Concentrative (Sahaj Samadhi) meditation training and visual awareness: An fMRI study on color afterimages

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Concentrative (Sahaj Samadhi) meditation training and visual awareness: An fMRI study on color afterimages

8

Amrendra Singha, V.S. Chandrasekhar Pammia, Anupam Guleriab Narayanan Srinivasana,* a

Centre of Behavioural and Cognitive Sciences, University of Allahabad, Allahabad, India b Centre of Biomedical Research, Lucknow, India *Corresponding author: Tel.: +91-9935827117, e-mail address: [email protected]

Abstract All of us consciously experience the world around us through our sensory modalities. Empirical studies on the relationship between attention and awareness have shown that attention does influence perceptual experience or appearance in addition to better performance in perceptual tasks. The practice of meditation also changes perceptual experience in addition to better perceptual performance. For example, a study with Sahaj Samadhi meditators utilizing negative color afterimages had shown that concentrative meditation influences visual experience. However the brain regions that are modified by meditation practice leading to such changes in visual experience or awareness are still not known. Here using negative color afterimages in a functional MRI study, we investigated the brain mechanisms underlying the changes in visual awareness as a function of attentional enhancement achieved through long-term concentrative meditation practice. We found increased activity in right lateralized inferior occipital and inferior frontal cortex, which suggests the importance of attentional control in modulating visual awareness. The results of this study indicate that the link between attention and conscious experience is possibly changed by meditation practices.

Keywords Meditation, Visual awareness, Afterimages, Concentrative meditation, fMRI, Inferior frontal cortex, Inferior occipital cortex

Progress in Brain Research, Volume 244, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2018.10.026 © 2019 Elsevier B.V. All rights reserved.

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1 Introduction 1.1 Meditation and attention Meditation can be defined as a form of mental training, which improves our core cognitive processes like attention, emotion and self-regulation, which ultimately leads to psychological well-being, mental peace, joy, empathy and compassion. Meditation practices vary widely but many of them involve focus and concentration. Concentrative or focused attention meditation training involves sustained focused attention, on an object of focus, which could be a mantra or breath, and bringing attention to the object of focus whenever it wanders. Such focused attention training result in changes in multiple cognitive processes including visual perception (McLean et al., 2010), attention (Ainsworth et al., 2013; Badart et al., 2018; Chan et al., 2017; Colzato et al., 2016; Lippelt et al., 2014; Lutz et al., 2009; Mograbi, 2011; Mclean et al., 2010; Raffone and Srinivasan, 2009, 2010), emotion regulation (Menezes et al., 2013), and self-regulation (Menezes et al., 2013). Open monitoring meditation techniques that typically involve enhancing or training distributed attention have also been found to influence visual perception (Carter et al., 2005) and attention (Felver et al., 2017; Hodgins and Adair, 2010; Jha et al., 2007; Norris et al., 2018; Rooks et al., 2017; Tarrasch, 2017; Watier and Dubois, 2016). More specifically, meditation has been shown to improve different attentional processes, depending on the nature of the meditation type or practice (Chan and Woollacott, 2007; Colzato et al., 2015, 2016; Lippelt et al., 2014; Jha et al., 2007; Tang et al., 2007; Tsai and Chou, 2016; Valentine and Sweet, 1999). Such meditation related changes result in better perceptual performance in tasks that measure different attentional processes, e.g., Attentional Network Task (Ainsworth et al., 2013; Baijal et al., 2011; Jha et al., 2007; Tsai and Chou, 2016), Attentional Blink (Colzato et al., 2016; Slagter et al., 2007), and Stroop (Chan and Woollacott, 2007; Moore and Malinowski, 2009) tasks. Multiple studies have used the ANT task to measure alerting, orienting and executive control (Ainsworth et al., 2013; Baijal et al., 2011; Jha et al., 2007; Tsai and Chou, 2016). For example, Ainsworth et al. (2013) randomly assigned participants to three different groups, i.e., an open monitoring meditation group, focused attention meditation group and a control group. They found that both meditation practices improved executive control compared to the non-meditating control group. A crosssectional study with adolescents who practiced transcendental meditation showed that they had better alerting and executive control than the control group (Baijal et al., 2011). In a more recent study (Tsai and Chou, 2016) that compared open monitoring, focused attention meditation and a control group using the ANT task measures, they found that both open monitoring and focused attention meditation groups showed better executive control abilities compared to control group. In addition, the open monitoring group showed enhanced attentional orienting ability compared to FA and control groups. Meditators have shown benefits in identifying two target objects presented in a rapid visual stream (Colzato et al., 2016; Slagter et al., 2007). In a rapid serial visual presentation (RSVP), second target identification accuracy is poor when the second

