neural correlates of focused attention and cognitive monitoring in meditation

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Brain Research Bulletin 82 (2010) 4656

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Brain Research Bulletin

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Research report

Neural correlates of focused attention and cognitive monitoring in meditation

Antonietta Manna a,b,,1, Antonino Raffone c,e,1, Mauro Gianni Perrucci a,b, Davide Nardo c,d,Antonio Ferretti a,b, Armando Tartaro a,b, Alessandro Londei c,d, Cosimo Del Gratta a,b,Marta Olivetti Belardinelli c,d, Gian Luca Romani a,b

a ITAB, Institute for Advanced Biomedical Technologies, G. DAnnunzio University Foundation, Chieti, Italyb Department of Clinical Sciences and Bioimaging, University of Chieti, Chieti, Italyc Department of Psychology, La Sapienza University, Rome, Italyd ECONA (Interuniversity Center for Cognitive Processing in Natural and Artificial Systems), Rome, Italye Perceptual Dynamics Laboratory, RIKEN Brain Science Institute, Wako-shi, Saitama, Japan

a r t i c l e i n f o

Article history:

Received 4 September 2009

Received in revised form 1 March 2010

Accepted 2 March 2010

Available online 16 March 2010

Keywords:

Meditation

Attention

Consciousness

Prefrontal cortex

Cognitive control

a b s t r a c t

Meditation refers to a family of complex emotional and attentional regulatory practices, which can be

classified into two main styles focused attention (FA) and open monitoring (OM) involving different

attentional, cognitive monitoringand awareness processes. In a functionalmagnetic resonance study we

originally characterized and contrasted FA and OM meditation forms withinthe same experiment, by an

integrated FAOM design. Theravada Buddhist monks, expert in both FA and OM meditation forms, and

lay novices with 10 days of meditation practice, participated in the experiment. Our evidence suggests

thatexpert meditatorscontrol cognitive engagement in conscious processing of sensory-related, thought

and emotion contents, by massive self-regulation of fronto-parietal and insular areas in the left hemi-

sphere, in a meditation state-dependent fashion. We also found that anterior cingulate and dorsolateral

prefrontal cortices play antagonist roles in the executive control of the attention setting in meditation

tasks. Our findings resolve the controversy between the hypothesis that meditative states areassociated

to transient hypofrontality or deactivation of executive brain areas, and evidence about the activation of

executive brain areas in meditation. Finally, our study suggests that a functional reorganization of brain

activity patterns for focused attention and cognitive monitoring takes place with mental practice, and

that meditation-related neuroplasticity is crucially associated to a functional reorganization of activity

patterns in prefrontal cortex and in the insula.

2010 Elsevier Inc. All rights reserved.

1. Introduction

Meditation can be conceptualized as a family of complex emo-

tional and attentional regulatory practices, involving different

attentional, cognitive monitoring and awareness processes. Many

recent behavioral, electroencephalographic and neuroimaging

studies have revealed the importance of investigating meditation

states andtraits to achieve an increasedunderstanding of cognitive

and affective neuroplasticity, attention and self-awareness, as wellas for relevant clinical implications[7,28].

Given that regulation of attention is the central commonality

across the many different meditation methods [14], medita-

Correspondingauthorat: Departmentof Clinical Sciencesand Bioimaging, ITAB,

Institute of Advanced Biomedical Technologies, G. DAnnunzio University, via Dei

Vestini, Campus Universitario, 66100 Chieti, Italy, Tel.: +39 0871 3556952;

fax: +39 0871 3556930.

E-mail address:[email protected](A. Manna).1 These authors have contributed equally to this work.

tion practices can be usefully classified into two main styles

focused attention (FA) and open monitoring (OM) depend-

ing on how the attentional processes are directed [7,28]. In the

FA (concentrative) style, attention is focused on an intended

object in a sustained fashion. The second style, OM (mindfulness-

based) meditation, involves the non-reactive monitoring of the

content of experience from moment to moment, primarily as

a means to recognize the nature of emotional and cognitive

patterns.FA meditation entails the capacities of monitoring the focus

of attention and detecting distraction, disengaging attention from

the source of distraction, and (re)directing and engaging atten-

tion to the intended object[28].These attentional and monitoring

functions have been related to dissociable systems in the brain

involved in conflict monitoring, selective and sustained attention

[12,28,32,40]. A study with a binocular rivalry paradigm showed

that Tibetan Buddhist monks were able to perceive a stable, super-

imposed percept of two dissimilar, competing images presented to

separate eyes for a longer duration both during and after FA med-

itation, but not during and after a form of compassion (emotional

0361-9230/$ see front matter 2010 Elsevier Inc. All rights reserved.

doi:10.1016/j.brainresbull.2010.03.001
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A. Manna et al. / Brain Research Bulletin 82 (2010) 4656 47

OM) meditation[10].These extreme increases in perceptual dom-

inance durations suggest that extensive training in FA meditation

mightimprovethe abilitiesto sustain attentionfocus on a particular

object andto control the flowof items being attended forconscious

access. A recent fMRI study investigated the neural correlates of

FA meditation in experts (following Tibetan Buddhist traditions)

and novices, with meditation focus on an external visual point

[4].FA meditation compared with a rest condition, was associated

with activation in multiple brain regions involved in monitoring,

such as dorsolateral prefrontal cortex (DLPFC), attentional orient-

ing (e.g., the superior frontal sulcus and intraparietal sulcus) and

engaging attention (visual cortex). The meditation-related activa-

tion patterns depended on the level of expertise of the meditation

practitioners.

