Toward a brain theory of meditation

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Toward a brain theory of meditation Antonino Raffonea,*, Laura Marzettib,c, Cosimo Del Grattab,c, Mauro Gianni Perruccib,c, Gian Luca Romanib,c, Vittorio Pizzellab,c a

Department of Psychology, Sapienza University of Rome, Rome, Italy Department of Neuroscience, Imaging and Clinical Sciences, “Gabriele D’Annunzio” University of Chieti-Pescara, Chieti, Italy c Institute for Advanced Biomedical Technologies, “Gabriele D’Annunzio” University of Chieti-Pescara, Chieti, Italy *Corresponding author: Tel.: +39-06-49917787; Fax: +39-06-4462449, e-mail address: [email protected]

b

Abstract The rapidly progressing science of meditation has led to insights about the neural correlates of focused attention meditation (FAM), open monitoring meditation (OMM), compassion meditation (CM) and loving kindness meditation (LKM), in terms of states and traits. However, a unified theoretical understanding of the brain mechanisms involved in meditation-related functions, including mindfulness, is lacking. After reviewing the main forms of meditation and their relationships, the major brain networks and brain states, as well as influential theoretical views of consciousness, we outline a Brain Theory of Meditation (BTM). BTM takes the lead from considerations about the roles of the major brain networks, i.e., the central executive, salience and default mode networks, and their interplay, in meditation, and from an essential energetic limitation of the human brain, such that only up to 1% of the neurons in the cortex can be concurrently activated. The development of the theory is also guided by our neuroscientific studies with the outstanding participation of Theravada Buddhist monks, with other relevant findings in literature. BTM suggests mechanisms for the different forms of meditation, with the down-regulation of brain network activities in FAM, the gating and tuning of network coupling in OMM, and state-related up-regulation effects in CM and LKM. The theory also advances a leftward asymmetry in top-down regulation, and an enhanced interhemispheric integration, in meditation states and traits, also with implications for a theoretical understanding of conscious access. Meditation thus provides a meta-function for an efficient brain/mind regulation, and a flexible allocation of highly limited and often constrained (e.g., by negative emotion and mind wandering) brain activity resources, which can be related to mindfulness. Finally, a series of experimental predictions is derived from the theory.

Progress in Brain Research, ISSN 0079-6123, https://doi.org/10.1016/bs.pbr.2018.10.028 © 2018 Elsevier B.V. All rights reserved.

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Keywords Meditation, Consciousness, Mindfulness, Attention, Brain network, Neuroplasticity, Theory

1 Introduction Meditation can be characterized as a family of mental training practices regulating cognition, emotion, and the self, in which mental and related somatic events are influenced by a specific directing of attention and awareness. As promulgated in several contemplative traditions, mental training based on meditation leads to enhanced awareness, cognitive and emotional regulation, and to mental states characterized by reduced negative (unwholesome) emotions and motives, such as anger, hatred, anxiety, and greed, and by enhanced positive (wholesome) mental states and virtues such as calmness, acceptance, joy, love and compassion (Goleman, 1977). In the last decades, a number of behavioral and neuroscientific studies have revealed the importance of investigating states and traits related to meditation to achieve an increased understanding of cognitive and affective neuroplasticity, attention, awareness and mental states (Cahn and Polich, 2006; Lutz et al., 2008a; Raffone and Srinivasan, 2010). Also clinical applications of meditation based programs are increasingly developed and assessed in a range of clinical conditions and contexts (Cahn and Polich, 2006; Hofmann et al., 2010). Following earlier attempts (Fox et al., 2016; Lutz et al., 2008a, 2015), in this paper we will address the main forms of meditation and will offer a theoretical framework on meditation based on recent theoretical and empirical advances in cognitive neuroscience of consciousness and meditation. We will in particular focus on Buddhist meditation, which is particularly linked to the recent development of secular programs based on mindfulness and compassion, and on our neuroscientific studies with the outstanding participation of Theravada Buddhist monks. In the next section we will characterize the main categories of meditation practices which have deeply influenced recently developed secular programs and have been increasingly studied. Two subsequent sections will provide the bases for our theoretical framework, in terms of recent developments on brain networks and brain states, and of a relevant theory of conscious access based on the notion of global workspace. We will then present the outline of a Brain Theory of Meditation (BTM), including its assumptions, supporting evidence and experimental predictions.

2 Characterizing different forms of meditation and their relationships In science of meditation, the relatively broad set of meditative practices has been usefully classified into two main forms or styles—focused attention meditation (FAM) and open monitoring meditation (OMM)—depending on how attentional and monitoring processes are set (Cahn and Polich, 2006; Lutz et al., 2008a; but

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see Travis and Shear, 2010 for a different perspective). A third important style of meditation includes the two related forms of compassion meditation (CM) and loving kindness meditation (LKM), with focus on particular feelings and intentions (Hofmann et al., 2011; Lippelt et al., 2014). In the FAM (“concentrative”) style, attention is focused on a given object in a sustained manner. The second OMM (“mindfulness” or “bare attention”) style involves the non-reactive monitoring of the contents of ongoing experience, primarily as a means to become reflectively aware of the nature of emotional and cognitive patterns, in a shift of emphasis from contents (e.g., of perception or thought) to processes. Both FAM and OMM techniques involve the moment by moment observations of the experiential field by allowing thoughts, sensations and feelings to arise and pass without clinging to them, in order to develop an internal “witnessing observer” or “mindful observer” (Cahn and Polich, 2006). In FAM high attentional stability and vividness (acuity) are achieved in a mental state of concentrated calm or serene focused attention, denoted by the word Samatha (with the literal meaning of quiescence) in the Buddhist contemplative tradition (Wallace, 1999). By using a telescope analogy, Wallace (1999) observed that in FAM or Samatha meditation, the development of attentional stability may be likened to mounting a telescope on a firm platform, while the development of attentional vividness is like polishing the lenses and bringing the telescope into clear focus. Apart from sustaining attentional focus on an intended object, FAM also involves the regulative skills of monitoring the current focus of attention, detecting distraction caused by external (e.g., sounds) or internal (e.g., feelings or thoughts) sources, disengaging attention from the source of distraction, and refocusing on the intended object (Hasenkamp et al., 2012; Lutz et al., 2008a). Attentional stability and vividness (acuity), as developed in FAM, are regarded as necessary for deep and reliable introspection to take place in meditation, as in the practice of Vipassana (insight) meditation (Wallace, 1999) in Buddhist traditions. Tsongkhapa (1357–1419), an eminent Tibetan Buddhist contemplative and philosopher, uses an analogy to highlight the importance of attentional stability and vividness for the cultivation of contemplative insight (see Wallace, 1999). If an oillamp that is both radiant and unflickering is used at night to light a hanging tapestry, the depicted forms can be vividly observed. By contrast, if the oil-lamp is dim, or even if it is bright but then flickers due to the wind, the depicted images cannot be seen. Thus, both stability of attentional focusing and the temporal resolution (acuity) of attention and consciousness linked to such focus play a crucial role for introspective awareness and insights in meditation. The attentional and monitoring functions of FAM have been related to different systems in the brain involved in attentional control and in selective and sustained attention (Lutz et al., 2008a; see also Weissman et al., 2006). Important neural correlates of FAM functions have been revealed by a functional magnetic resonance imaging (fMRI) study conducted by Hasenkamp et al. (2012). This study elegantly identified different brain regions and networks involved in mind wandering (distraction), awareness of distraction, shifting back to the meditation object, and then sustaining focus on it.

