René Descartes famously stated, “I think therefore I am.” A concept centered around the idea that the existence of our meta-conscious thought proves our existence. Furthermore, it denotes a sense of self-derived from the presence of our thinking. What if this famous idea is wrongly reversed? What if our perceived sense of self derives from our thoughts, and these thoughts act as an illusion of the true nature of the self?
A couple of my posts have focused on the idea that the calm mind, potentially derived from a practice of meditation, can achieve a heightened sense of awareness. Some neuroscientists now view the mind as a predictive modeling machine (Seth, 2013), constantly receiving signals from both internal and external sources, generating predictions and models to understand the current condition. This theory inspired me to create an analogy of a calm pond: Imagine the brain and mind as a pond, and instead of neuronal signals, raindrops are falling into the pond. When the pond is calm, and a single drop falls, the pond’s ripples provide adequate information to deduce the location and size of the raindrop. By observing the single ripple, one can simply understand the raindrop. However, if there is a storm and many raindrops impact the pond simultaneously, then the ripples are indistinguishable. This makes the analysis of the incoming information near impossible. This may be how the brain works. This would be why calming the mind generates such benefits in health because the brain can analyze the information accurately and execute the proper response. This idea is supported by scientific evidence that interoception increases with mindfulness practice. I have alluded to this idea as a possible explanation of why meditation generates a higher form of consciousness. More on this later.
To further explore this idea, a deeper exploration into the neuroscience of internal mental processes is required. The areas of the brain that are clinically recognized to perform internal mental operations are known as the default mode network (DMN) (Ekhtiari et al., 2016; van Buuren et al., 2010). The DMN is not a single area of the brain but a network and interaction between many areas. The brain areas involved within the DMN include the medial prefrontal cortex (mPFC), the anterior and posterior cingulate cortex (ACC and PCC), temporoparietal junction (TPJ), later temporal cortex (LTC), and the temporal pole (TempP)(Farb et al., 2007; Zhou et al., 2020). In general, the mental processes conducted by the DMN are self-referential processing, long-term memory retrieval, and mind-wandering (Ekhtiari et al., 2016; Marstaller et al., 2017; Spreng & Grady, 2010; van Buuren et al., 2010). However, the functions expand beyond just those. Different brain areas carry differing roles in these processes. For example, the PCC plays a unique role in the autobiographical retrieval process and plays a role in self-centered spatial navigation (Hamilton et al., 2015). However, sometimes these processes manifest in more complex interactions. For example, both the PCC and anterior portion of the mPFC (amPFC) facilitate self-referential processes and the interaction between other hubs of the DMN (Zhou et al., 2020). The role of the DMN is complicated, but its relationship to meditation is significant.
The DMN’s plays a significant role in mental ruminations and the activity of the mind. In our modern culture, mental ruminations are commonplace and widely accepted. With this cultural norm, there is no adequate training to properly handle these thoughts when they become repetitive, unconstructive, and potentially destructive. Repetitive unconstructive ruminations are associated with and can lead to depression (Watkins, 2008). Therefore, this mental habit attributes to a significant source of many mental health issues. It is a primary reason why meditation seems to be such an effective mental health benefiting practice. In Eastern traditions, this unhealthy mind is called the “monkey mind”: a mind that swings from thought to thought, often time traveling to the past and future. Meditation, and similar practices, aim to quiet this monkey mind. From a clinical perspective, it is fascinating to consider that the DMN may be a neural network representing the monkey mind’s activation. There is research to support this idea as well. Autobiographical memory retrieval processes activate the DMN (Spreng & Grady, 2010). Additionally, the DMN seems to maintain a cohesive perception of the self across time to interpret novel information (Marstaller et al., 2017). Clearly, not only is the DMN involved in processes that involve thoughts about the self, but it is also primarily responsible for our mental time traveling processes. If meditation aims to bring our experience to the present, then the DMN is the antithesis.
As previously stated, mental ruminations and other unconstructive thought patterns drive the development of mental health issues such as anxiety and depression. Given that the DMN has a strong relationship to these thought patterns, it is also interesting to note that DMN activity dominance is associated with the development of depression (Hamilton et al., 2011). The brain areas that seem to be activated more often during depression are the anterior and dorsal regions of the mPFC, PCC, temporal lobes, and the TPJ (Zhou et al., 2020)—further suggesting that the DMN is the brain region highly responsible for our inner self-referential thoughts, our time traveling thoughts, and the subsequent mental health outcomes.