OM meditation involves no explicit attentional focus, and there-

fore does notseemassociated tobrainareas implicated in sustained

or focused attention, but to brain regions involved in vigilance,

monitoring and disengagement of attention from sources of dis-

traction from the ongoing stream of experience[28].OM practices

are based on an attentive set that is characterized by an open

presence and a nonjudgemental awareness of sensory, cognitive

and affective fields of experience in the present moment, and

involves a higher-order awareness or observation of the ongoing

mental processes[7].The cultivation of this reflexive awarenessin OM meditation is associated to a more vivid conscious access

to the rich features of each experience and enhanced metacogni-

tive and self-regulation skills[28].Behavioral studies have shown

a more distributed attentional focus[39],enhanced conflict moni-

toring [37] and reduced attentional blink or more efficient resource

allocation to serially presented targets [34] in OM meditation prac-

titioners.

Despite the increasing number of studies on neuralcorrelates of

meditation states and traits, the differential brain activity patterns

in focused attention and open monitoring meditation forms have

not been contrasted yet in a neuroimaging experiment. Therefore,

in an fMRI experiment we studied the FA and OM meditation-

related brain activity patterns of Buddhist monks whoare expertin

Samatha (FA) and Vipassana (OM) meditation forms, and follow theoldest (Theravada) currently active Buddhist tradition. Vipassana

(insight) meditation is central in mindfulness-based clinical inter-

ventions and studies [8,38]. Although lay practitioners ofVipassana

have participated in recent research (e.g., [17,34]),to our knowl-

edge this is the first study in which Theravada Buddhist monks are

involved.

Our integrated FAOM experimental design allows testing of

whether FA and OM meditation styles enhance or, by contrast,

reduce brain activations in frontal and other executive areas, given

controversial evidence and theoretical stances. Indeed, it has been

recently argued that meditative states are associated to transient

hypofrontality or deactivation in executive networks[15,26]. In

contrast, other authors have emphasized the activation of exec-

utive areas in meditation [7,28]. We hypothesize that the brainregions associatedwith conflict monitoring, suchas the dorsal ante-

rior cingulate cortex (ACC) and DLPFC [9,40],selective attention,

such as the temporalparietal junction, ventrolateral prefrontal

cortex, intraparietal sulcus and frontal eye fields [12] and sus-

tained attention, such as right frontal and parietal areas, and the

thalamus[13,32],were more involved in inducing and maintain-

ing the state of FA meditation as compared to the conditions of

OM meditation and non-meditative rest[28].Given neuropsycho-

logical [22] and psychophysical [18] evidence of dominance of

the left cerebral hemisphere in conscious access, and theoretical

bases to hypothesize a leading role of this hemisphere in conscious

experiences [2,22,27], we predict a leftward bias of activation in

fronto-parietal areas in OM meditation as compared to the other

conditions.

2. Materials and methods

2.1. Participants

Participants included 8 Theravada Buddhist monks (males, meanage 37.9years,

range 2553 years, SD 9.4years),with 15,750h on averageof balancedSamatha (FA)

andVipassana(OM) meditation practice in Theravada monasteries (SD 9900 h). The

monks were from the Santacittarama monastery, in central Italy, following a Thai

Forest Tradition (the order was funded by Ajahn Chah, one of the most influential

Buddhist teachers in the 20th century). In this tradition, monks experience reg-

ular intensive meditation retreats, with a balanced practice of FA (Samatha) andOM (Vipassana) meditation forms, including an about 3-month long winter retreat.

Outside the retreat period, the monks typically practice SamathaVipassanamed-

itation, with a balance of FA and OM meditation, 2 h per day with the monastery

community. Individual meditation practice, with a balance of FA and OM medita-

tion forms is also emphasized. Thus, on average the expertise of the monks in the

studied group can be estimated in 15,750h of balanced FAOM meditation prac-

tice. Participants also included a group of 8 novice meditators (males, mean age

32 years, ages 2636 years, SD 3 years), recruited from the local community. All

novice subjects were interested in meditation but had no prior meditation experi-

ence. The novice participants were given oral and written instructions on how to

performSamathaand Vipassanameditation styles, and during the 10 days before

the fMRI scan session practiced each of the two meditation styles 30 min per day.

The meditation instructions were written by Ajahn Chandapalo, the abbot of the

Santacittarama monastery, expertSamathaVipassanameditation teacher. All par-

ticipantswere right-handed. Subjectsgave theirwritten informedconsent according

to the Declaration of Helsinki[41].

2.2. Task and protocol

The FAOM experimental paradigm consisted of 6min FA (Samatha) and 6min

OM (Vipassana) meditation blocks, each preceded and followed by a 3 min non-

meditative resting state block (Rest), for three times (seeFig. 1).The total duration

of the experiment was 57min. The condition switch was instructed by an auditory

word-signal during the experiment.

To perform FA meditation, participants were given the following instruction:

gently engage in sustaining the focus of your attention on breath sensations, such

as at the nostrils, noticing with acceptance and tolerance any arising distraction,

as toward stimuli or thoughts, and return gently to focus attention on the breath

sensations after having noticed the distraction source. In OM meditation, partici-

pants weregiventhe followinginstruction:observe andrecognize anyexperiential

or mental content as it arises from moment to moment, without restrictions and

judgement,including breath and body sensations,percepts of external stimuli, aris-

ing thoughts and feelings. The instruction for Rest was the following: rest in a

relaxed awakestate. In FA and OMmeditation aswell asin theResttaskcondition,

the subjects did not employ any discursive strategy, recitation, breath manipula-tion or visualization technique. During all the conditions, the participants kepteyes

closed. At the end of the experiment, all participants reported they could perform

the FA, OM and Rest task conditions according to the given instructions, with no

differences in the experienced difficulty to perform FA and OM meditation condi-

tions.