1 Introduction

target appears around 100–300 ms after the first target; this phenomenon is called attentional blink. Slagter et al. (2007) recorded event related potentials in an RSVP task, before and after 3 month meditation training. They found that 3 months of meditation training led to reduced attentional blink (better second target performance) and reduction in resource allocation to first target, as shown by smaller P3b brain potential, which is a marker of resource allocation. They also found that those participants who showed the largest decrease in brain resource allocation to first target showed the greatest decrease in the size of the attentional blink. In a more recent study, differences in attentional processing over time between focused attention (FA) and open monitoring (OM) meditators were studied using the attentional blink task (Colzato et al., 2015). Participants in the study were given a brief session of focused attention meditation or open monitoring meditation training. After training, they found that the size of the attentional blink was considerably smaller after OM meditation compared to FA meditation. Based on these findings, Colzato et al. (2015) argued that different types of meditation have different effects on cognitive control, which possibly influences the allocation of attention over time. Sustaining attention over time has been found to be better with OM meditation compared to FA meditation indicating possible differences in attentional scope (Valentine and Sweet, 1999). Benefits in executive control due to meditation have also been studied using Stroop task (Chan and Woollacott, 2007). They used the standard color-word Stroop task as well as local-global Stroop task with meditators and controls. They found that meditation experience is negatively correlated with Stroop interference; less Stroop interference was found among those who meditated for longer periods every day. Also, they found that meditation experience (number of minutes per day) was associated with facilitation in local-global Stroop task performance. The studies discussed so far indicate changes in attentional processes due to meditation training, which in turn results in better perception. In the next section, we discuss the evidence for the role of attention in influencing perceptual experience.

1.2 Attention and perceptual experience Spatial attention, both exogenous and endogenous, has been shown to facilitate perceptual performance, with better accuracy or faster reaction time at the cued compared to the uncued location (Carrasco, 2014; Posner, 1980). While evidence for better performance in perceptual tasks due to spatial attention is unequivocal, whether attention influences the way stimuli appear to us or the way we consciously experience them has been hotly debated (Baijal and Srinivasan, 2009; Carrasco et al., 2004; Fuller and Carrasco, 2006; Gobell and Carrasco, 2005; Mishra and Srinivasan, 2017). Multiple studies have shown that changes in attention results in changes in visual awareness (Baijal and Srinivasan, 2009; Botta et al., 2014; Carrasco et al., 2004; Lou, 2001; Suzuki and Grabowecky, 2003; van Boxtel et al., 2010). For example, unattended color inducers produced stronger color afterimages (Lou, 2001; Suzuki and Grabowecky, 2003). Other studies have shown that not just attention but changes in scope of attention (focused or distributed) also produce changes in properties of

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color afterimages (Baijal and Srinivasan, 2010). Scope of attention was manipulated by varying the size (small or large) or the level (local or global) of target stimuli and measuring the duration of afterimage induced by a peripheral color inducer. Afterimage durations were found to be longer when spatial attention was more focused with small stimuli compared to large stimuli in the central task. Recent studies have shown that attention also influences the appearance of higher-level or complex visual aspects like attractiveness (Nakamura and Kawabata, 2013; St€ ormer and Alvarez, 2016) and emotional intensity (Mishra and Srinivasan, 2017). St€ ormer and Alvarez (2016) used an exogenous cuing paradigm in which an exogenous cue preceded two faces presented on either side of fixation. Participants were asked to report the upward or downward shift of the more attractive face of the two. They found that the face at the cued location was perceived to be more attractive compared to the one at uncued location and concluded that attention influences the perceived attractiveness of faces. Using a similar exogenous paradigm, Mishra and Srinivasan (2017) showed that the cued face was perceived as more happier or more sadder than the uncued happy or sad face, respectively. These studies indicate that attention influences perceptual experience and any training method that modifies attentional processes would also modify perceptual experience.

1.3 Meditation and perceptual experience Given that meditation influences attention and attention alters perceptual experience, some studies on meditation have also investigated the effect of meditation practice or yoga training on perceptual experience (Carter et al., 2005; Srinivasan and Singh, 2017; Vani et al., 1997). Binocular rivalry in which two different stimuli are presented to left and right eyes with participants reporting alternation in seeing between them has been used to study conscious perception among Buddhist meditators (Carter et al., 2005). In their study, meditators were presented with vertical and horizontal green stationary gratings using head mounted display goggles to the right and the left eye, respectively. Meditators after practice of one-point meditation showed larger perceptual dominance durations, that is longer periods with the same percept without switching. However, there was no difference in before and after practice when they practiced compassion meditation. In addition, a motion induced blindness task was also given to these expert Buddhist meditators and their experience was compared with non-meditators to study changes in perceptual appearance. When a global moving pattern is presented superimposed on a high contrast stationary or slowly moving stimuli, the stationary or slowly moving stimuli is experienced to disappear and reappear alternately for periods of several seconds and this is termed motion induced blindness. Motion induced blindness has been used to study the mechanisms of consciousness and attention (Booneh et al., 2001). Meditators sustained motion blindness for much longer durations with one expert meditator sustaining it for as long as 723 s (Carter et al., 2005). Afterimages can be used as a tool to study the neural mechanisms underlying visual awareness (Kirschfeld, 1999). Unlike tasks that involve measuring objective performance, which could reflect conscious or unconscious processes, afterimages