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In OMM, monitoring is reflected in an open-field capacity to notice arising sensory, feeling and thought events within an unrestricted “background” of awareness. In the transition from a FAM to an OMM state, the object as the primary focus is gradually replaced by a sustaining of an open awareness or presence (Lutz et al., 2008a). Behavioral studies have shown a more distributed attentional focus (Valentine and Sweet, 1999), enhanced conflict monitoring (Tang et al., 2007) and reduced attentional blink or more efficient resource allocation to serially-presented targets (Slagter et al., 2007), in OMM meditators. As suggested by Lutz et al. (2008a), OMM can lead to a development of regulatory influences on emotional processes through prefrontal regulation of limbic responses. Indeed, neuroimaging studies have shown that simple verbal labeling of affective stimuli leads to the activation of the (right) ventrolateral prefrontal cortex, and to reduced responses of the amygdala through ventromedial prefrontal cortex activity (Hariri et al., 2000; Lieberman et al., 2007). This strategy of labeling aspects of experience (e.g., “this is unpleasant”; “there is aversion”) is for example used in Vipassana (or insight) meditation, and enables a detached awareness of affective contents in moment by moment experience. OMM can be directly associated to mindfulness meditation (e.g., Cahn and Polich, 2006), although also FAM can play an important role for the establishment of an undistracted and non-reactive mental state enabling accurate monitoring and introspective awareness in meditation, by its stability aspect (Lutz et al., 2008a). Indeed, without a stable focus of attention it is likely to observe mind wandering, as the spontaneous and unintentional “occurrence of thoughts whose content is both decoupled from stimuli present in the current environment and unrelated to the task being carried out at the moment of their occurrence” (Stawarczyk et al., 2011, p. 1). Intensified vividness or acuity of FAM can further support introspective insights or mindful (reflective) awareness about the nature and interplay of mental processes (e.g., physical sensations leading to pain feeling, then to a mental state of aversion and finally to a body reaction during sitting meditation). Finally, FAM and OMM can work synergistically to reduce mind wandering by enhancing attentional stability (FAM) and in reducing identification with thoughts and mood states (OMM). Mindfulness can be characterized as intentional and non-judgmental attention or awareness of experience in the present moment (e.g., Baer, 2003; Kabat-Zinn, 1990). It refers to a vigilant mental state with an immediate and equanimous awareness or monitoring of virtually all mental contents at any given moment, including sensations, perceptions, cognitions and affects (Grossman, 2010). The mindful mental state can be contrasted with states of mind in which the focusing of attention is dissociated from the experience in the present moment, such as mind wandering, which occurs through thoughts, fantasies and self-projections in the past or future, and behaving automatically without awareness of one’s actions (Brown and Ryan, 2003). Mindfulness is generally considered to entail two core components: attention and acceptance (e.g., Malinowski, 2013). According to the influential approach (and related scale) of Baer et al. (2006), mindfulness can be characterized in terms of five aspects or facets: non-reactivity to inner experience; observe (or notice) sensations,

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perceptions, thoughts, and feelings in the present moment; acting with awareness; describe (or label) with words emotional or affective experiences in the present moment; and non-judging of internal experience in the present. Thus, in presence of attentional stability enhanced by FAM and mindfulness enhanced by OMM, conscious mental activity becomes characterized by both stability against reactivity and mind wandering, and flexibility for a rapid and undisturbed access to multiple contents and processes in the fields of present moment experience. It has to be noted that the witnessing observer or meta-awareness function, which is related to the notion of mindfulness, plays a key role in both focused attention and open monitoring meditation facets. Indeed, it is possible to be mindfully aware of all that is currently salient, and it is also possible to be mindful of something in particular by focusing attention toward a stimulus or phenomenon (Kornfield, 1993). It is also possible to focus attention on a given object (such as breath sensations in meditation), and to be reflectively mindful of such focus and any distracting source. Thus, in several meditation practices the focused attention and open monitoring facets can be more plausibly regarded as two sides of the same coin, as in Buddhist insight meditation (e.g., Khantipalo, 1984), with a fundamental role of mindfulness. This is also remarked by Chiesa (2012), “…concentrative and mindfulness meditation practices are no longer described as opposed processes. Instead, several authors recognize that they usually share a common background of focused attention (concentration), which can take different directions depending on the specific meditation form…While the former primarily concerns the stability of the meditative state, the latter concerns the specific phenomenological ‘angle’ from which the receptive field can be observed” (p. 3). Moreover, the acuity or vividness in the Samatha (concentrated calm) mental state developed by focused attention in meditation can be used for insights about the subtle changeability of mental processes and their interplay during open monitoring in meditation as well as in informal practice off the meditation cushion. For example, with a high vividness of mindfulness developed by focusing on the breath, one can rapidly observe the chain of moments of experience during a meal from taste sensations, to pleasure, to desire, to the impulse to grab more food and to the actual movement with the fork or spoon. Finally, pure OMM practices, such as non-referential open presence meditation, do not involve focused attention on an object, although an object in the field of experience such as the breath can still be used as an anchor for mental presence (see Lutz et al., 2007 for a review on different forms of Buddhist meditation). Together with FAM and OMM, compassion meditation (CM) and loving kindness meditation (LKM) are two other important related forms of Buddhist meditation (Buddharakkhita, 1995; Hofmann et al., 2011; The Dalai Lama, 2001). CM focuses awareness upon the aspiration to alleviate suffering of all living beings, and LKM upon loving and kind concern (wish) for their wellbeing and happiness. CM and LKM consist of unconditionally directing these feelings and wishes toward oneself, toward specific others, or to all beings. Generally, practitioners of CM and LKM silently repeat some phrases, such as “may I/you/all beings be happy” or “may I/you/ all beings be free from suffering.” Some CM and LKM practices involve the