2.3. Functional MRI recording

Functional MRI scans were acquired on a Siemens Magnetom Vision scanner

at 1.5T, equipped with a standard receiver head coil. BOLD contrast functional

imaging was performed using a T2-weighted echo planar (EPI) free induction decay

(FID) sequence with: TR= 4 s, 28 slices, voxel size 4 mm4 mm4 mm, 860 func-

tional volumes for each run. A high-resolution T 1-weighted whole-brain image

was also acquired at the end of each session via a 3D-MPRAGE sequence (sagit-

Fig. 1. Sequence of the experimental conditions during the measurements.


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48 A. Manna et al. / Brain Research Bulletin 82 (2010) 4656

tal matrix= 256256, FOV = 256mm, slice thickness=1 mm, no gap, in-plane voxel

size=1mm1 mm, flip angle= 12, TR/TE = 9.7/4.0ms).

2.4. Physiological measures

Respiration rateand ECGwere recorded throughout eachscanning session in all

subjects. EEG was also recorded, with data to be analyzed for a subsequent report.

2.5. Data analysis

Rawdata wereanalyzed using Brain VoyagerQX 1.7software (Brain Innovation,TheNetherlands).Thefirstfive scansof each runwerediscardedto avoidthe T1sat-

uration effect. Preprocessing consisted in a 3D motion correction and in a temporal

filtering of voxel time series. The data set of one of the monks was discarded from

further analysis due to excessive motion. Preprocessed functional volumes were

co-registered with the corresponding structural data set. Co-registration transfor-

mation wasdetermined using theslice position parametersof thefunctional images

and the position parameters of the structural volume. Temporal filtering included

linear andnon-linear (high-pass filter of twocycles pertime course)trendsremoval.

Structural and functional volumes were than transformed into the Talairach space

[36]. No spatial or temporal smoothing was applied.

Statistical analysis was carried out for individual subjects and condition using

the General Linear Model [21]. To account for the hemodynamic delay, the box-

car waveform of each task condition was convolved with the Boynton empirically

founded hemodynamic response function[3]. In order to search for activated areas

common to the entire group of subjects, a voxel-wise random effect group analysis

was performed, distinguishing between monks and novice meditators (within-

group analysis). To this purpose, all the subjects time series were z-normalized

and individualbetascomputedby specifying subject-specific regressors in theGLM.

Moreover, to quantitatively evaluate differences between the brain activity pat-

terns of monks and novices, and to includegroupas a factor in our statistical model

of the fMRI data, between-group inferences were also computed (between-group

analysis).

Group statistical maps were thresholded at an overall significance level (the

probabilityof a false detectionfor theentirefunctional volume)ofp < 0.01,corrected

for multiple comparisons. The correction for multiple comparisons was performed

using a cluster-size thresholding algorithm[19]based on Monte Carlo simulations

and implemented in the BrainVoyager QX software. A threshold ofp < 0.01 at the

voxel level, a FWHM = 1 voxel as Gaussian kernel of the spatial correlation among

voxels and 5000 iterations were used as input in the simulations, yielding a mini-

mum cluster size of 8 voxels (< 0.01).

2.6. Activations

Clusters of activation were obtained from the group activation maps consider-

ing voxels showing a significant response (p < 0.01, corrected) to any experimentalcondition. The Talairach coordinates ofTable 1are referred to the most significant

voxelin eachactivated cluster.A correlation analysisbetween these activations was

performed. Specifically, the correlation between the time course of the mean BOLD

response (in a certain experimental condition) recorded from voxels belonging to

two given clusters was evaluated. In order to assess the significance level for the

r-Pearson coefficient, the Bonferroni correction for multiple comparisons among

clusters was applied to thep-threshold.

Moreover, an additional correlation betweenBOLD estimatedparameters(beta-

weightsresulting from both contrasts, FA > Rest and OM> Rest) and both expertise

levelandagewas evaluated, with reference to the ROIs emerging from the within-

group analysis for the monks.

2.7. Respiration rate correlation

Since all subjects underwent physiological monitoring during scanning, a

correlation analysis between the average respiration rates recorded in different

meditation/rest conditionswas performed; in addition, t-test across conditionswasevaluated for bothmonks and novices,to probe condition-related breathing behav-

ior differences between expert and novice meditators.

3. Results

3.1. Within-group analysis

In order to test the involvement of differential brain activations

in FA and OM meditation styles, with reference to Rest, the FA

meditation vs. Rest condition (FA > Rest) and OM meditation vs.

Rest condition(OM > Rest)contrastswere considered.Complemen-

tarily, we analyzed brain activations in the OM meditation vs. FA

meditation (OM > FA) contrast. The results revealed by these con-

trasts for monks and novices are summarized inTable 1.

3.1.1. Contrasts in the monk group

The contrast FA > Rest (Fig. 2)showed a wide pattern of deacti-

vations in the left hemisphere, comprising multiple clusters in the

middle frontal gyrus (MFG), dorsolateral prefrontal cortex (DLPFC)

(BAs9/46), lateral anterior prefrontal cortex (aPFC) (BA10), pre-

cuneus(BA7), transversetemporalgyrus (TTG)(BA41), anterior and

posterior insula (BA13). The deactivations of the inferior frontal

gyrus (IFG) (BA44 andBA46) andthe superior temporal gyrus (STG)

(BA22) were found in therighthemisphere. Moreover,threemedial

frontal areas exhibited an increased activity as compared to Rest,

located in the left and right dorsal anterior cingulate cortex (ACC)

(BA24), and in the right medial aPFC (BA10).