2 Neuroimaging study with color afterimages

are reported based on the perceptual experience of observers. Hence, this provides us an interesting method to study visual awareness without considering dependent measures like accuracy or reaction time. While initially afterimages were thought of as primarily a retinal phenomenon, recent studies have shown that afterimages are influenced by attention (Baijal and Srinivasan, 2009; Lou, 2001; Suzuki and Grabowecky, 2003). Attention to adapting inducer weakens color afterimages and attention to afterimages themselves makes them disappear soon (Lou, 2001; Suzuki and Grabowecky, 2003). In addition, changes in scope of attention during color afterimage formation influence the duration of afterimage formation (Baijal and Srinivasan, 2009). Color afterimages have also been used to study changes in visual awareness as a function of meditation training with focused attention (Sahaj Samadhi: SS) meditators (Srinivasan and Singh, 2017). In this study, participants performed a primary counting task on different stimuli that were presented at the center one after another. While the stimuli were being presented in succession, there was a constant blue inducer frame surrounding these stimuli. These letter or digit stimuli that appeared at the center differed in terms of size (large or small) and hierarchy (global or local). All the stimuli in a trial were either single letters/digits of the same size (small or large) or a big letter/digit made up of small 8s or (global) a big 8 made up of small letters/ digits (local). Participants were asked to report the duration as well as phenomenal characteristics like clarity and color of the afterimage. The findings from the study showed that concentrative meditation training influences duration and clarity of color afterimages. However, there was no effect on the saturation of the color afterimage. Afterimage durations were larger when participants performed small or local letter tasks compared to global or large letter tasks. This suggested that scope of attention influences formation and perception of color afterimages, which is consistent with results from a previous study on scope of attention and color afterimages (Baijal and Srinivasan, 2009). In terms of clarity also, Srinivasan and Singh (2017) showed that meditators perceive the afterimages to be sharper compared to nonmeditators. They concluded that the enhanced ability to focus due to concentrative meditation possibly leads to higher perceived contrast (Carrasco et al., 2004) making the afterimages sharper. While studies with typical adult population as well as with meditators have shown that attention and meditation training influence visual awareness as measured by color afterimages (Baijal and Srinivasan, 2009; Srinivasan and Singh, 2017), the neural mechanisms underlying the attentional effects on color afterimages have not been studied so far. Hence, we performed a neuroimaging study to investigate the brain areas underlying color afterimage differences between SS-meditators and non-meditators.

2 Neuroimaging study with color afterimages Multiple studies have shown structural and functional changes in the brain as a consequence of meditation practice especially in frontal areas (for review, see Boccia et al., 2015; Marchand, 2014; Tang et al., 2015). Effect of concentrative meditation

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on attention has been linked to increased theta band frontal activations (Baijal and Srinivasan, 2010) and changes in dorsolateral prefrontal cortex (Hasenkamp and Barsalou, 2012; Lazar et al., 2000). Studies have reported enhanced activation in ACC (Holzel et al., 2007) in experienced concentrative meditation practitioners as compared to controls. There is also evidence suggesting that the activation in ACC might decrease with higher level of meditation expertise (Brefczynski-Lewis et al., 2007). In terms of visual awareness, studies have implicated the role of early visual cortex (Hurme et al., 2017; Lamme and Supe, 2000) as well as extra-striate cortex in visual awareness (Tong et al., 1998). The role of specific visual areas can be differentiated in terms of the Hierarchical and Interactive models of visual awareness (Tong, 2003). The hierarchical models suggest that only extrastriate regions (V4, V5) are directly involved in visual awareness and the role of V1 is to only facilitate the flow of information to higher visual areas (Crick and Koch, 1995; Rees et al., 2002). However, the interactive models propose that V1 is directly involved in visual awareness by forming dynamic recurrent circuits with extra-striate areas (Lamme and Roelfsema, 2000; Pollen, 1999). Here, we investigated the neural areas involved in differences in appearance of color afterimages as a function of concentrative meditation training among SS-meditators. To our knowledge, so far, no study has investigated the neural basis for formation of color afterimages using fMRI methodology. Since this study involved color afterimages, it was expected that visual color areas like V4 would show larger activation when attention is more focused on the central task and less focused attention on the inducer, in general. In addition, the same areas were expected to show larger activation among meditators given the findings of larger afterimage durations with meditators (Srinivasan and Singh, 2017). The results of this study were expected to indicate the involvement of early areas of V1 if any, in the context of awareness of color afterimages. In addition, it was expected that activity in attentional areas in the frontal cortex, more specifically attentional control (Aron et al., 2004; Cai et al., 2014; Chikazoe et al., 2008; Hampshire et al., 2010; Sebastian et al., 2016, 2017; Zhang et al., 2017) will show differences as a function of meditation training.