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visualization of the mental image of the targets or light from one’s heart toward others or concentrically in all directions to help the generation of loving kindness and compassion feelings and intentions (Sujiva, 1991). CM and LKM share attributes with both FAM and OMM, and are often practiced in synergy with FAM and OMM for the reduction of unwholesome mental states (e.g., anger, hatred) and for the development of virtues (Buddharakkhita, 1995; Hofmann et al., 2011; The Dalai Lama, 2001). Neuroscientific findings about CM and LKM will be discussed in Section 5 in light of the proposed theory.

3 Brain networks, brain states and meditation New paradigms are emerging in cognitive, affective and social neurosciences that emphasize the interactive function of brain areas working together as large-scale brain networks (Fox et al., 2005; Van den Heuvel and Hulshoff Pol, 2010). The study of brain networks and their interactions appears highly relevant for science of consciousness and meditation (Lutz et al., 2015; Malinowski, 2013; Raffone and Srinivasan, 2017). This approach provides new insights into how functionally connected systems in the brain support or constrain cognitive and affective functions (Bressler and Menon, 2010), also with implications for understanding attentional, monitoring and affective functions in meditation. In the theory proposed in Section 5 we will also highlight energetic aspects linked to brain networks and states (Lennie, 2003; Tomasi et al., 2013). Currently, three core brain networks with a central role in coordinating cognitive, affective and interpersonal processing in the brain have been identified: the central executive network (CEN), the default mode network (DMN) and the salience network (SN). The CEN is a fronto-parietal system and is crucial for actively maintaining and manipulating information in working memory, for rule-based problem solving and for decision making in the context of goal-directed behavior. The DMN has been thought to reflect episodic memory retrieval, autobiographical memory, internal thought, self-related and social cognitive processes, value-based decision making emotion regulation, and mind wandering (Rangel et al., 2008). The SN is a cingulate-frontal system, and is involved in detecting, integrating and filtering relevant interoceptive, autonomic and emotional information (Seeley et al., 2007). Neuroimaging research has also suggested that a key function of this network is to identify the most homeostatically relevant among several internal and extrapersonal stimuli to guide behavior by switching on or off other networks (Menon and Uddin, 2010; Sridharan et al., 2008). These key brain networks can be modified through mental training (Tang et al., 2015). It has been shown that in mindfulness meditators DMN activity tends to decrease during their practice (e.g., Brewer et al., 2011; Garrison et al., 2015). This is notable in the context of findings that over-activation of DMN in some psychopathological conditions (i.e., insufficient deactivation during tasks) leads to repeated

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intrusions of DMN activity into the CEN thus causing attention fluctuations and lapses (Broyd et al., 2009; Yordanova et al., 2011). Studies of DMN in older adults undergoing a mindfulness based program have shown that the more mindful participants had an increase in otherwise age-related decreased DMN activity (Wells et al., 2013). Mindfulness meditation may therefore promote an individual’s ability to construct coherent narratives and planning in the service of the CEN. Moreover, studies (e.g., Hasenkamp et al., 2012) also show the central involvement of SN in mindful awareness (of distraction in meditation), pointing to the possibility that through SN switching functions (Menon, 2011) mindfulness meditation training can efficiently train and balance the interactions between all large-scale networks. This has the potential to affect a set of brain functions and states including executive control, cognitive flexibility, emotional regulation, as well as reactions of the autonomous nervous system (see also Malinowski, 2013). Neuroscientific findings have also shown that the interactions within and between brain networks are altered in aging (e.g., Hafkemeijer et al., 2012) and evidence-based models of psychopathology highlighted that altered interactions of key brain networks underlie different psychopathologies (for a review, see Menon, 2011). Indeed, most, if not all, major psychopathologies involve dysfunction of cognitive and emotion regulation processes relying on distributed brain regions that span multiple brain lobes (Menon, 2011). Other studies have shown the effectiveness of mindfulness training in transforming the dynamics of brain networks: remarkably, the same brain networks that are altered in aging and in major psychopathologies are positively influenced through mindfulness practice (e.g., Hasenkamp et al., 2012; Marzetti et al., 2014; Tang and Posner, 2014). Further theoretical advances in neuroscience have linked meditation (mindfulness) practice to brain training, a term that refers to practices that change the brain in ways that improve performance in domains beyond those that have been trained (Tang and Posner, 2014). In relation to this, an important distinction is made between the training of specific brain networks and of integrated brain states. Specific brain networks refer to the neural mechanisms involved in performing a specific task such as keeping a phone number in mind or directing your attention to a particular location. If a brain training regime only trains a specific task, there is little transfer to other tasks. On the other hand, general brain states can be trained in such a way that they exert influence not just on that specific task, but generally on many different tasks. Together with physical exercise, meditation (mindfulness) training is thought to be one of the most widely used methods of training brain states, and probably the most effective one (e.g., Lutz et al., 2008a; Tang and Posner, 2014; Tang et al., 2007, 2015). Recently, Raffone and Srinivasan (2017) have suggested that the effects of mindfulness meditation training on a broad range of cognitive functions (e.g., multiple attentional functions, facets of cognitive control, working memory, perceptual awareness, episodic/autobiographical memory, domains of problem solving and thinking) can be mediated by multiple demand (MD) regions in the brain (see also Raffone and Srinivasan, 2009), thus plausibly involving the interplay of multiple brain networks in integrated brain states. The MD areas are involved in a common pattern