The contrast OM>Rest (Fig. 3) revealed three activations in

the left hemisphere: medial aPFC (BA10), superior temporal gyrus

(STG) (BA22) and superior parietal lobule (SPL)/precuneus (BA7;

the activation cluster was centered in the SPL but extended medi-

ally in the precuneus). The contrast OM> FA (Fig. 4) showed

a large pattern of activations in the left hemisphere, including

DLPFC (BAs9/46, superior frontal gyrusSFG and middle frontal

gyrusMFG), lateral aPFC (BA10, MFG), medial frontal gyrus

(MeFG) (BA9), precuneus (BA7), superior parietal lobule (SPL)

(BA7), and anterior insula (BA13). In the right hemisphere, the SFG

in lateral aPFC (BA10), the IFG (BA46) and the TTG (BA41) were

activated. It is due to make the reader notice that a large part of theactivations are actually due to the fact that those areas are deac-

tivated during FA, rather than activated during OM. A deactivation

of the dorsal ACC (BA24) and the medial aPFC (BA10) was found in

the right hemisphere.

3.1.2. Contrasts in the novice group

As regards the novices, the contrast FA > Rest (Fig. 5)showed a

single activation in the left posterior cingulate(BA31). The contrast

OM> Rest (Fig. 5)showed activations in the left dorsal ACC (BA32),

the right rostral ACC (BA32), the right lateral orbitofrontal cortex

(IFG, BA47) and the right medial aPFC (BA10). The contrast OM> FA

yielded no significant activation.

3.1.3. Cluster correlationsIn order to explore the differential state-dependent signal cor-

relations between areas activated in the FA > Rest and OM> Rest

contrasts, as well as between these areas and other hypothesis-

relevant regions, we conducted a correlation analysis with clusters

of activation derived from the contrasts, in the monks and con-

trol subject groups. We evaluated the correlation between time

courses of the mean BOLD response recorded from voxels belong-

ingto twogivenclusters, in FA,OM or Rest conditions. In themonks,

the correlations between clusters which were(positively) activated

in the FA > Rest contrast were considered, with the correlations

between such clusters and a subset of hypothesis-relevant clus-

ters deactivated in the same contrast, including left lateral DLPFC

and right IFG. In the same way, the correlations between the clus-

ters which were (positively) activated in the OM > Rest contrastwere considered, with thecorrelations between such clusters anda

subsetof hypothesis-relevant clusters activatedin theOM > FAcon-

trast, including anterior insula, lateral aPFC and SPL. Correlations

were also computed between clusters activatedin theFA > Rest and

OM > Rest contrasts in the novices.

In particular, we hypothesized positive correlations within the

set of the three clusters activated in FA > Rest, and within the set

of the three clusters activated in OM > Rest, to reflect two inter-

area brain circuitries for FA and OM meditation: a medial frontal

(prevalently right) circuitry for attentional focusing and monitor-

ing in FA meditation; a left fronto-parieto-temporal circuitry for

open awareness in OM meditation, We also hypothesized nega-

tive correlations between the three activated clusters and a set of

deactivated executive clusters in the FA> Rest contrast, including


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Table 1

Contrast results for monks and novices.

Group/contrast/area x y z k T p

Monks

FA meditation> Rest

Left SFG, BA10 10 66 19 81 5.579 ***

Left dorsal ACC, BA24 9 26 16 270 6.832 ***

Left MFG, BA46 48 39 13 618 5.706 ***

Left MFG, BA9 47 32 28 243 6.338 ***

Right MeFG, BA10 12 50 13 351 8.821 ****Right dorsal ACC, BA24 12 32 14 432 6.639 ***

Right IFG, BA44 54 17 13 135 5.174 **

Right IFG, BA46 48 41 14 270 8.225 ****

Left precuneus, BA7 0 70 49 270 3.806 *

Left TTG, BA41 41 25 10 314 8.552 ****

Right STG, BA22 57 51 13 54 6.439 ***

Left anterior insula, BA13 42 8 3 270 5.627 ***

Left anterior insula, BA13 42 19 1 162 3.581 *

Left posterior insula, BA13 41 10 7 1458 8.714 ****

OM meditation > FA meditation

Left MFG, BA46 41 44 25 108 7.319 ***

Left MeFG, BA9 3 38 29 162 8.993 ****

Left SFG, BA9 27 48 31 54 4.333 **

Left MFG, BA10 26 59 13 57 5.201 **

Left MFG, BA46 48 32 13 81 4.311 **

Right SFG, BA10 24 41 22 54 5.386 **

Right dorsal ACC, BA24 12 30 14 270 9.525 ****Right MeFG, BA10 15 48 10 351 4.726 **