2.1 Method 2.1.1 Participants Thirty-six volunteers with normal or corrected-to-normal visual acuity and normal color vision (assessed through Ishihara Color Test) provided informed consent and participated in the experiment. Participants consisted of two groups: a group of concentrative meditators (N ¼ 14) and a control group of non-meditators (N ¼ 18). The two groups did not differ in age or education. The difference between the age of meditators (mean ¼ 35.27 years, SD ¼ 10.98 years) and non-meditators (mean ¼ 38.07 years, SD ¼ 10.96 years) was not significant, t(30) ¼ 0.714, P ¼ 0.481. The participants in the meditation group were practitioners of Sahaj Samadhi (SS) meditation, which is associated with Sudarshan Kriya yoga. They were mostly teachers of Sudharshan Kriya yoga and associated with Art of Living foundation,

2 Neuroimaging study with color afterimages

who had been practicing SS meditation for more than 3 years. SS meditation practice is typically preceded by a 20-min session of Pranayama and Sudarshan Kriya yoga, which is a rhythmic breathing exercise. In SS meditation, the practitioner silently repeats a mantra (typically a specific sequence of words with religious significance), and whenever the mind wanders from this mantra, the practitioner has to bring it back to the mantra. Hence, this is usually classified as a type of concentrative meditation. The meditators have been practicing SS meditation for at least 20 min every day. The study was approved by the Institutional Ethics Committees of University of Allahabad and the Centre for Biomedical Research, Lucknow.

2.1.2 Stimuli and apparatus The stimuli used for the attentional task were hierarchical letters containing S, H and numbers 6, 9 (see Fig. 1). The local level consisted of many small letters/numbers arranged to form a global 8. The stimuli at the global level consisted letters/numbers of many local 8s. The letter stimuli were presented in the center of a blue square frame inducer (14.4 cd/m2) whose inner boundary subtended 7.19°  7.19° with thickness 0.8°. The background color was gray (58 cd/m2). Stimuli were presented and behavioral response was recorded (E-Prime software) using a PC computer in the MRI control room. The stimuli were viewed through an MR-compatible projector system. Responses were recorded with MR-compatible response box in both hands. The timing of the stimuli and the recording of the responses were controlled by E-Prime Professional 2.0 (Empirisoft Corp, USA).

FIG. 1 Example stimuli containing (A) small letter S, (B) large letter S, (C) large 8 made up of small (local) Ss and (D) global S made up of small letter 8s.

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2.1.3 Procedure The basic structure of a trial is shown in Fig. 2. The basic procedure was similar to that used in Srinivasan and Singh (2017). In each trial, a stream of 27 letter stimuli was presented for a total duration of 20 s. Each letter stimulus was presented for 500 ms followed by a blank screen for 250 ms. The inducer (blue square) remained unchanged and was present for the whole duration of 20 s. The same blue inducer was used in all the trials. The scope of attention was manipulated by changing the nature of the target stimulus in terms of size (small or large) or the level (global or local) of the hierarchical stimuli (Fig. 1). The participant’s task was to count the number of times the letter “S” appeared in each trial. Participants were instructed about the task and they performed a practice session before the commencement of fMRI recording. The participants were informed before the beginning of each block whether they had to do a global, local, large (single large), or small (single small) letter stimuli task. In the global task block, participants viewed hierarchical stimuli, that is small 8’s arranged to form a large S, H, 6, and 9 that appeared one after another. In the local block, the participants viewed stimuli composed of small characters S, H, 6, and 9 forming a large 8. In the small and the large blocks, only a single small or large letter appeared, respectively, one after another. After the disappearance of the blue square and letter stimuli, a blank gray

FIG. 2 Structure of a trial in the fMRI study.

2 Neuroimaging study with color afterimages

screen was presented on which the participants perceived a yellow color afterimage. To report the onset and offset of the yellow afterimage, participants pressed the left hand thumb button and right hand thumb button, respectively. The gray blank screen was presented for a fixed duration of 15 s irrespective of participant’s response. Each experimental block consisted of 10 trials. There were 4 blocks resulting in a total of 40 trials for the experiment.

2.1.4 MRI data acquisition BOLD imaging was performed on a 3T Siemens Magnetom Skyra scanner at the Centre of Biomedical Research, Lucknow. Each scanning session consisted of acquisition of a three-dimensional T1-weighted image using the magnetization-prepared rapid gradient-echo (MPRAGE) sequence with parameters TR (image repetition rate) ¼ 1900ms, TE (effective echo time) ¼ 2.44 ms, flip angle ¼ 9, matrix ¼ 256  256, 1 mm isotropic voxels, sagittal partitions. T2-weighted functional images were acquired using a gradient-echo echo planar imaging (EPI) sequence. The fMRI acquisition parameters were as follows: TR ¼ 3000 ms, TE ¼ 30ms, flip angle ¼ 90°, FOV ¼ 204.8 mm, matrix ¼ 64 64, 36 slices, slice thickness ¼ 4.2 mm without gap, interleaved scanning, transverse slice, with a voxel size of 3.2 mm  3.2 mm  4.2 mm.