The DMN represents, in large part, the mental activity of the mind that removes us from a calm and present state of being. In other words, it adds more “raindrops” to the calm pond (my analogy from before) making it harder for the brain to analyze and adequately react to incoming information. Evidence for this idea lies in the observation that the DMN is responsible for monkey mind-like processes and in learning and conditioning. Again, the brain is constantly receiving neuronal signals from the body. Say it receives a signal from the toe: it must first predict that the signal came from the toe, then understand what the signal meant, and react accordingly. So, if the signal was a pain signal, the brain may command the toe to lift from the ground. If the signal stops, the brain knows the toe is no longer in pain, verifying the prediction. If the signal doesn’t stop, further trial and error are required. This is a simple example, but the brain is likely processing and reacting to signals like this all the time, both from information coming from outside the body and within. Therefore, much learning and prediction model generation is taking place. Imagine the famous experiment of Pavlov’s dogs. The dogs learned that a particular cue meant food, and their bodies learned to react accordingly. This learning and conditioning are a fundamental aspect of biological life. The DMN plays a significant role in this learning within our brain. For example, the PCC responds to error detection, and the signal is amplified when small rewards or novel stimuli are introduced to the experience (Heilbronner & Platt, 2013). Areas of the DMN (such as the mPFC and PCC) are also thought to be involved in contextualizing memories of safety and inhibit fear responses when appropriate (Marstaller et al., 2017). Finally, the mPFC is thought to play a role in goal-directed motivation (Hamilton et al., 2015). All this evidence suggests that the DMN plays a significant role in the learning process by contextualizing information.
Keep in mind that the DMN can only accurately contextualize incoming stimuli if the full range of signals is adequately recognized. According to the calm pond idea, the noisy activation of a ruminating mind may hinder this ability. Here, greater clarification and definition on what a polluted mind means is needed. To define such mental patterns, functions of specific DMN regions will be explained. Commonly activated regions within the DMN that involve self-referential processes are (Farb et al., 2007; Knyazev, 2013):
- The orbitomedial prefrontal cortex (omPFC) – which contextualizes experienced stimuli as experienced by the self
- The ACC – which actively monitors the self-experienced stimuli
- The mPFC – which evaluates the self-experienced stimuli
- The PCC – which is involved in a generated a broader context of the personal experience given certain self-experienced stimuli.
By now, it may be evident that the DMN is involved with what is commonly referred to as the “ego”. Some researchers claim that the DMN develops the ego itself (R. L. Carhart-Harris & Friston, 2010). The term “ego” derives from Freudian psychoanalytic, and for this reason, the term “narrative-self” will be used instead. It is crucial to consider the word choice here. As previously explained, the DMN generates a time-oriented perception of the self to contextualize information. Furthermore, the four brain areas above all involved contextualizing an experience as experienced by the narrative self (rather than the self being the experience), monitoring these experiences across time, and evaluating these experiences as a broader implication of the experience of the self. The DMN is generating a narrative of the self through every experience. This is indeed where many unconstructive ruminations arise. Any reader can likely relate to ruminating over themselves and their circumstances and thinking about what this means in the larger context of their lives, worth, purpose, etc. This is the monkey mind. This is the DMN.
So, the real question becomes: what effect does the strong presence of a narrative-self have on our broader experience and health? Does a strong presence of the narrative-self influence the body’s interoceptive abilities and ability to properly analyze and predict incoming stimuli? This is a complex and challenging question, but evidence suggests that this is indeed the case. In a fantastic study by Farb and others in 2007, fMRIs were used to monitor brain activity in those who did and did not practice mindfulness meditation (Farb et al., 2007). In this study, a distinction was made between narrative focus and experiential focus. For eight weeks, those who underwent mindfulness meditation training were taught to practice experiential focus, which involves having present centered awareness of all thoughts, feelings, and experiences in a non-judgmental manner. Narrative focus was defined as judging experiences and trying to figure out what those stimuli meant. Brain scans were performed on both trained and untrained participants during both focus styles. For both groups, narrative focus increased activation of the mPFC and PCC as expected. During experiential focus, both groups reduced mPFC activity, but only the meditation trained group increased activation of the insula. This is incredible because the insula is highly involved in interoception and the sensations of internal physical states (Fox et al., 2014; Mehling et al., 2012). This study by Farb and others suggests a functional difference between the narrative-self and an experiential-self and shows how the quieting of the narrative-self increases interoceptive abilities and enhances the brains’ ability to analyze incoming stimuli properly. Not to mention, this study shows how this skill can be trained.