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of activity that is a salient part of the brain’s response to many different kinds of cognitive challenge or tasks. This MD pattern extends over a specific set of regions in prefrontal and parietal cortices, with a particular involvement of the region in and around the posterior part of the inferior frontal sulcus, in the pre-supplementary motor area and adjacent dorsal anterior cingulate, in the anterior insula and adjacent frontal operculum, in and around the intraparietal sulcus, and part of the rostrolateral (anterior lateral) prefrontal cortex (Duncan, 2010; Duncan and Owen, 2000). The MD brain regions also appear to largely overlap with the CEN and the SN, with key roles in orchestrating brain states. These regions are characterized by a high sensitivity to mindfulness meditation training (for reviews, see Malinowski, 2013; Tang et al., 2015), with an involvement in multiple forms of meditation (Fox et al., 2016). Furthermore, EEG and MEG investigations suggest the importance in meditation of large scale coherent oscillatory patterns in the brain, which are plausibly involved in integrated brain states (e.g., Hauswald et al., 2015; Lutz et al., 2004; Marzetti et al., 2014; Murata et al., 2004; Zalesky et al., 2014). These patterns can thus support interactions between neurons in MD areas and widespread neurons in the brain that could underlie flexible regulatory processes associated to enhanced cognitive and affective functions with mindfulness meditation training (see also Raffone and Srinivasan, 2009). In the next section we will focus on a theory of consciousness which is relevant for the theoretical development proposed in Section 5.

4 Conscious access, global workspace and meditation The major brain networks with a central role in coordinating conscious cognitive and affective processes, as well as MD regions, can be linked to the influential notion of Global Workspace (GW) for conscious access and processing. Indeed, conscious access is an important function in cognition, emotion regulation and meditation practices. In respect to the latter, ongoing conscious access to the meditation object (e.g., changes in breath sensations) takes place in FAM, while conscious access to a range of contents in the fields of present moment experience occurs in OMM (see also Raffone and Srinivasan, 2009). The GW, which can be particularly related with CEN and SN networks (Dehaene et al., 1998; Raffone and Srinivasan, 2017), enables conscious access to contents represented in different processing modules, i.e., encoded in widespread brain areas. The notion of GW was first proposed in the Global Workspace Theory (GWT) of Bernard Baars (Baars, 1988, 1997; Baars et al., 2003), which is currently one of the most influential theories of human consciousness and its neural correlates, also with implications for an increased theoretical understanding of meditation (Raffone and Srinivasan, 2009). In GWT, the GW conscious system enables an ongoing gateway to a large set of active representations in different modules of the brain, making them integrated and accessible in consciousness. By contrast, in unconscious sensory processing these modules process information in a substantially segregated fashion.

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In GWT a key role is played by broadcasting of selected contents in and from the GW, and in this way conscious information can be widely disseminated in the brain. In this broadcasting process perceptual inputs can be intentionally enhanced, new memories and motor responses can be selected, and sequence of thoughts can be generated in both task-related and task-unrelated (mind wandering) forms. Furthermore, in GWT the unconscious contextual systems in the brain play a role in shaping conscious events, acting as a “backstage in the theatre” in which GW conscious contents are selected. Such contexts work to constrain conscious events, with motives and emotions viewed as goal contexts, and executive functions working as hierarchies of goal contexts (see also Baars and Franklin, 2003). According to Baars, self-related information forms the most basic unconscious context for all conscious experience, thus with the implication of the DMN for such function. OMM can be regarded as a form of meditation for introspective or reflexive access to such otherwise implicit contexts of conscious experience (Lutz et al., 2008a, 2015). Finally, endogenous states influencing perception and conscious processing can be related to the notion of mental state (Barendregt and Raffone, 2013; Salzman and Fusi, 2010), as a background of conscious access and processing taking place in the GW. The SN in particular can play a key role for feelings and mental states implicated in conscious experiences in the GW (see also Craig, 2009), in interaction with the limbic network, thus acting as a hub for state-related aspects in GW processing, including in meditation. The CEN (e.g., dorsolateral prefrontal cortex) would be complementarily involved in processing conscious contents in the GW (Dehaene et al., 1998; Raffone et al., 2014). In particular, emotions may exert a deep influence on both unconscious and conscious processing, with the latter involving the GW. As remarked by LeDoux (2000), by its projections to cortical areas, the amygdala can influence perceptual and shortterm memory processes, as well as processing in higher-order areas including GW areas, such as in the SN. The amygdala also projects to nonspecific systems involved in the regulation of arousal and bodily responses (behavioral, autonomic, endocrine), and can thus influence cortical processing indirectly. Thus, after a fast unconscious response which is effective at an unconscious level on the mind and body state (e.g., arousal and unpleasant feeling after seeing an apparently dangerous spider), an emotional stimulus can access consciousness with a GW representation (conscious thinking about the spider). A mindful mental state may plausibly enable a faster conscious access to and regulation of feelings and emotions associated to a given stimulus (such as the seen spider), in terms of top-down inhibition of the amygdala and posterior insula by orbitofrontal and anterior cingulate cortices (Salzman and Fusi, 2010), thus resulting in reduced physiological and behavioral reactivity (KabatZinn, 1990). In Section 5 we will suggest mechanisms of regulation of emotional reactivity and mind wandering linked to FAM and OMM. The Global Workspace Theory has been revised over the last few years to emphasize dynamic aspects and processing flexibility (Baars et al., 2013). In this more recent version of the approach the GW is considered a functional capacity for dynamically coordinating and propagating neural signals over different task-related

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networks. The GW notion of Baars has been revisited by others in terms of the Global Neuronal Workspace model (Dehaene and Naccache, 2001; Dehaene et al., 1998, 2006, 2011), which proposes that the neural basis of conscious access is a sudden self-amplifying process or ignition leading to a global brain-scale pattern of activity. Related to the Global Neuronal Workspace model, following the lead of computational modeling investigations based on GW principles (Raffone and Pantani, 2010; Simione et al., 2012), a Theory of Attention and Consciousness (TAC) (Raffone et al., 2014) has been developed. TAC provides a neurocognitive characterization of processing from early stages of sensory processing to encoding in working memory, with a novel taxonomy of attentional functions, including attentional filtering, attentional selection and top-down attentional modulation, as also related to conscious access in the GW. An extension of the theory may further include attentional processes and conscious access toward stimulus-independent (intrinsic) mental contents, as well as the role of self-related representations, in association with the DMN and its interplay with other brain networks. Such developments linked to the GW notion may have important implications for an increased understanding the mechanisms of attention, consciousness and emotion regulation in meditation, as well as for a sharper neurocognitive characterization of mindfulness.