2.2 Results 2.2.1 Behavioral results Mean afterimage duration as well as the mean ratings for color and clarity for the two groups (i.e., non-meditators and the Sahaj Samadhi meditators) was measured as a function of scope of attention (local, global, small, and large) in the central task that the participants performed inside the scanner. Data from one non-meditator and three SS-meditators were excluded from the behavioral analysis due to lack of recorded response in multiple trials. A two-way mixed ANOVA with groups (non-meditators and SS-meditators) as a between subjects variable and scope of attention (global, large, local, and small) as within subjects variables was performed on accuracy, afterimage duration, afterimage clarity, and afterimage color. The results showed no difference in accuracy for the two groups, F(1, 30) ¼ 0.749, P ¼ 0.394, η2p ¼ 0.024 (see Table 1 and Fig. 3). The accuracy scores for SS-meditators and non-meditators were 94.8% and 96.2%, respectively. The effect of scope on accuracy was not significant, F(3, 90) ¼ 2.502, P ¼ 0.064, η2p ¼ 0.077. The interaction between scope and group was not significant, F(3, 90) ¼ 1.839, P ¼ 0.146, η2p ¼ 0.058. As expected, the mean afterimage duration for SS-meditators was significantly longer than that of non-meditators F(1, 30) ¼ 5.296, P ¼ 0.029, η2p ¼ 0.150 (Fig. 3). However scope did not have an effect on duration of afterimage F(3, 90)¼ 0.745, P ¼ 0.528, η2p ¼ 0.024. The interaction between scope and group was not significant, F(3, 90) ¼ 1.123, P ¼ 0.344, η2p ¼ 0.058.

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Table 1 Accuracy of primary letter counting task for SS-meditators and non-meditators Accuracy

Global Large Local Small

SS-meditators

Non-meditators

96.29% 95.89% 91.81% 95.57%

96.32% 96.75% 96.05% 95.85%

(4.01) (6.63) (9.58) (4.62)

(5.51) (4.26) (4.98) (5.22)

FIG. 3 Mean afterimage duration for SS-meditators and non-meditators.

The main effect of group on clarity of afterimages was not significant F(1, 30) ¼ 2.033, P ¼ 0.164, η2p ¼ 0.063 (see Table 2). However, the effect of scope on afterimages clarity was significant, F(3, 90) ¼ 4.655, P ¼ 0.005, η2p ¼ 0.134. The clarity was higher for small and local task conditions compared to the global and large conditions (P < 0.05). The results indicate that clarity is higher when attention is more focused for both SS-meditators and non-meditators. The interaction between scope and group was not significant, F(3, 90) ¼ 1.330, P ¼ 0.270, η2p ¼ 0.042. There was no significant difference between the two groups in the perceived color of the afterimage, F(1, 30) ¼ 0.077, P ¼ 0.783, η2p ¼ 0.003 (see Table 2). The effect of scope on color of afterimages was not significant, F(3, 90) ¼ 0.809, P ¼ 0.492, η2p ¼ 0.026.

2 Neuroimaging study with color afterimages

Table 2 Clarity and color rating for SS-meditators and non-meditators Clarity

Global Large Local Small

Color

Meditators

Non-meditators

Meditators

Non-meditators

6.38 (1.06) 6.36 (1.33) 6.66 (1.24) 7.14 (1.18)

5.77 (1.66) 5.75 (1.47) 6.52 (1.21) 6.18 (1.54)

5.32 (1.81) 5.09 (1.45) 5.24 (1.98) 5.04 (1.88)

4.91 5.11 5.13 4.72

(1.59) (1.46) (1.77) (1.78)