Right IFG, BA46 51 29 14 108 4.683 **

Left STG, BA22 48 31 5 297 4.157 **

Left TTG, BA41 39 31 13 513 5.183 **

Right TTG, BA41 54 20 13 189 8.367 ****

Left precuneus, BA7 6 73 46 297 6.957 ***

Left SPL, BA7 30 55 61 108 3.69 *

Left anterior insula, BA13 32 23 5 513 7.76 ***

OM meditation> Rest

Left MeFG, BA10 3 53 10 216 7.867 ***

Left SPL/precuneus, BA7 18 64 43 108 4.503 **

Left STG, BA22 54 37 7 297 5.63 ***

Novices

FA meditation> Rest

Left posterior cingulate, BA31 23 25 37 216 8.889 ****

OM meditation> Rest

Left dorsal ACC, BA32 12 20 22 117 4.809 **

Right rostral ACC, BA32 12 39 4 378 7.892 ****

Right MeFG, BA10 15 56 14 243 6.812 ****

Right IFG, BA47 21 23 5 2125 8.035 ****

Contrast results for monks and novices. Single-voxel uncorrectedp-value are denoted by *(p < 0.01), **(p < 0.005), ***(p < 0.001), ****(p < 0.0001).

lateral frontal areas in theleft andrighthemispheres. Finally, in this

correlation analysis we considered activated clusters in the insula,

given the observed massive deactivation of it in the FA > Rest con-

dition, and its implication in meditation from previous studies (see

[7,28]).

Average positive and negative significant correlations in each

of the groups, were computed. We considered clusters as corre-

lated if the r-value was larger than 0.4 in at least four subjectsin the group, for positive correlations, and lower than -0.4 in at

least four subjects, for negative correlations. The positively or neg-

atively correlated clusters, according to such criteria, are shown in

Table 2.

3.1.4. Correlations in the monk group

As regards clusters resulting from FA> Rest contrast, we found a

highpositivecorrelation between theactivatedmedialfrontalareas

during FA,OM andRest conditions (with theleft dorsalACC andthe

right medialaPFC correlatingonly in theRest condition). A negative

correlation, during the Rest condition, was found between these

activated right and left dorsal ACC clusters, and a deactivated left

DLPFC cluster,as well asbetween the leftdorsalACC and a right IFG

activation in the same contrast. A negative correlation between the

(activated) right medial aPFC cluster and a (deactivate) left DLPFC

cluster, was also found in Rest.

With reference to clusters activated in the OM > Rest and

OM > FA contrasts, we found that left medial aPFC positively cor-

related with lateral aPFC, STG and anterior insula in the left

hemisphere. Theleft STGalso correlated with theleft superior pari-

etal lobule and the left anterior insula. These correlations were

foundin all experimental conditions. Finally, the left SPL/precuneuscorrelated with the left STG, in the Rest condition.

3.1.5. Correlation with expertise level

The probed correlation between beta-weights recorded in

both contrasts (FA> Rest and OM > Rest) and meditation expertise

revealed no significant outcomes for the OM condition, whereas

during FA meditation both deactivations of right IFG (BA46) and

of the posterior insula (BA13) positively correlate with meditation

expertise (Fig. 7). Finally, no significant correlation with age was

observed.

3.1.6. Correlations in the novice group

Correlations between the four activations in the FA > Rest

or OM> Rest contrasts, in the novices group, were computed.


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Fig. 2. Activations and deactivations revealed by the FA > Rest contrast, in the monks group. Note the deactivation of insula (BA13), MFG (BA46), TTG (BA41) and precuneus

(BA7) in the left hemisphere, and of IFG (BAs44/46) in the right hemisphere. Note also the activation of left/right dorsal ACC (BA24) and right medial aPFC (BA10). In this and

in all the figures the right hemisphere is on the left side (radiological convention).

Fig. 3. Activations revealed by the OM > Rest contrast, in the monks group, including medial aPFC (BA10), SPL/precuneus (BA7) and STG (BA22), in the left hemisphere.

Table 2

Correlationsbetweenactivationsresulting fromthe FA> Rest, OM> Restand OM> FA contrasts, for bothmonks and novices.The percentage of subjectsfor which significance

was displayed, is indicated.

Group Contrast Condition Areas Averager-v alue S ubje cts pe rcentage

Monks FA > Rest Rest Dorsal ACC, L-BA24/MeFG, R-BA10 0.46 88%

Monks FA > Rest All Dorsal ACC, L-BA24/Dorsal ACC, R-BA24 0.59 100%

Monks FA > Rest All MeFG, R-BA10/Dorsal ACC, R-BA24 0.58 100%

Monks FA >Rest Rest Dorsal ACC, L-BA24/MFG, L-BA9 0.44 62.5%

Monks FA >Rest Rest Dorsal ACC, L-BA24/IFG, R-BA44 0.44 62.5%

Monks FA > Rest Rest MeFG, R-BA10/MFG, L-BA9 0.43 62.5%

Monks FA >Rest Rest Dorsal ACC, R-BA24/MFG, L-BA9 0.44 88%

Monks OM > Rest All MeFG, L-BA10/MFG, L-BA10 0.47 62.5%

Monks OM > Rest All MeFG, L-BA10/STG, L-BA22 0.40 62.5%

Monks OM > Rest All MeFG, L-BA10/Anterior insula, L-BA13 0.43 62.5%

Monks OM > Rest Rest Precuneus, L-BA7/STG, L-BA22 0.44 62.5%

Monks OM > Rest All STG, L-BA22/SPL, L-BA7 0.43 62.5%

Monks OM > Rest All STG, L-BA22/Anterior insula, L-BA13 0.53 75%

Controls OM > Rest All Dorsal ACC, L-BA32/MeFG, R-BA10 0.41 63%

Controls OM > Rest All Rostral ACC, R-BA32/MFG, R-BA11 0.53 75%


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Fig.4. Activations anddeactivationsrevealed by theOM > FA contrast,in themonks group. Notethe activation of anteriorinsula(BA13),STG (BA22),TTG (BA41),MFG (BA46),

MeFG (BA9) and SPL (BA7) in the left hemisphere. Note the activation of IFG (BA46) in the right hemisphere as well. The deactivation of right dorsal ACC (BA24) and medial

aPFC (BA10), are also shown.

