 2 weeks of IBMT with 30 min per session (5 h training in total). Classifiers were trained on measures of functional connectivity in this fMRI data, and they were able to reliably differentiate (with 72% accuracy) patterns of connectivity from before vs. after the IBMT training. After training, an increase in positive functional connections (60 connections) were detected, primarily involving bilateral superior/middle occipital gyrus, bilateral frontale operculum, bilateral superior temporal gyrus, right superior temporal pole, bilateral insula, caudate and cerebellum. These results suggest that brief mental training alters the functional connectivity of large-scale brain networks at rest that may involve a portion of the neural circuitry supporting attention, cognitive and affective processing, awareness and sensory integration and reward processing.
Article
Background: Medical management of acute pain among hospital inpatients may be enhanced by mind-body interventions. Objective: We hypothesized that a single, scripted session of mindfulness training focused on acceptance of pain or hypnotic suggestion focused on changing pain sensations through imagery would significantly reduce acute pain intensity and unpleasantness compared to a psychoeducation pain coping control. We also hypothesized that mindfulness and suggestion would produce significant improvements in secondary outcomes including relaxation, pleasant body sensations, anxiety, and desire for opioids, compared to the control condition. Methods: This three-arm, parallel-group randomized controlled trial conducted at a university-based hospital examined the acute effects of 15-min psychosocial interventions (mindfulness, hypnotic suggestion, psychoeducation) on adult inpatients reporting "intolerable pain" or "inadequate pain control." Participants (N = 244) were assigned to one of three intervention conditions: mindfulness (n = 86), suggestion (n = 73), or psychoeducation (n = 85). Key results: Participants in the mind-body interventions reported significantly lower baseline-adjusted pain intensity post-intervention than those assigned to psychoeducation (p < 0.001, percentage pain reduction: mindfulness = 23%, suggestion = 29%, education = 9%), and lower baseline-adjusted pain unpleasantness (p < 0.001). Intervention conditions differed significantly with regard to relaxation (p < 0.001), pleasurable body sensations (p = 0.001), and desire for opioids (p = 0.015), but all three interventions were associated with a significant reduction in anxiety (p < 0.001). Conclusions: Brief, single-session mind-body interventions delivered by hospital social workers led to clinically significant improvements in pain and related outcomes, suggesting that such interventions may be useful adjuncts to medical pain management. Trial registration: Trial Registry: ClinicalTrials.gov ; registration ID number: NCT02590029 URL: https://clinicaltrials.gov/ct2/show/NCT02590029.
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Background and objective: Sleep disturbance is a common problem among adults with obesity. Mindfulness interventions have been shown to improve sleep quality in various populations but have not been investigated in adults with obesity. The aim of this study was to compare the effects of a mindfulness-based weight-loss intervention with an active control on self-reported sleep quality among adults with obesity. Method: This study was a secondary analysis of a randomized controlled trial and included 194 adults with a body mass index in the range 30-45 kg/m(2). The treatment intervention included mindfulness-based eating and stress-management practices, and the active control intervention included training in progressive muscle relaxation (PMR). Both groups received identical diet and exercise guidelines in 17 group sessions conducted over 5.5 months that were matched for time, attention, and social support. The primary outcome of this analysis was between-group change in self-reported sleep quality, which was assessed using the Pittsburgh Sleep Quality Index (PSQI) global score at baseline and at 6, 12, and 18 months. Results: Between-group differences in mean PSQI change scores in the mindfulness group (n = 100) compared to the control group (n = 94) were -0.27 (-0.68, 1.22; p = 0.58) at 6 months, -0.57 (-0.35, 1.50; p = 0.22) at 12 months, and -0.50 (-0.53, 1.53; p = 0.34) at 18 months, all in the direction of more sleep improvement in the mindfulness group but none reaching statistical significance. In the mindfulness group, average weekly minutes of meditation practice time was associated with improved sleep quality from baseline to 6 months. Conclusions: No statistically significant evidence was found that a weight-loss program that incorporates mindfulness improves self-reported sleep quality compared to a control diet/exercise intervention that included PMR. Within the mindfulness group, average weekly minutes of mindfulness practice was associated with improved sleep quality.
Article
A broad range of mind-body therapies (MBTs) are used by the public today, and a growing body of clinical and basic sciences research has resulted in evidence-based integration of many MBTs into clinical practice. Basic sciences research has identified some of the physiological correlates of MBT practices, leading to a better understanding of the processes by which emotional, cognitive and psychosocial factors can influence health outcomes and well-being. In particular, results from functional genomics and neuroimaging describe some of the processes involved in the mind-body connection and how these can influence health outcomes. Functional genomic and neurophysiological correlates of MBTs are reviewed, detailing studies showing changes in sympathetic nervous system activation of gene transcription factors involved in immune function and inflammation, electroencephalographic and neuroimaging studies on MBT practices, and persistent changes in neural function and morphology associated with these practices. While the broad diversity of study designs and MBTs studied presents a patchwork of results requiring further validation through replication and longitudinal studies, clear themes emerge for MBTs as immunomodulatory, with effects on leukocyte transcription and function related to inflammatory and innate immune responses, and neuromodulatory, with effects on brain function and morphology relevant for attention, learning, and emotion regulation. By detailing the potential mechanisms of action by which MBTs may influence health outcomes, the data generated by these studies have contributed significantly towards a better understanding of the biological mechanisms underlying MBTs.