2.2.2 fMRI data processing and statistical analysis Data analysis were performed using statistical parametric mapping (SPM)—8 software (Wellcome Department of Cognitive Neurology, London, UK; see http://www.fil.ion. ucl.ac.uk/spm). For each subject in each group, functional data were first corrected for motion artifact for each of the four different blocks. This was achieved by using a least square approach and a six parameter (rigid body) spatial transformation. The first image of each block/session was taken as reference image and the subsequent images were aligned to that reference image. Data from participants with estimated motion parameters >0.5 mm were not included in the functional analysis. Following this, the high resolution anatomical (structural) images were coregistered with functional images. After this, using a representative brain from MNI series (Montreal Neurological Institute, Quebec, Canada; Evans et al., 1993) as template, the first structural volume and subsequent functional volume was normalized. Finally, the functional images were spatially smoothed with an isotropic Gaussian kernel of 6 mm width. Using a fixed effect General Linear Model, condition specific (local, global, small, and large) effects were estimated for each subject. Parameters estimated from the linear model were used to specify areas of significant cortical activity. Following single subject analysis (first level), group analysis (second level) was carried out. The design was an event-related design with the analysis focusing on the attention phase (first 20 s when the participants performed the primary task) and afterimage phase (a 15 s window where the participants reported the afterimage) in the second level analysis. A 2  4 model was constructed and we tested two different contrasts for both attention and afterimage phase, i.e., SS-meditators > non-meditators and nonmeditators > SS-meditators. The imaging analysis revealed the brain activations during afterimage (AFT) formation in SS meditation compared to non-meditators (SS-meditators > nonmeditators, FWE corrected P < 0.05, k > 20 voxels) (Fig. 4). Right hemispheric activations were found in Inferior Occipital Cortex, Inferior Frontal Cortex and Inferior Frontal Cortex/Lateral Orbitofrontal Cortex (see Fig. 4 and Table 3) for SS-meditators > non-meditators. However, no significant brain activations was found for the contrast non-meditators > SS-meditators and the scope of attention effect (across four attentional conditions) including pair-wise comparisons of attention conditions (Global, Large, Local, and Small).

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FIG. 4 Brain activity for SS-meditators compared to non-meditators during afterimage formation.

Table 3 Brain activations during afterimage (AFT) formation in Sahaj Samadhi meditation (SS) compared to non-mediators Brain area SS > non-meditators Inferior Occipital Cortex Inferior Frontal Cortex Inferior Frontal/Lateral Orbitofrontal Cortex

R R R

BA

Coordinates (mm)

T score (number of voxels in the cluster)

19 6/44 45/47

37 37 44

6.02 (27) 5.21 (20) 5.18 (24)

86 3 26

0 30 5

Stereotaxic MNI coordinates of significant BOLD signals with cluster level FWE corrected P < 0.05, k > 20 voxels.

2.3 Discussion The results show changes in right occipital cortex (V4) and right inferior frontal cortex activations, which potentially underlie changes in visual awareness, as a function of long-term yogic practice that included concentrative meditation. Here, we used an fMRI adapted version of a task involving negative color afterimages (Srinivasan and Singh, 2017) to investigate the neural correlates underlying formation of color afterimages as a function of long term concentrative meditation practice. To our knowledge, this is the first study to investigate the neural basis of formation of color afterimages.

2 Neuroimaging study with color afterimages

The finding that afterimage durations are significantly longer for SS-meditators is consistent with the finding of Srinivasan and Singh (2017). Although we did not find a significant effect for clarity of afterimages, which was shown by Srinivasan and Singh (2017), the trend in our study was similar. In the present study as well, SS-meditators reported the afterimages to be more clear (sharper) compared to non-meditators. One difference in the present study compared to the study by Srinivasan and Singh (2017) is that some of the experimental parameters associated with stimulus presentation like visual angle and afterimage inducer (blue square) display duration were slightly different. This could have possibly led to a weaker trend for clarity as well as relatively shorter duration afterimages for both SS-meditators and non-meditators in the present study. The functional data showed increased BOLD activity in the right inferior occipital cortex (V4) and right inferior frontal cortex for SS-meditators during afterimage formation. Previous studies have linked spatial attention to brain activity in frontal regions (Coull and Nobre, 1998; Park et al., 2016; Szczepanski et al., 2010). For example, Coull and Nobre (1998) conducted a positron emission tomography and fMRI study to identify the brain correlates of spatial and temporal attention. In their study, they manipulated the expectations of the participants about where and when target would appear by using different cues for cueing spatial attention (target on left or right) and temporal attention (target after 300 or 1500 ms). They found a bilateral frontal activity for spatial orienting of attention. These frontal regions included lateral premotor (BA 6), lateral medial (BA 6) and ventrolateral prefrontal cortex (BA 11). These studies linked spatial attention to activity in frontal and parietal cortex and have shown dominance of right hemisphere in modulating spatial attention (Coull and Nobre, 1998; Park et al., 2016; Szczepanski et al., 2010). The finding of the present study shows an increased activity in right inferior frontal region for meditators compared to non-meditators for afterimage formation. Previous studies with typical adult population have linked the activity in inferior frontal cortex to response inhibition, which is a measure of attentional control (Aron et al., 2004; Chikazoe et al., 2008; Floden et al., 2010; Hampshire et al., 2010; Hughes et al., 2013; Kemmotsu et al., 2005). Many studies on attentional control have specifically shown, right inferior frontal activity (Aron et al., 2004; Cai et al., 2014; Chikazoe et al., 2008; Hampshire et al., 2010; Sebastian et al., 2016, 2017; Zhang et al., 2017). For example, Hampshire et al. (2010) used a Stroop task in an fMRI study and found strong evidence for the role of Inferior frontal gyrus in attentional switching, a process through which focus of attention is moved from one locus to another. Similarly, Chikazoe et al. (2008) conducted an fMRI study to understand the role of inferior frontal region in response inhibition and processing of infrequent stimuli. To investigate whether the frontal activation associated with go/no-go trial is due to response inhibition or processing of infrequent stimuli, they incorporated infrequent go trials and no-go trials apart from frequent go trials in their study. They found increased inferior frontal activity for response inhibition as suggested by infrequent no-go vs infrequent go trials.