5 Outline of a brain theory of meditation (BTM) The cost of a single neuronal action potential (spike), which arises in restoring ionic balances perturbed by synaptic potentials and the action potential as well as in the release and reuptake of neurotransmitter at synapses, is high (Attwell and Laughlin, 2001). Thus, the fraction of the neurons that can be concurrently active (with an enhanced firing rate), in the human cortex in a given task is fewer than 1%, as calculated in the influential work of Lennie (2003). This must also limit the range of tasks that can be undertaken concurrently. Mind wandering, which is highly recurrent in everyday life (Killingsworth and Gilbert, 2010) and has been related to the activation of the DMN and the CEN (Christoff et al., 2009), has plausibly a high impact on the necessarily limited aggregate neural activity at any time in the human cortex. Therefore, during mind wandering significantly less aggregate neuronal activity becomes available for currently relevant tasks to be performed, in particular when such tasks demand attention and resources for conscious controlled processing. Reciprocally, for the same limitations in aggregate neuronal activity less mind wandering is likely to take place during the performance of tasks demanding more attention and neuronal activity resources for conscious controlled processing (e.g., Singer, 2009). It is well established that meditation and mindfulness practices regulate mind wandering and the activity of the DMN (Di Francesco et al., 2017; Tang et al., 2015). Moreover, several studies show that meditation and mindfulness practices influence key regions in CEN, DMN and SN (see also Lutz et al., 2015), as well

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as the MD system of the brain, which may plausibly mediate the range of salutary effects of these practices on cognitive and affective functions as well as physical and mental health (Raffone and Srinivasan, 2017; Tang et al., 2015). Given their widespread converging and diverging connectivity patterns in the brain, such networks can play a key role in regulating the allocation of the limited energy for neural activity of the human cortex. Therefore meditation and mindfulness practices might train more efficient brain states with a higher regulation of energy consumption in the human brain, in combination with training of the limited capacity processing resources of attention, cognitive control and conscious processing (Lutz et al., 2008a; Malinowski, 2013; Raffone and Srinivasan, 2010). At the Institute for Advanced Biomedical Technologies (ITAB) of Chieti (Italy) we have conducted neuroscientific studies that can shed light on the effects of meditation and mindfulness on the regulation of brain states and networks, and thus contribute to provide the bases for the theoretical development proposed in this paper. In our functional Magnetic Resonance Imaging (fMRI) study (Manna et al., 2010), with the outstanding participation of Theravada Buddhist monks with expertise in both FAM and OMM, we found decreased activity in FAM (with focus on breath sensations) as contrasted with both a non-meditative rest condition and OMM in a set of temporo-parieto-frontal cortical areas, including areas in DMN, CEN and SN. We found a particular involvement of associative cortical areas in the left hemisphere in such decreased activities, though also with the implication of the same regions in the right hemisphere. Areas in the right dorsal anterior cingulate cortex and anterior medial prefrontal cortex were instead activated in FAM as contrasted with the other conditions. As revealed by contrasting FAM with both rest and OMM, and OMM with rest, the pattern of brain activations in OMM resembled the pattern in rest, though with the higher activation of three left associative cortical areas (in medial prefrontal, parietal superior and temporal superior regions) in OMM as contrasted with rest. In our subsequent magnetoencephalographic (MEG) study (Marzetti et al., 2014), with the same participants and design, we focused on the coupling (phase coherence) of the oscillatory activity of posterior cingulate cortex (PCC), a key hub of the DMN, with the activity of other areas of the brain in FAM, OMM and in the non-meditative rest condition. We found a reduced coupling in the alpha band between PCC and other brain regions in DMN, CEN and SN areas, in particular in the left hemisphere, in FAM as compared with both rest and OMM (Fig. 1). In further phase coherence analyses of the MEG data above we have extended our focus to a subset of key nodes in DMN, SN and CEN, by investigating their mutual coupling in FAM, OMM and non-meditative rest (Raffone et al., n.d.), in different oscillatory bands. We have found a generally decreased coupling among nodes within and between such networks in multiple oscillatory bands (delta, theta, beta and gamma) in both FAM and OMM as contrasted with the non-meditative rest condition, thus suggesting a global effect at the level of such networks and interacting hubs in the brain.

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FIG. 1 (A) Brain regions connected to the Posterior Cingulate Cortex (PCC) more during REST than while performing FAM; (B) brain regions connected to PCC more during OMM than during FAM; (C) schematic of the MEG block design protocol: each monk performed a balanced number of REST, FAM and OMM sessions. Adapted from Marzetti, L., Di Lanzo, C., Zappasodi, F., Chella, F., Raffone, A., Pizzella, V., 2014. Magnetoencephalographic alpha band connectivity reveals differential default mode network interactions during focused attention and open monitoring meditation. Front. Hum. Neurosci. 8, 832.

In light of the results above with fMRI and MEG experiments, other relevant neuroscientific and meta-analysis studies, the meditation categories (attributes), and theoretical paradigms reviewed above, here we outline a Brain Theory of Meditation (BTM), which is articulated in the following explanatory domains.

5.1 Interplay of brain networks and integrated brain states in meditation Meditation practice crucially involves the interplay of the major brain networks in integrated brain states, with particular reference to the central processing networks CEN, SN and DMN, and the coupling of these networks with other cortico-thalamolimbic regions involved in attentional processes, states of consciousness (including meditative absorptions, see Goleman, 1977), conscious access to selected perceptual and thought contents, metacognitive and interoceptive awareness, cognitive control and emotion regulation.