So far, we have seen how the DMN is involved in the generation of the narrative-self and how this influences our ability to analyze the signals coming from the body. The next reasonable question is to what extent can this be changed? And what are the implications of such change? As was previously shown in the mentioning of the study by Farb and others in 2007, mindfulness meditation appears to be capable of changing DMN activity. This is not the only study to suggest this. Another study showed that meditation decreased mPFC activity in DMN regions, such as the TPJ and PCC (Scheibner et al., 2017). It has also been shown that the neurotransmitter GABA reduces DMN activity, and both yoga and meditation have been implicated in the release of GABA (Guglietti et al., 2013; Hu et al., 2013; Streeter et al., 2018). The release of GABA release is also modulated by the vagus nerve, providing evidence of the possible mechanism at which meditation inhibits DMN activity (Hu et al., 2013; Keute et al., 2018; Streeter et al., 2018). Through these studies, it seems evident that meditation decreases DMN activity. In what ways is this significant? Firstly, it provides more explanation as to why meditation seems capable of alleviating depression. Similarly, it offers more evidence for how meditation increases interoceptive awareness (de Jong et al., 2016; Farb et al., 2010; Hanley et al., 2017). The increase in interoception suggests that the brain is more adequately processing not only the internal environment more adequately, but presumably the outside environment as well. Reality in general is being more accurately understood. It is possible that this also implicates a broader understanding of how meditation can alter consciousness and allowing monks, yogis, and the like to achieve nirvana/samadhi/enlightenment, or whatever you prefer to call such a state of altered consciousnesses. Perhaps this experience of altered consciousness is a more accurate interpretation of reality, produced by enhanced interoception and exteroception.
The subject of altered consciousness is perhaps best explored through brain changes induced by another technique commonly used in a spiritual manner: psychedelics. The famous studies from Johns Hopkins University using psilocybin found that this drug causes a spiritual experience often described as a sense of unity of all things that transcend space and time (Griffiths et al., 2006, 2008). Many participants rate this experience as one of the most significant spiritual experiences of their life (Griffiths et al., 2006). These experiences were often described with an experienced loss sense of self and an altered form of consciousness (Griffiths et al., 2008). It is not hard to imagine that this experience seems very similar to that of a trained monk or yogi, who learn to let go of their narrative-self and gain a sense of oneness with all things. This connection is further verified by the observation that psilocybin decreases the activity of the ACC, PCC, and mPFC (Robin L. Carhart-Harris et al., 2012). Ayahuasca, another psychedelic drug used in spiritual rituals by the indigenous peoples of the Amazon, also has been shown to have similar effects (Palhano-Fontes et al., 2015). Additionally, LSD has been shown to do the same (Speth et al., 2016). Suppose both psychedelic drugs and meditative practice decrease the same DMN, which generates the narrative-self. In that case, both methods likely lead one to the same place: an experience beyond time and space, where one is present with a profound sense of unity with everything.
This, to me, is a profound idea. It suggests that quieting the mind, or calming the “pond”, improves mental, physical, and spiritual health. It provides one with a perception full of compassion, peace, and love. It not only can make the individual healthier, but so too the community and planet. It is extraordinary evidence that improving the self is the greatest means of improving the world around us. Not to mention, it provides a simple means of liberating oneself from the struggle and hardship of life. Perhaps it is not life that is hard on us, but ourselves, by allowing the narrative-mind to take hold of our reality, rather than letting a purer form of consciousness dominate our perceptions. This is the pursuit, and meditation techniques are the practice.