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Previous studies on meditation and executive control have used Stroop interference task and have shown that mindfulness meditators have better attentional control and cognitive flexibility compared to non-meditators (Moore and Malinowski, 2009). The findings of the present study, that is, increased right inferior frontal activation for SS-meditators compared to non-meditators, could be due to enhanced attentional control. This is in line with previous studies (Aron et al., 2004; Chikazoe et al., 2008; Floden et al., 2010; Hampshire et al., 2010; Hughes et al., 2013; Kemmotsu et al., 2005) suggesting the role of right inferior frontal cortex in attentional control and cognitive flexibility. Sahaj Samadhi meditation is a focused attention meditation and it involves participants to focus attention on an object or mantra, and bring back attention to the object of focus whenever it wanders from it. SS meditation involves voluntary control of attention. In light of above discussed studies (Aron et al., 2004; Chikazoe et al., 2008; Floden et al., 2010; Hampshire et al., 2010; Hughes et al., 2013; Kemmotsu et al., 2005), the activity in right inferior frontal activation in our study could be possibly linked to attentional control. Consistent with this, a study on long term practice of Sahaj yoga meditation has shown enlargement of several right hemispheric brain regions that are associated with sustained attention as well as brain regions that are involved in top down control or processing of attention (Herna´ndez et al., 2016). The improvement in attentional control due to concentrative meditation indexed by increased right inferior frontal activity is possibly modulating the attentional effects on color afterimages (Baijal and Srinivasan, 2009; Srinivasan and Singh, 2017; Suzuki and Grabowecky, 2003). Along with right inferior frontal activation, the activation in right inferior occipital (V4) activity was greater for meditators. Activity in the inferior occipital cortex areas has previously been linked to conscious visual awareness (Carmel et al., 2006; Lumer et al., 1998; Lumer and Rees, 1999; Tong et al., 1998). Further, previous studies have implicated both frontal and occipital cortex in visual awareness (Lumer et al., 1998; Lumer and Rees, 1999). For example, Lumer and Rees (1999), using bistable viewing condition in an fMRI study, showed that functional interaction between extrastriate occipital and prefrontal cortex may contribute to visual perception. Other neuroimaging studies have suggested that spatial attention influences perception through the interaction between control regions in frontoparietal cortex which is involved in generating and maintaining expectation and occipital cortex which is involved in sensory processing of visual stimulus (Corbetta and Shulman, 2002; Kastner and Ungerleoder, 2000; Serences and Yantis, 2006). Attentional effects on color afterimages have been explained using a two-system model, which postulates interactions between a Boundary Contour System (BCS) and a Feature Contour System (FCS) (Wede and Francis, 2007). According to the model, the FCS processes information about color and other features between the boundaries specified by the BCS. They argued that paying attention to the adapting inducer results in stronger after effects in the polarity independent BCS that leads to weaker afterimages produced in the polarity dependent FCS. Conversely lesser attention to the adapting inducer results in stronger afterimages in the FCS. The results

2 Neuroimaging study with color afterimages

on color afterimages with meditators indicate that better focusing of attention of meditators to the primary task may result in changes in the BCS system leading to stronger afterimages in the FCS (Srinivasan and Singh, 2017). The additional results from our fMRI study suggest that this model possibly needs to postulate differences in the two hemispheres given the significantly larger activation found with meditators in the right occipital cortical areas. The present study is possibly the first study to identify right lateralized activity in meditators for the formation of color afterimages. The activity in right inferior occipital cortex (V4) could be due to sensory processing of different properties of color afterimages (e.g., color), which is modulated by the right inferior frontal cortex. The increased activation in right inferior occipital activity (V4) is not accompanied by increases or changes in other early visual areas like V1, supporting theories that argue for a larger or exclusive role for extrastriate visual areas in visual awareness (Tong et al., 1998). Finally the findings from the present study show that yogic practice involving concentrative meditation influences visual awareness. The study indicates two right lateralized brain regions, i.e., right inferior frontal and right inferior occipital as important for differences in visual awareness in Sahaj Samadhi meditators and non-meditators. There are a definite lack of studies, which have measured different attentional processes with SS-meditators using tasks that have been used with other types of meditators. Unpublished data with SS-meditators in our lab that compared SS-meditators with non-meditators, using ANT task indicates differences in attentional processes due to SS meditation practice (Kumar, 2014). In addition, since SS meditation is a concentrative meditation, other concentrative meditation studies showing improvement in attentional processes can be used as an indicator that similar benefits would also be present with SS meditation (Badart et al., 2018; Chan et al., 2017; Colzato et al., 2016; Lippelt et al., 2014). Another indication for betterattentional processing among SS-meditators comes from EEG obtained during the practice of SS meditation in the lab (Baijal and Srinivasan, 2010). The SS-meditators showed enhanced theta oscillations especially in the frontal cortical areas during meditation practice indicating the involvement of attentional areas during SS meditation. In addition, the inferior frontal area that showed more activation among SS-meditators in the current study has been shown to be involved in attentional control. Overall the findings from this study suggest that the enhanced focus and control of attention achieved through long term practice of concentrative meditation may not only influence behavioral performance in a perceptual task but also influence the phenomenal aspects of perception or perceptual experience in general. These meditation induced changes in visual awareness are regulated by the interaction between the frontal and occipital regions of the brain. Theoretical frameworks based on adaptive workspace (Raffone and Srinivasan, 2009, 2017) have argued that the adaptive processes linked to global workspace (Baars, 1998) provide the neuroflexibility that underlie the changes in appearance or conscious experience as a function of meditative practice. The enhanced attentional control in concentrative meditators as