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5.2 Brain mechanisms of focused attention meditation In association with the notion of meditative quiescence (Samatha in Buddhist tradition), FAM can lead to a reduced activation of CEN, SN and DMN areas (see also the review and meta-analysis of Fox et al. (2016) for decreased activities in the DMN in FAM), and of their coupling with other brain regions involved in emotion, motivation (drives), and thinking processes, thus providing a neurodynamic substrate for the reduced reactivity, identification, mind wandering and judgments which are observed in meditation and mindfulness practices incorporating FAM. In terms of theories of consciousness based on the notion of global workspace (GW), FAM reduces mandatory access to salient perceptual, emotional and thought contents in the GW, and thus the amplification and ignition processes leading to increases of neural activity in the brain related to conscious access (see Section 3). Such reduction or down-regulation, endogenously dependent on a mental state induced by the set of attention and mindfulness in FAM, would be highly relevant in light of the severe limitation of concurrently activated neurons in the human cortex (Lennie, 2003). In other words, FAM would enable a sharpening of neuronal activities in the major brain networks with a more focused and efficient use of neuronal resources in a given task. According to BTM the skills of efficient regulation of concurrent demand for neural activity in the brain acquired through FAM, with the involvement of MD areas, are regarded as transferable to multiple task settings. Thus, FAM can have a high impact on the efficiency of the moment by moment management of the highly limited aggregate neural activity (energy) in the human cortex across tasks, with a down-regulation of unnecessary or interfering neural activities across brain networks.

5.3 Brain mechanisms of open monitoring meditation In association with the key notion of “witnessing observer” in meditative practices emphasizing open monitoring and mindfulness, OMM leads to a flexible modulation of neural activity propagation or broadcasting of signals in the major central networks of the brain orchestrating large scale recurrent (reentrant) neural interactions in cognitive, affective and interpersonal processing. Our earlier MEG study (Marzetti et al., 2014) showed in particular an enhanced coupling between PCC and the left intraparietal sulcus (a key MD region of the brain) in the alpha band during OMM as compared to non-meditative rest, which could be used for selective broadcast of signals during mindful conscious access in OMM. The subsequent MEG analyses (Raffone et al., n.d.) reveal down-regulated dynamic links within and between key nodes of CEN, SN and DMN in delta, theta, beta and gamma oscillatory ranges in OMM as compared to non-meditative rest, except for the alpha band for which the two conditions do not differ.

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Given that alpha oscillations have been linked to gating of information by inhibiting task-irrelevant regions, thus routing information to task-relevant regions (Jensen and Mazaheri, 2010), coupling within and between CEN, DMN and SN during OMM in the alpha band, unlike other oscillatory ranges, would plausibly prevent proliferative mentation (mind wandering and emotional reactivity) and enable a selective and efficient reentrant signaling in the brain supporting mindful conscious access and insight. This process would resemble the brainweb for conscious experiences suggested by Varela et al. (2001), with the meditation-enhanced capacities of selective gating and tuning. Interestingly, in the upper alpha range we found that coupling is higher in OMM as compared to FAM between a subset of nodes in CEN, DMN and SN, thus suggesting a possible prominence of a gating-related coupling in this band during OMM. As for FAM (see above), BTM suggests that the skills of efficient management of communication within and between brain networks acquired through OMM practice can be transferred to multiple contexts and task performance conditions. OMM can also have a high impact on the efficiency of the management of the highly limited aggregate neural activity (energy) at any time in the human cortex with a sharpening of reentrant signaling within and between brain networks via complementary gating of interfering inputs and routing of selected contents. For example, Slagter et al. (2007) showed a more efficient allocation of attentional and conscious access resources after an intensive OMM training. A linked study (Slagter et al., 2009) found an increased theta synchrony supporting conscious perception of a second target in a rapid visual serial presentation after an intensive OMM training.

5.4 Differentiating the brain mechanisms of FAM and OMM While FAM optimizes brain energy by narrowing the subset of firing neurons during a given time window in the brain, OMM optimizes brain energy by tuning (gating or enhancing) the communication between widespread neurons with higher firing rates in a given time window. This proposal appears more functionally elaborated and plausible as compared to the earlier transient hypofrontality hypothesis of Dietrich (2003), according to which mental states commonly referred to as altered states of consciousness, including meditation states, are principally due to transient prefrontal cortex deregulation. The transient hypofrontality hypothesis thus appears over-general in respect to the undifferentiated consideration of meditation (irrespective of its forms) and other mental states, as well as for an undifferentiated consideration of prefrontal cortex regions. However, BTM shares with the transient hypofrontality hypothesis the consideration of the down-regulation of brain activities in meditation, with a key role of anterior brain regions, in particular reference to FAM. BTM predicts a higher aggregate neural activity in OMM as compared with FAM, with a particular involvement of SN, DMN and CEN. The theory also predicts a lower time-integrated neural activity in performing a range of cognitive tasks in FAM as compared to non-meditative rest and OMM, thus with the predicted lower demand of brain network (state) energy in FAM, for a given level of performance.

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Another BTM’s prediction is that there are more efficient transitions between different tasks and sub-tasks in OMM-related states and traits (see also Slagter et al., 2007). A lower aggregate oscillatory coupling in multiple bands (except for the alpha band) in FAM and OMM as compared with non-meditative rest, with a particular involvement of SN, DMN and CEN, in particular in the left hemisphere, is furthermore predicted. BTM furthermore predicts an enhanced repetition priming in meditation states and traits, mediated by the down-regulation and tuning processes in FAM and OMM. Neuroscientific studies of priming, the facilitation in accuracy and response time in processing a repeated stimulus, have most often shown reductions in neural activity, both at the level of neuronal activity in nonhuman primate recording (Li et al., 1993; Miller et al., 1991), and at the level of aggregate measures of neural activity based on hemodynamics in humans (e.g., Buckner et al., 1995; Henson et al., 2000). It has been suggested that changes in processing efficiency are associated with a “sharpening” or “tuning” of the neuronal responses within cortical areas that represent perceptual attributes of the repeatedly presented stimulus (Desimone, 1996; Wiggs and Martin, 1998). BTM predicts that FAM modulates the repetition priming effect by reducing both neural activation levels and (oscillatory) coupling between involved neuronal populations, whereas OMM modulates it by affecting (oscillatory) coupling to a larger extent than FAM.