We found a positive correlation between left dorsal ACC andright medial aPFC, and between right rostral ACC and the right

orbitofrontal cluster, in all conditions.

3.2. Between-group analysis

Quantitative differences emerged from the between-group

analysis (seeFig. 6).In order to evaluate if these differences were

significant and determine their direction, t-tests (between the

BOLD of monks andcontrols) were computed on theresulting clus-

ters. This analysis confirms that the monks, as compared to the

novices, increased dorsal ACC (BA24) and right MeFG (BA6 and

BA10) activity bilaterally to focus their attention (FA meditation).

In OM meditation, the monks engaged more than novices the leftprecuneus/SPL (BA7), the right dorsal ACC (BA32) and the right

parahippocampal gyrus. By contrast, novice participants showed

a higher engagement of the right rostral ACC (BA32), bilateral IFG

(BA47), right orbitofrontal (BA11) and right medial aPFC in open

monitoring.

3.2.1. Respiration rate correlation

The resulting correlation matrix (Fig. 8)showed no significant

differences between OM, FA and Rest conditions for the monks,

i.e. individual differences in basal rates of respiration (e.g., during

rest) are preserved in the other conditions (FA, OM). In contrast,

the novices differentiatedtheir respiration rates, aboveall between

Fig. 5. Activations and deactivations revealedby theFA >Rest andOM >Rest contrasts, in thenovice group. Onthe left, thedeactivation of theleftposterior cingulate (BA31)

in FA > Rest is shown. The other sections show the activation of the orbitofrontal IFG (BA47), medial aPFC (BA10) and rostral ACC (BA32), in the right hemisphere, and dorsal

ACC (BA32) in the left hemisphere. The orientation of the sections follows the radiological convention.


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Fig. 6. Quantitative differences between monks and novices emerging from the between-group analysis during FA (left) and OM (right) meditations. The letterk indicates

the number of voxels, andpthe significance of the peak voxel.

OM and rest condition (Fig. 8(a) and (b),t-test across conditions).

This result attests a peculiar condition-related breathing behavior

of each group, and indicates that novice participants might reduce

their focus on respiration when they are asked to emphasize the

monitoring faculty.

4. Discussion

For the first time brain activity patterns in FA and OM med-

itation were contrasted in a neuroimaging (fMRI) experiment,

in expert (Buddhist monks) and lay novices, with an integrated

FAOM paradigm. Overall, we found striking differences between

the patterns of brain activity of monks and novices, in OM and

FA meditation styles. The brain activity patterns of the monksin OM meditation resembled their ordinary brain resting state,

whereas their brain activity in focused attention meditation

sharply contrasted with both these states. In the monks, the

larger differentiation between brain activity patterns in FA and

OM meditation conditions, as compared to the OM > Rest con-

trast, indeed suggests that open monitoring (mindfulness) is also

reflected and thus practiced in ordinary non-meditative condi-

tions.

It hasbeen recently arguedthat meditative states areassociated

to transient hypofrontality or deactivation in executive networks

[15,26]. In contrast, other authors have emphasized the activa-

tion of executive areas in meditation [7,28]. As expected, the

results with our experimental design resolve this controversy: we

conclude that FA meditation is associated to an enhanced (predom-

inantly right) medial frontal and a reduced (predominantly left)

lateral prefrontal activation, and OM meditation to an increased

(predominantly left) medial frontal activation, as compared to

rest. We also conclude that OM meditation, as compared with FA

meditation, is characterized by a lateral prefrontal activation in

both hemispheres, with a more subtle differentiation in medial

frontal brain activations associated to these fundamental medita-

tion styles.

Unlike brain activations, signal correlations between areas

activated in the contrasts were mostly not sensitive to the

meditation/rest conditions, against our expectations. The result-

ing correlation patterns suggest that networks or large-scale

multiregional assemblies of neurons, plausibly emerging by neu-

roplasticity, are recruited throughout different rest and meditationconditions. However, the activation level of their components

located in different brain areas would depend on the meditation or

rest conditions, as shown by our contrasts. As discussed below, the

resulting positive and negative correlation patterns contribute to

shed light on functional connections between subsets of activated

brainareas,and suggest thata functionalreorganizationof thebrain

resting state takes place in mental practice experts, with spatially

distributed neural activations modulated by different meditation

states.

We will first consider meditation state effects in the monks and

then in the novices, and subsequently discuss these two groups

comparatively. The implications of our findings for the cognitive

neuroscience of attention and awareness, will be thoroughly con-

sidered through the discussion.


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Fig. 7. Significant correlation results between clusters emerging from the within-

group analysis in the monk group. The correlation between beta-weights recorded

in each condition (FA and OM) and both meditation expertiseand age reveals that

during the FA meditation the right IFG (BA46) and the left posterior insula (BA13)

positively correlate with meditation expertise. No significant correlation with age

was observed.