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reflected by increased activity in inferior frontal cortex could be possibly linked to executive control exercised for controlling information in global workspace, which is reflected in terms of changes in visual awareness. The findings of the present study fit with theories based on the phenomenological account of meditation practices (Lutz et al., 2015). The phenomenological matrix has been hypothesized to be different for different mindfulness practices. The model consists of three primary dimensions: object orientation, dereification and metaawareness as well as four secondary dimensions: aperture, clarity, stability and effort. In the model, aperture refers to the broadness of scope of attention while clarity refers to degree of vividness of an experience. Effort dimension is linked to phenomenal impression of how easy or difficult it is to maintain one’s current mental state. Stability is linked to the length of persistence of experience. The findings of the studies with color afterimages address two secondary dimensions of the model, i.e., stability and clarity. According to the model (Lutz et al., 2015), expert focused attention meditators are characterized by low aperture, high stability, low effort, and high clarity. The current study was performed with SS-meditators, who according to the model would be expected to show similar attributes. In the context of the current study, stability would be linked to afterimage durations and clarity would be linked to the sharpness of the afterimage. The results from the studies on color afterimages support the high stability (longer afterimage durations) and high clarity (sharper afterimages) characterization of focused attention meditation of the phenomenological model (Lutz et al., 2015). The current study also indicates how the different aspects of experience described in phenomenological models of meditation can be studied empirically using perceptual phenomena like afterimages. It should be noted though that SS-meditators perform kriya yoga, which includes breathing exercises like Sudharshan Kriya and Pranayama. Hence, the effect cannot be solely attributed to SS meditation per se. However, we do think it is likely due to the practice of SS meditation (Srinivasan and Baijal, 2007). An earlier study investigating perception using mismatch negativity (MMN) showed that MMN amplitudes increased immediately after SS meditation but not after Pranayama and Sudharshan Kriya, indicating that perception is influenced by SS meditation per se (Srinivasan and Baijal, 2007). Further studies are needed to clearly delineate the effects to specific aspects of this yoga practice.

3 Conclusion The results of the studies on color afterimages show that our perceptual experience and not just our perceptual performance, are changed by meditation practice. The results show that meditators seem to have a much sharper perceptual experience with color afterimages. More studies are needed to see whether this sharpness extends to other visual stimuli as well as stimuli in other modalities. The neural findings indicate better attentional control (indicated by differences in activation in the right

References

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Acknowledgments This study was supported by a research grant (SR/CSI/27/2010) from the Department of Science and Technology, India. The authors thank the Art of Living Organization especially their teachers in Lucknow and Allahabad who kindly consented and participated in the study.

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Further reading Carrasco, M., Penpeci-Talgar, C., Eckstein, M., 2000. Spatial covert attention increases contrast sensitivity across the CSF: support for signal enhancement. Vision Res. 40 (10  12), 1203–1215. Kozhevnikov, M., Louchakova, O., Josipovic, Z., Motes, M.A., 2009. The enhancement of visuospatial processing efficiency through Buddhist deity meditation. Psychol. Sci. 20, 645–653. Lazar, S.W., Kerr, C.E., Wasserman, R.H., Gray, J.R., Douglas, N., Treadway, M.T., et al., 2005. Meditation experience is associated with increased cortical thickness. Neuroreport 16 (17), 1893–1897. Lutz, A., Brefczynski-Lewis, J., Johnstone, T., Davidson, R.J., 2008a. Regulation of the neural circuitry of emotion by compassion meditation: effects of meditative expertise. PLoS One 3 (3), 1–10. Lutz, A., Slagter, H.A., Dunne, J.D., Davidson, R.J., 2008b. Attention regulation and monitoring in meditation. Trends Cogn. Sci. 12 (4), 163–169. Yeshurun, Y., Carrasco, M., 1998. Attention improves or impairs visual performance by enhancing spatial resolution. Nature 396, 72–75.