5.5 Brain mechanisms of compassion meditation and loving kindness meditation Also CM and LKM modulate the state of brain networks, with particular reference to CEN, SN and DMN, and their interplay in brain states, as related to their salutary effects on mental and somatic states. In particular, in their forms with OMM features, in terms of non-referential compassion and loving kindness (in any condition toward all beings), CM and LKM would enhance coherence in large scale resonant assemblies in the brain, as shown by Lutz et al. (2004) in the gamma frequency range (i.e., 25–42 Hz). In association with their effects on mental states, with enhanced positive emotions and motives (Fredrickson et al., 2008), CM and LKM affect the GW for conscious access by increasing the likelihood that attention and conscious access select skillful percepts, thoughts and actions, rather than contents and responses driven by negative emotions (e.g., worry, anger) or greed/craving. Even if the amygdala can be activated as a neural substrate of the empathic facet of compassion in reaction to stimuli linked to pain of others (Lutz et al., 2008b), CM practice, in combination with the cultivation of attentional stability and mindfulness through FAM and OMM, can prevent emotional contagion. A mediation of anterior cingulate cortex and anterior insula in the SN would play a key role in such top-down regulation of the GW, brain networks and states (see Lutz et al., 2008b). Similar neurodynamics can take place in the contemplative cultivation of sympathetic joy (Buddharakkhita, 1995; Hofmann et al., 2011; The Dalai Lama, 2001).

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Thus, according to BTM FAM can down-regulate the activation and coupling patterns associated to emotional reactivity, judgments, drives and mind wandering, by involving the major brain networks in this regulation, while focusing and monitoring attention. OMM can modulate the coupling of such networks by gating and selective enhancement mechanisms, while monitoring the whole field of experience. CM and LKM can enhance or up-regulate activities in the networks and their dynamic links in the brain which are resonant with the amplified states of compassion and loving kindness. LKM in particular would involve an intensified coupling between PCC and left inferior frontal gyrus, a region implicated in emotion and cognitive control, as suggested by fMRI results (Garrison et al., 2014).

5.6 Left-brain dominance for top-down regulation in meditation The findings of Manna et al. (2010) and Marzetti et al. (2014) further suggest a particular implication of areas in the left (dominant) hemisphere in the modulation of neural activation and coupling patterns in FAM and OMM. A prominent involvement of clusters in the left hemisphere in meditation practices also appears in the review and meta-analysis of Fox et al. (2016). BTM thus hypothesizes that left MD areas of the brain linked in particular to CEN and SN play a key role in the higher-order regulation of brain and related somatic states in meditation. The “witnessing or mindful observer” in meditation may thus in particular implicate left higher-order integrative areas in key brain networks, flexibly and without the mandatory involvement of conceptual interpretations and language. This BTM’s hypothesis can be related to the notion of “left-brain interpreter” proposed by Gazzaniga and LeDoux (1978), later endorsed by Baars (1997) in terms of an executive interpreter in conscious processing mediated by the GW. It can also be related to the classic model of Luria (1973) of the “working brain,” in which left prefrontal areas are at the highest level for cognitive control and the top-down regulation of functional systems and states in the brain. The hypothesis can furthermore be related to the asymmetric sampling in time hypothesis (Poeppel, 2003; Poeppel and Hackl, 2008), according to which the left hemisphere is more effective in processing or temporal integration within short time windows (around 25–50 ms) as compared to the right hemisphere. The latter hypothesis is based on converging evidence (Belin et al., 1998; Zatorre and Belin, 2001) suggesting that slow, low-frequency temporal features (around 200 ms; 3–7 Hz; syllables) are biased to right hemisphere auditory cortex, whereas fast, high-frequency temporal features (around 20–50 ms; 20–50 Hz; phonemes) are biased leftward. These biased processes can plausibly extend to other areas of the hemispheres involved in attentional and conscious access (GW) functions. In BTM, effectiveness in fast integration of signals in key brain networks would support both a higher vividness (acuity) in conscious access (see Section 2) and a rapid modulation of brain states in meditation and in association with meditation traits. Finally, the hypothesis is aligned with the theoretical proposal of an anterior cerebral asymmetry for emotion processing (Davidson, 1992), with positive emotions,

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which are likely to be developed in meditation practices, processed dominantly in left anterior areas of the brain. Indeed, functional studies based on EEG have reported a leftward bias of frontal brain activity linked to positive emotion in meditators (Davidson et al., 2003; Moyer et al., 2011). The study of H€ olzel et al. (2010) found increased gray matter in the left hippocampus of mindfulness meditators. In another structural neuroimaging study (Luders et al., 2011) long-term meditation practitioners were reported to have a significantly higher fractional anisotropy (a measure thought to reflect fiber density, axonal diameter and myelination in white matter) in the superior longitudinal fasciculus, a major association fiber tract that connects frontal, occipital, parietal and temporal lobes, with even more pronounced effects in the left than the right hemisphere. Asymmetries in the volume of the superior longitudinal fasciculus have also been associated to MEG functional characteristics related to alpha band inhibition in selective attention, i.e., oscillatory power in the occipital cortex (Marshall et al., 2015) and connectivity between the occipital cortex and the superior parietal cortex (D’Andrea et al., 2018), thus supporting the idea that the observed higher superior longitudinal fasciculus values in meditators (Luders et al., 2011) might be related to their enhanced inhibition abilities. Another recent study (Kurth et al., 2015) of brain structural asymmetries in long-term meditation practitioners has found a leftward gray matter asymmetry in the superior parietal lobe, a key region for the control of attention (Corbetta and Shulman, 2002) and executive (GW) functions (Dehaene et al., 1998). Taken together, these findings suggest increased leftward gray matter asymmetries in the set of associative cortical regions subserved by the superior longitudinal fasciculus, thus supporting our hypothesis. Taking together the views above, BTM thus predicts a relatively more accurate time perception with longer as compared to shorter intervals (involving the relatively more activated right hemisphere) in FAM meditation (with a predicted rightward asymmetry in neural activation), and a more accurate perception with shorter as compared to longer intervals (involving the left hemisphere) in CM and LKM (with a predicted leftward asymmetry in neural activation) (Poeppel, 2003; Poeppel and Hackl, 2008).

