The Default Mode Network and Depression

The inner landscape of the mind can be a dark and gloomy place for people with depression and anxiety. It is often filled with negative self-talk and repetitions of bad memories. And worse, it can be a difficult place to escape; people with depression often feel trapped in their heads. In recent years, a brain network called the Default Mode Network (DMN) has been implicated as the neural substrate for depressive rumination. Not only does it help explain why people with depression get trapped, promising results are already emerging suggesting we can target the DMN to help people with anxiety and depression.

When thinking becomes rumination

Rumination is “a recurrent, self-reflective, and uncontrollable focus on depressed mood and its causes and consequences.” (Hamilton, et al., 2015)It goes beyond just worrying. We often ruminate over things we have no control over, such as painful past events. An example might be recalling a job interview that you bombed and rehashing it over and over, or simply thinking to yourself, “why do I always feel so sad?”

Healthy people have these kinds of thoughts too on occasion, but as with most psychiatric conditions, it’s the level of intensity or pervasiveness of symptoms that tip the scales towards mental illness. People with anxiety and depression tend to replay upsetting scenes over and over in their minds to the point of obsession. It’s a thinking pattern that quite literally has them spinning.

A meta-analysis published this year (Zhou et al., 2020) identifies the Default Mode Network (DMN) as the “principal neural substrate of rumination.” Depressed brains show differences in the wiring between the DMN and other brain structures. A closer look at the structure and function of the DMN may help explain why.

It The DMN’s involvement extends beyond depression; there’s mounting evidence correlating disruptions in the DMN with a long list of psychological and neurological conditions, from anxiety to Alzheimer’s disease to autism. Although scientists are still working out what these correlations may imply, they’re already beginning to shed light on this sometimes darker place in the mind. More knowledge about the DMN may inform better treatment options for those of us who are prone to rumination.

What is the Default Mode Network?

The Default Mode Network (DMN) is a collection of several regions in the brain that are functionally connected. It’s one of several large-scale brain networks that control various cognitive functions, such as directing attention or visual processing.

The DMN tends to be active when we are thinking about ourselves, but those aren’t its only functions. It is also associated with the mind-wandering or daydreaming, theory of mind, empathy and moral reasoning, thoughts on social concepts, memory storage and retrieval, story comprehension, and possibly even appreciation of aesthetic beauty.

The DMN is sometimes called the task-negative network because it is not active if we’re engaged in task-oriented or goal-directed behavior. When we’re engaged in an activity or paying attention to something, a different brain network activates, called the task-positive network. Interestingly, it was the lack of activity in the areas of the DMN during attentional tasks that lead to its discovery, not the mind wandering or daydreaming activities.

The Signal in the Noise

The DMN was discovered unexpectedly, by a group of researchers studying the brain’s activity while performing cognitive tasks. Brain activity can be studied by measuring the amount of blood flow to corresponding regions using fMRI, or functional Magnetic Resonance Imaging. If a researcher were trying to detect which areas of the brain become active due to an experimental variable such as cocaine use, for example, they would first need to measure the brain’s activity without the experimental variable (the cocaine), i.e., a control state.

For most fMRI experiments, a control scan is performed while the patient is “at rest.” In this case, “at rest” is defined as “[lying] quietly in an fMRI machine with eyes closed or eyes open fixed on a cross.” (Tryon, 2014) To calculate the net brain activity for the experimental variable, researchers subtract out the control or “resting” activity. They could do this because of the assumption that the resting state activity didn’t count—it was only noise.

The dark matter of the brain

Research suggesting the contrary started popping up as far as 1929, when Hans Berger invented the electroencephalogram, a device that measures brain activity by monitoring the electrical activity. Berger noted that some brain activity was observed even at rest, however his observations went largely unnoticed.

In the mid 90’s, positron emission tomography (PET) researchers began noting “negative signal changes” in the brain. PET is an imaging method used in medicine and research to visualize various physiological processes such as metabolism and blood flow. Scientists noted that while blood flow increased in certain areas of the brain when performing a task, it also decreased in other areas. Eventually these “task-induced deactivations” were well known to researchers; some research even noted that the deactivations occurred in the same areas. But still little attention was paid to this phenomenon.

When the DMN was officially identified in 2001, researchers (Raichle et al.) encountered a problem when studying brain activity during an active task. It required them to flip the previous fMRI scenario on its head. They subtracted experimental images of “active” brains from the control/”rest” images; instead of the usual pattern of brain activation, they were looking at deactivation. The result was a distinct pattern of deactivation of specific brain regions, and these regions were collectively defined as the DMN.

The default mode network and depression

Many studies have now suggested that the DMN is involved in depressive rumination. One study looked at the connection of the DMN to another brain structure, the subgenual prefrontal cortex (sgPFC). (Hamilton, et al., 2015) Elevated activity in the sgPFC is linked with social withdrawal and sadness or depression, and this area seems to be hyperconnected to the DMN. Here is a unfortunate application of the neuroscience aphorism “neurons that wire together fire together”: in this case, the neural correlates for “self” and “sadness” seem to be hardwired so that thinking of one elicits feeling of the other and vice versa.