Carhart-Harris, R. L., & Friston, K. J. (2010). The default-mode, ego-functions and free-energy: A neurobiological account of Freudian ideas. Brain, 133(4), 1265–1283. https://doi.org/10.1093/brain/awq010
Carhart-Harris, Robin L., Erritzoe, D., Williams, T., Stone, J. M., Reed, L. J., Colasanti, A., Tyacke, R. J., Leech, R., Malizia, A. L., Murphy, K., Hobden, P., Evans, J., Feilding, A., Wise, R. G., & Nutt, D. J. (2012). Neural correlates of the psychedelic state as determined by fMRI studies with psilocybin. Proceedings of the National Academy of Sciences of the United States of America, 109(6), 2138–2143. https://doi.org/10.1073/pnas.1119598109
de Jong, M., Lazar, S. W., Hug, K., Mehling, W. E., Hölzel, B. K., Sack, A. T., Peeters, F., Ashih, H., Mischoulon, D., & Gard, T. (2016). Effects of mindfulness-based cognitive therapy on body awareness in patients with chronic pain and comorbid depression. Frontiers in Psychology, 7(JUN). https://doi.org/10.3389/fpsyg.2016.00967
Ekhtiari, H., Nasseri, P., Yavari, F., Mokri, A., & Monterosso, J. (2016). Neuroscience of drug craving for addiction medicine: From circuits to therapies. In Progress in Brain Research (Vol. 223, pp. 115–141). Elsevier B.V. https://doi.org/10.1016/bs.pbr.2015.10.002
Farb, N. A. S., Anderson, A. K., Mayberg, H., Bean, J., McKeon, D., & Segal, Z. v. (2010). Minding One’s Emotions: Mindfulness Training Alters the Neural Expression of Sadness. Emotion, 10(1), 25–33. https://doi.org/10.1037/a0017151
Farb, N. A. S., Segal, Z. v., Mayberg, H., Bean, J., Mckeon, D., Fatima, Z., & Anderson, A. K. (2007). Attending to the present: Mindfulness meditation reveals distinct neural modes of self-reference. Social Cognitive and Affective Neuroscience, 2(4), 313–322. https://doi.org/10.1093/scan/nsm030
Fox, K. C. R., Nijeboer, S., Dixon, M. L., Floman, J. L., Ellamil, M., Rumak, S. P., Sedlmeier, P., & Christoff, K. (2014). Is meditation associated with altered brain structure? A systematic review and meta-analysis of morphometric neuroimaging in meditation practitioners. Neuroscience and Biobehavioral Reviews, 43, 48–73. https://doi.org/10.1016/j.neubiorev.2014.03.016
Griffiths, R. R., Richards, W. A., Johnson, M. W., McCann, U. D., & Jesse, R. (2008). Mystical-type experiences occasioned by psilocybin mediate the attribution of personal meaning and spiritual significance 14 months later. Journal of Psychopharmacology, 22(6), 621–632. https://doi.org/10.1177/0269881108094300
Griffiths, R. R., Richards, W. A., McCann, U., & Jesse, R. (2006). Psilocybin can occasion mystical-type experiences having substantial and sustained personal meaning and spiritual significance. Psychopharmacology, 187(3), 268–283. https://doi.org/10.1007/s00213-006-0457-5
Guglietti, C. L., Daskalakis, Z. J., Radhu, N., Fitzgerald, P. B., & Ritvo, P. (2013). Meditation-related increases in GABAB modulated cortical inhibition. Brain Stimulation, 6(3), 397–402. https://doi.org/10.1016/j.brs.2012.08.005
Hamilton, J. P., Farmer, M., Fogelman, P., & Gotlib, I. H. (2015). Depressive Rumination, the Default-Mode Network, and the Dark Matter of Clinical Neuroscience. In Biological Psychiatry (Vol. 78, Issue 4, pp. 224–230). Elsevier USA. https://doi.org/10.1016/j.biopsych.2015.02.020
Hamilton, J. P., Furman, D. J., Chang, C., Thomason, M. E., Dennis, E., & Gotlib, I. H. (2011). Default-mode and task-positive network activity in major depressive disorder: Implications for adaptive and maladaptive rumination. Biological Psychiatry, 70(4), 327–333. https://doi.org/10.1016/j.biopsych.2011.02.003
Hanley, A. W., Mehling, W. E., & Garland, E. L. (2017). Holding the body in mind: Interoceptive awareness, dispositional mindfulness and psychological well-being. Journal of Psychosomatic Research, 99, 13–20. https://doi.org/10.1016/j.jpsychores.2017.05.014