4.1. Self-regulation of cognitive engagement in the monks

At a macroscopic level, a relative left-lateralization of brain

activity patterns resulted in our experiment. Most of the deactiva-

tions in FA> Rest and activations in OM> FA, and all the activations

in OM > Rest, were in the left hemisphere. These patterns include

a massive deactivation of left anterior and posterior insula in

FA> Rest, and a consistent activation of the left anterior insula

in OM > FA. We also found that the precuneus, which has been

associated to self-referential activations[11,26], was involved in

the left hemisphere in all contrasts. Specifically, it was deacti-

vated in FA>Rest, and activated in OM>Rest and OM>FA, as

hypothesized. The left precuneus was the only neural site to show

a similar pattern in our contrasts. This evidence suggests that

the left precuneus might plausibly act as a key brain region in

the self-induced transitions between brain resting states asso-

ciated to meditative and non-meditative attentional sets, in the

monks.The OM > Rest and OM > FA contrasts, with related correlation

analyses, also point out the relevance of the left SPL in BA7, which

might act in an inter-area circuitry with the left STG activated in

the OM > Rest contrast.In asymmetrywith the left hemisphere, in the right hemisphere

we did not find activation or deactivation of (medial and lateral)

BA9, insula and posterior parietal areas, in any of the contrasts.

This evidence could not be predicted in light of the findings of

a set of thicker cortical areas (including anterior insula) in the

right hemisphere of insight meditators[25].This set of right hemi-sphere areas found in previous MRI structural studies might be

involved in an ongoing phenomenal awareness of the fields of

experience,independent on meditation-relatedattention focusand

open monitoring. Indeed, during FA and OM meditations (as well

as in rest), Buddhist monks experience an ongoing phenomenal

awareness of sensory fields, even though items in these fields may

not be intentionally accessed and investigated [28]. Conscious

access to selected contents of experience might instead take place

in fronto-parietalareas of the left hemisphere, consistent with psy-

chophysical evidence about dominance of the left hemisphere in

perceptual awareness[18,29,31].

Finally, the activations found in the OM > Rest contrast in the

monks concern three main regions typically associated to self-

referential processing[32],with a peculiar left-lateralization. This

Fig. 8. Correlationsbetweenrespirationfrequencies recordedin differentmeditation/rest conditions: correlation matrix (left) andt-testevaluated for monks (a)and novices

(b). No significant differences emerged in monks, i.e. individual differences in basal rates of respiration (e.g., during rest) are preserved in the other conditions (FA, OM); in

contrast,novicesdifferentiatedtheir respirationrates,aboveall betweenOM andRest condition(a andb: t-test across conditions). Thisfurther result revealscondition-related

breathing behavior differences between expert and novice meditators.


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left-lateralized network of cortical midline and superior temporal

areas might reflect a neuroplasticity-based cognitive reorganiza-

tion of themonk brains, with neuronal populations in brain regions

ordinarily linked to self-referential processing reallocated to a

metacognitive observation of phenomenal experience and of the

experiencing subject [33,35]. This refers to a crucial aspect of

Buddhist practice and meditation, i.e. the cultivation of whole-

some mental states going beyond the cognition of a separated self

[1].

As we did not find activation (or deactivation) of the left IFG,

hypothesized to play an important role in self-awareness as an

inner speech-related region [30],it can be inferred that the left-

lateralized activity patterns we have observed are likely not to be

associated with a narrative self function theorized to account for

the dominance of the left hemisphere in conscious access [2,22].

Moreover, given that it has been recently shown that the left IFG

is characterized by a higher regional grey matter concentration in

Vipassanameditators[23], the activation of this area could have

been revealed in OM > Rest and OM > FA. Our negative evidence,

however, indicate thatthe monksdid notperforma language-based

access to present moment experiences.

Our evidence suggests that the monks might control cognitive

engagement and broadcasting in brain networks for conscious

access to sensory-related, thought and emotion contents, by mas-sive self-regulation of fronto-parietal and insular areas in the left

hemisphere, in a meditation state-dependent fashion. Specifically,

this self-regulation appears mostly controlled by alternated acti-

vations of (right) dorsal ACC and a set of neural sites in (left)

MFG(right) IFG, andreflected in massive changes in activity levels

of (left) insula and parietal posterior cortex, as well as in a shift of

medial aPFC activation.

4.2. Control of focused attention in the monks

The observed dorsal ACC (left and right BA24) activations

showed by the FA > Rest contrast are consistent with their pre-

dicted involvement in conflict monitoring during FA meditation.

The right medial aPFC (BA10) area activated in the same contrastis plausibly involved in focused awareness during FA medita-

tion. The observed high positive correlations between these three

frontal medial areas suggest that these midfrontal areas interact

in a unitary circuitry, with a higher activation during FA medi-

tation. The hypothesized activations in FA meditation associated

to selective attention (temporalparietal junction, ventrolateral

prefrontal cortex, intraparietal sulcus and frontal eye fields) and

sustaining attention (right frontal and parietal areas, andthe thala-

mus) were not observed. As an unpredicted result, in FA > Rest we

observed a remarkable deactivation of DLPFC, more pronounced in

the left hemisphere. The deactivation of the left DLPFC was even

more widespread in OM > FA, with the additional involvement of

the dorsolateral SFG. This evidence suggests that sustaining the

attentional focus in FA meditation implies a deactivation of DLPFCareas.

Interestingly, a negative correlation (in Rest) between both the

right and left dorsal ACC clusters activated in FA > Rest, and a left

DLPFC cluster deactivatedin FA> Rest,was found.Thisnegativecor-

relation suggests that, especially when distraction is more likely

(Rest), dorsal ACCand leftDLPFC playa contrasting rolein maintain-

ing cognitive focus and opening the field of cognitive monitoring.

We also found evidence about a role of the right IFG (BA44 and

BA46) and the left DLPFC, as shown in contrasts and correlations

(see Section3).