Another study (Menon et al., 2010) looked at the way the DMN interacts with two other brain networks. When the DMN shuts down during task-oriented, externally focused behavior, another brain network called the central-executive network (CEN) comes online. A third network called the salience network (SN) is responsible for receiving incoming stimuli and modulating between the DMN (for internal contemplation) and the CEN (for external tasks). When compared to healthy brains, those of depressed patients showed stronger connections between the SN and DMN, as well as weaker connections between the SN and CEN. This finding could support the common tendency of depressed individuals to ruminate over a problem instead of actively trying to solve it.

What Helps?

Although there is much more we still need to learn about the DMN and how it impacts our health, research is already pointing towards possible treatment options. One study reviewed the effects of mental training on the function of the DMN and said that “Success in goal-oriented activities seems not to necessarily require the absence of mind wandering, but the individual’s ability to detect when the mind is not on task, in order to reorient attention back.” In other words, it’s okay to let your mind wander as long as you know it’s wandering. (Ramirez-Barrantes et al. 2019)Another word for this is metacognition, defined as the “awareness and understanding of one’s own thought process.” The authors of the study suggested that if metacognition gives someone the ability to purposefully choose where to direct their attention (either internally or externally, as appropriate), then perhaps training in metacognition could prove to be a useful intervention for depressive rumination.

Mindfulness Meditation

Studies observing experienced meditators have shown that meditation can reduce activity in the DMN, even beyond the reduction normally seen during an active task.

One particular study (Brewer et al., 2011) used three different types of mindfulness meditation and compared experienced meditators to non-meditator controls. They used fMRI scans to determine both the level of activity as well as the functional connectivity of the DMN of each group. They used three practices: concentration, loving-kindness and choiceless awareness, each of which are thought to cultivate various positive qualities of the mind. All of these practices were chosen for their tendency to “reverse the habit of mind-wandering” and potentially avoid default-mode processing.

The study found that the DMNs of experienced meditators were less active than controls. They also discovered that the ways in which the various nodes of the DMN were connected to each other looked distinctly different between groups.Specific patterns of connectivity in the DMN also correlated with self-reported levels of mind-wandering. Furthermore, in the experienced meditator group, activity in the DMN while in a resting state closely resembled that of the meditation state. This suggests that meditation may be able to transform our normal mind-wandering, self-absorbed, stuck-in-the-past state to what the authors call “a more present-centered default mode.”

Psychedelics

But meditation may not be the only way to improve metacognition and change the brain—another newly emerging intervention for rumination may alter the same areas of the brain and produce many of the same effects. Psychedelics like psilocybin and ayahuasca have shown to have a quieting effect on the DMN, in much the same way that experienced meditation does. Interestingly, both meditation and psychedelics have been associated with the “dissolution of the ego,” or a loss of the sense of self. This is reported in a dose-dependent manner in the case of psychedelics, and it correlates with less connectivity in the DMN (Carhart-Harris et al., 2017).

There are still many questions to answer about the neural correlates of depression in the brain. Why is relapse so common? Why do antidepressants only work for some people? The results of research on treatment targeting the Default Mode Network are just the beginning, but they have shown us what is possible. Even though depression and anxiety seem to hardwire the brain to be negative, these studies have proven that the brain can be changed and rewired. With hope, those who ruminate can learn to escape the darkness and bad memories and cultivate a brighter, more intentional default mode.

Written by Stacey Neglia. Illustrated by Melis Cakar.
Edited by Sean Noah, Desislava Nesheva and Elizabeth Burnette.

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References

Hamilton, J.P., Farmer, M., Fogelman, P., Gotlib, I.H. (2015). Depressive Rumination, the Default-Mode Network, and the Dark Matter of Clinical Neuroscience. Biological Psychiatry, 78(4). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4524294/

Zhou, H. et al. (2020) Rumination and the default mode network: Meta-analysis of brain imaging studies and implications for depression. NeuroImage. 206. https://www.sciencedirect.com/science/article/pii/S105381191930878X

Li, B.J., et al. A brain network model for depression: From symptom understanding to disease intervention. (2018). CNS Neuroscience and Therapeutics, 24(11). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6490158/

Ramirez-Barrantes, R., et al. (2019). Default Mode Network, Meditation, and Age-Associated Brain Changes: What Can We Learn from the Impact of Mental Training on Well-Being as a Psychotherapeutic Approach? Neural Plasticity. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6466873/

Raichle, M.E., Snyder, A.Z. (2007). A default mode of brain function: A brief history of an evolving idea. NeuroImage, (37).

Sansone, R.A., Sansone, L.A. (2012). Rumination. Innovations in Clinical Neuroscience, 9(2). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3312901/

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Dai, L., et al. (2019). Brain structural and functional changes in patients with major depressive disorder: a literature review. PeerJ. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6886485/

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Carhart-Harris et al., (2017). Psilocybin for treatment-resistant depression: fMRI-measured brain mechanisms. Scientific Reports. 7, 13187. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5640601