5.7 Enhanced inter-hemispheric integration in meditation states and traits Together with the left-brain dominance in top-down regulation, BTM also suggests an enhanced inter-hemispheric integration in meditation states and traits, with particular reference to anterior brain areas. This is in alignment with longitudinal and cross-sectional structural neuroimaging data showing a higher thickness or fractional anisotropy of the anterior (frontal) part of the corpus callosum in meditators (Luders et al., 2011, 2012; Tang et al., 2010, 2012). In meditators, the top-down regulation of brain states generated in left anterior regions can thus be more effectively propagated to connected right brain networks, such as right anterior insula (in the SN), playing a crucial role in interoceptive awareness and emotion regulation (Craig, 2009), and

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with a higher thickness in long-term meditators (Lazar et al., 2005). Reciprocally, key areas for cognitive and affective regulation in the right hemisphere, such as right anterior insula, can rapidly propagate signals to the left brain networks that generate the major transitions in the endogenous regulation of global brain states, based on mindfulness. In such coordinated exchanges, areas in the right hemisphere, suggested to be characterized by longer time-integration windows (about 200 ms) (Poeppel, 2003; Poeppel and Hackl, 2008), such as the right insula, would gradually accumulate interoceptive, homeostatic, environmental, hedonic, motivational and cognitive-social information. Craig (2009) suggested a progressive accumulation or integration from posterior to anterior regions of the insula corresponding to emotional moments across time, a phenomenon also plausibly linked to time perception. In coordination with the right anterior insula, left SN (anterior insula and anterior cingulate cortex) and CEN areas would ignite a discrete transition in the GW (Dehaene and Changeux, 2005) for a conscious regulation of the momentary brain/mind state. Manna et al. (2010) found a pronounced deactivation of insular regions in both hemispheres in FAM, though more pronounced in the left hemisphere, as compared to non-meditative rest and OMM. In accordance with the proposed theory, the massive deactivation of insula in FAM in the long-term meditators would attenuate interference with the focus on the meditation object of any source in the fields of experience whose associated emotional and motivational states are integrated through the right insula and hypothetically transmitted to the left insula to influence the reallocation of attention and then conscious access. Such deactivation was not observed in OMM, in which regulation plausibly occurs at a later stage in mindful conscious access. BTM thus predicts a leading involvement of areas connected by the anterior (frontal) part of the corpus callosum across hemispheres and the superior longitudinal fasciculus within hemispheres in transitions of oscillatory coupling induced by the different forms of meditations (as also compared with non-meditative rest), with higher couplings in the left hemisphere in (non-referential) CM and LKM as compared with OMM. The theory also predicts an enhanced functional connectivity between right and left (anterior) insula (as compared with non-meditative rest), with in particular a stronger oscillatory coupling in the alpha band, during OMM; by contrast a reduced functional connectivity is predicted to be observed in FAM (as contrasted with non-meditative rest).

5.8 Implications for conscious access theories BTM advances a new look at the top-down regulation of the major brain networks and their coupling with implications for brain states, mental states and consciousness. Based on insights from meditation research, BTM suggests that the GW for conscious access and processing can be functionally reorganized by meditative states and traits, rather than representing a fixed set of processors in a given state for conscious access. The configuration of GW processors would thus be dynamic rather

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than static, with a range of working states beyond a simple vigilance state underlying its operations (Dehaene and Changeux, 2005; Dehaene et al., 2006). Moreover, BTM suggests mechanisms for the down- and up-regulation of GW distributed processors, differential roles of brain oscillatory patterns and of the two hemispheres, based on insights from meditation studies. The theory advances a principle of complementarity of gradual accumulation processes in the right hemisphere with discrete transition processes in the left hemisphere in a revised GW for conscious access, in alignment with recent theoretical proposals about consciousness and mental programs (Raffone et al., 2014; Zylberberg et al., 2011). BTM further suggests an enhanced coordination of GW processes in the two hemispheres for conscious access in meditators, due to more efficient anterior inter-hemispheric connections.

5.9 Meta-function of brain regulation and flexible resource allocation More generally, according to BTM meditation provides a meta-function for an efficient brain/mind regulation, and a flexible allocation of highly limited and often constrained (e.g., by negative emotion and mind wandering) brain activity resources, which can be related to mindfulness. Indeed negative emotions and drives likely boost mind wandering (Smallwood et al., 2009), which in turn tends to feed negative mental states (Killingsworth and Gilbert, 2010). Breaking such loops is often hard, such as in depression (with the occurrence of rumination), which has been linked to excessive DMN activity and connectivity between DMN and subgenual cingulate cortex in the SN (e.g., Connolly et al., 2013). The down-regulation and gating/tuning functions associated to FAM and OMM, respectively, together with the positive (wholesome) up-regulations of CM and LKM, can plausibly break such loops and enable a more free and wholesome allocation of the highly limited brain resources at any mindful moment. BTM thus predicts a lower aggregate neural activity in DMN and CEN in mind wandering (Christoff et al., 2009), more reduced neural activity in DMN and CEN in mind wandering with meta-awareness as compared to mind wandering without meta-awareness, and reduced DMN–CEN coupling related to mind wandering, in meditators as compared to non-meditators.

5.10 Further development of the theory A further development of BTM will need to address the roles of effort and expertise in meditation (Brefczynski-Lewis et al., 2007; Tang et al., 2015). Moreover, the potential implications for aging and psychopathology, which have both been related to the major brain networks (see Section 3), can be usefully investigated. Finally, the involved brain processes and mechanisms need to be specified to a larger extent, possibly also with the aid of computational modeling investigations, in combination with further experimental studies.

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Acknowledgments We would like to dedicate this work to Prof. Chandrasekhar Pammi of the University of Allahabad who suddenly passed away in February 2018, with our acknowledgments of his contributions to research on cognitive and computational neuroscience aspects of decision making, sequence learning and spatial navigation, as well as of his outstanding humanity and kindness. We would like to thank the monks of Santacittarama Buddhist Monastery and associated monasteries for their outstanding participation in our studies. We would also like to thank Prof. Joseph Glicksohn and another anonymous reviewer for their helpful comments and suggestions leading to a much improved manuscript. A.R. has been supported by the grant from BIAL Foundation (Portugal) on the project “Aware Mind-Brain: bridging insights on the mechanisms and neural substrates of human awareness and meditation.” L.M. has been supported by the BIAL Foundation Grant 66/2016 “Mindfulness Meditation shapes synchronization of brain networks for effective perceptual decision making.”

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