Heilbronner, S. R., & Platt, M. L. (2013). Causal evidence of performance monitoring by neurons in posterior cingulate cortex during learning. Neuron, 80(6), 1384–1391. https://doi.org/10.1016/j.neuron.2013.09.028
Hu, Y., Chen, X., Gu, H., & Yang, Y. (2013). Resting-state glutamate and GABA concentrations predict task-induced deactivation in the default mode network. Journal of Neuroscience, 33(47), 18566–18573. https://doi.org/10.1523/JNEUROSCI.1973-13.2013
Keute, M., Ruhnau, P., Heinze, H. J., & Zaehle, T. (2018). Behavioral and electrophysiological evidence for GABAergic modulation through transcutaneous vagus nerve stimulation. Clinical Neurophysiology, 129(9), 1789–1795. https://doi.org/10.1016/j.clinph.2018.05.026
Knyazev, G. G. (2013). EEG correlates of self-referential processing. Frontiers in Human Neuroscience, 7(MAY), 1–14. https://doi.org/10.3389/fnhum.2013.00264
Marstaller, L., Burianová, H., & Reutens, D. C. (2017). Adaptive contextualization: A new role for the default mode network in affective learning. Human Brain Mapping, 38(2), 1082–1091. https://doi.org/10.1002/hbm.23442
Mehling, W. E., Price, C., Daubenmier, J. J., Acree, M., Bartmess, E., & Stewart, A. (2012). The Multidimensional Assessment of Interoceptive Awareness (MAIA). PLoS ONE, 7(11). https://doi.org/10.1371/journal.pone.0048230
Palhano-Fontes, F., Andrade, K. C., Tofoli, L. F., Jose, A. C. S., Crippa, A. S., Hallak, J. E. C., Ribeiro, S., & de Araujo, D. B. (2015). The psychedelic state induced by Ayahuasca modulates the activity and connectivity of the Default Mode Network. PLoS ONE, 10(2), 1–13. https://doi.org/10.1371/journal.pone.0118143
Scheibner, H. J., Bogler, C., Gleich, T., Haynes, J. D., & Bermpohl, F. (2017). Internal and external attention and the default mode network. NeuroImage, 148(January), 381–389. https://doi.org/10.1016/j.neuroimage.2017.01.044
Seth, A. K. (2013). Interoceptive inference, emotion, and the embodied self. Trends in Cognitive Sciences, 17(11), 565–573. https://doi.org/10.1016/j.tics.2013.09.007
Speth, J., Speth, C., Kaelen, M., Schloerscheidt, A. M., Feilding, A., Nutt, D. J., & Carhart-Harris, R. L. (2016). Decreased mental time travel to the past correlates with default-mode network disintegration under lysergic acid diethylamide. Journal of Psychopharmacology, 30(4), 344–353. https://doi.org/10.1177/0269881116628430
Spreng, R. N., & Grady, C. L. (2010). Patterns of brain activity supporting autobiographical memory, prospection, and theory of mind, and their relationship to the default mode network. Journal of Cognitive Neuroscience, 22(6), 1112–1123. https://doi.org/10.1162/jocn.2009.21282
Streeter, C., Gerbarg, P. L., Nielsen, G. H., Brown, R. P., Jensen, J. E., Silveri, M., & Streeter, C. C. (2018). Effects of Yoga on Thalamic Gamma-Aminobutyric Acid, Mood and Depression: Analysis of Two Randomized Controlled Trials. Neuropsychiatry, 8(6), 1923–1939. https://doi.org/10.4172/Neuropsychiatry.1000535
van Buuren, M., Gladwin, T. E., Zandbelt, B. B., Kahn, R. S., & Vink, M. (2010). Reduced functional coupling in the default-mode network during self-referential processing. Human Brain Mapping, 31(8), 1117–1127. https://doi.org/10.1002/hbm.20920
Watkins, E. R. (2008). Constructive and unconstructive repetitive thought. Psychological Bulletin, 134(2), 163–206. https://doi.org/10.1037/0033-2909.134.2.163
Zhou, H. X., Chen, X., Shen, Y. Q., Li, L., Chen, N. X., Zhu, Z. C., Castellanos, F. X., & Yan, C. G. (2020). Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression. In NeuroImage (Vol. 206, p. 116287). Academic Press Inc. https://doi.org/10.1016/j.neuroimage.2019.116287