It can therefore be concluded that dorsal ACC and lateral (in

particular dorsolateral) prefrontal cortex play antagonist roles in

executive control of the attentionsetting,as observed in meditation

tasks without goal-related actions.

4.3. Meditation state effects in the novices and comparison with

the monks

As regards thenovices,we only found thedeactivation of theleft

posterior cingulate cortex in FA > Rest. Considering this result and

the evidence about the precuneus in the monks, consistent with

the recent proposal that the precuneus/posterior cingulate cortex

plays a pivotal role in the default mode network [20], it can be

hypothesized that the left precuneus/posterior cingulate region is

the component of the default mode network which can be more

sensitively affected by a goal-independent task, such as FA med-

itation. We also conclude that unlike FA meditation on a visual

point [4], breath-centered FA meditation may demand a longer

(more intensive) practice to observe more differentiated fMRI acti-

vations, at least with a paradigm characterized by short-duration

meditation blocks as in our experiment. It can also be concluded

that the monks performed a demanding FA meditation task in our

experiment.

Four activated clusters in the OM > Rest contrast were found in

the novice group. Overall, it seems that in novices open monitoring

mostly involved right prefrontal areas. The activation of the left

dorsal ACC might be explained by the executive demandto novices

in OM meditation performance. The positive correlation between

left dorsal ACC and right medial aPFC in the novice group, suggestthat these two areas co-operate in enabling cognitive focus.

The activations in novices of (right) rostral ACC and (right) lat-

eral orbitofrontal cortex (IFG), which were not found in the monk

group, suggest that in novices open monitoring may reflect an

evaluation-based stance. Indeed, there is evidence that rostral ACC

and lateral orbitofrontal cortex are involved in affective and cogni-

tive evaluation processes[6,16,24].These two areas were found to

be positively correlated in the novice group.

The key involvement of dorsal anterior cingulate cortex (BA24)

andright medialfrontalgyrus forfocusedattentionin monks,andof

the right rostral anterior cingulate cortex (BA32) and orbitofrontal

cortex/inferior frontal gyrus (BA11/BA47) for open monitoring in

novices, is confirmed by the between-group analysis.

4.4. Correlates of monk expertise

The probed correlation between beta-weights recorded in both

conditions and meditation expertise of the monks revealed that

during FA meditation both the deactivations of theright IFG(BA46)

and of the left (posterior) insula (BA13) positively correlate with

meditation expertise, i.e. larger deactivations are observed in more

expert practitioners. This evidence suggests that the expertise-

dependent sustained focused attention implies the deactivation

of such regions, likely to be involved in a more transient aware-

ness of experience contents [28]. The disengagement of these

areas might also be plausibly related to a more effortless main-

tenance of attentional (cognitive) focus in expert meditators[28],

in terms of a reduced background of neural activations which canpotentially reorient the allocation of limited attention-relatedbrain

resources.

4.5. Potential caveats and further investigations

It remains to be seen how the differential brain activity patterns

we have found correlate with hours of practice in a larger group

of FA/OM meditation practitioners. Although all the participants in

our study reported that they could perform FA and OM meditation

forms according to the given instructions and with no differences

in experienced difficulty, in a further study with a larger group

of participants, a quantitative measure of effort (e.g., self-ratings

on a Likert-scale), performed block by block, can provide a more

accurate information about effort for FA and OM meditation forms.


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Indeed, effort is an important aspect of meditation performance

[4,28]. Consideration of other aspects, such as balancing for subjec-

tive efficacy (how well FA andOM were performed), intensity (how

intense the experience was) and stability (for how long the med-

itative state persisted) within and between groups, also appears

important. As suggested by previous research[4],controlling for

subjective motivation while meditating and structural differences

in brain anatomy due to ethnicity, are further relevant aspects to

keep into account.

In further studies it may be insightful to compare brain activity

patterns in OM meditation conditions with differential awareness

of fields of experience, such as body sensory field, external sensory

fields andinternal thoughts andfeelings. There is indeedevidence

with a related theoretical account [5], to differentiate prefrontal

regions involved in stimulus-oriented and stimulus-independent

processing. Moreover, it appears useful to design an experiment

comparing brain activity patterns in FA meditation with focus on

breath-related sensations(as in our study) and on an external visual

point (as in[4]). FA meditation might involve a different level of

engagement with external world processing and modulation of

self-referential (default mode) brain networks, depending on the

focused object.

To conclude, the present study appears to shed light on fun-

damental aspects of meditation practice and the related set ofcognitive functions, beyond and complementarily to the findings

in previous studies, as related to the unique participants in it and

its design. The present findings might open the way to deeper

investigations of meditation-based awareness, with important

implications for the domain of neural correlates of consciousness

[33].

Conflict of interest

Theauthors declare that they have no competingfinancialinter-

ests.

Acknowledgements

First of all, we thank themonksof theSantacittaramamonastery

for their kind participation in the study, as well as for useful feed-

back at different stages of the work. We thank Antoine Lutz for

important suggestions to improve the design of the experiment.

We also thank Alessandro DAusilioand Valerio Santangelo foruse-

ful comments, and Luca Simione for kind assistance. Finally, we

have benefited from helpful and critical discussions about statisti-

cal data analysis from two of our close colleagues, Gianna Sepede

and NicolettaCera andwe wish to sincerely thank their continuous

support in this study. Finally, we would like to thank two anony-

mous reviewers for important remarks and comments which have

conducted to a significantly improved manuscript.

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