Role of Default Mode Network in Depression

March 28, 2012


“What is the role of the default mode network in depression?”

Vladimir Maletic, MD, MS:

Over the last decade we have seen an important evolution in our understanding of the pathophysiology of depression. A relatively static model focused on identifying an abnormal activity pattern in the individual brain areas has been replaced with a dynamic model evaluating the relationship between major brain networks either in the resting state or in a response to a given challenge. Three networks appear to have an important role in mood disorders: salience network, default mode network, and executive network.

Executive network (EN) is anchored in dorsolateral prefrontal cortex (DLPFC) and the lateral parietal cortex. These areas share a pattern of coactivation across a wide range of cognitive tasks. The role of EN encompasses maintaining and manipulating information in the working memory. 1-2  An effective EN function also includes proper allocation of the attentional resources in order to best support our adaptive, goal-directed behaviors. In other words, this is the cortical problem solver. Salience network (SN) includes connections between limbic areas such as amygdala, ventral striatum/nucleus accumbens, hypothalamus, and related subcortical areas including dorsomedial thalamus, periaqueductal gray, and substantia nigra/ventral tegmental area. Additionally, SN has rich connections with paralimbic areas such as frontoinsular cortex, anterior insula (AI), dorsal anterior cingulate cortex (dACC), and superior temporal lobe. 1-3  Dorsomedial thalamus appears to be the key link between paralimbic cortical areas and subcortical structures. One can view the SN as the main motivator or driver of adaptive behaviors.

The default mode network (DMN) is most active when the brain is at rest or involved in social communication. Its activity is attenuated during the performance of cognitively demanding tasks. 1-2  In addition to posterior cingulate cortex (PCC), DMN incorporates other midline cortical structures such as ventromedial PFC (vmPFC) and dorsomedial PFC (dmPFC). Extended DMN includes inferior parietal lobule, lateral temporal cortex, medial temporal lobe (including hippocampal formation), and angular gyrus. 1, 4-5  Reminiscing about a childhood vacation or “replaying a tape” of a recent confrontation with our coworker is likely to elicit an increased PCC activity. Attempting to explain to our friend why we liked the book that we just read is likely to involve the medial PFC activity. In short, DMN goes offline when we are involved in task-oriented behaviors or problem solving, but shows greater engagement during self-referential processes, value-based decision making, social cognition, emotional regulation, and episodic, semantic, and autobiographical memory retrieval. 1-2

Ever since PCC was identified as a prominent node in the DMN, its role in major depressive disorder (MDD) has become a focus of intense research. If activity in DMN is associated with self reflection and a “wandering mind,” should we expect altered function in depression? Recent research has confirmed our doubts. Under usual circumstances subgenual ACC (sgACC) is tasked with funneling the emotional information from the limbic areas to the prefrontal cortical areas, mobilizing them to mount an adaptive response. When the SN (sgACC/AI) signals reach the PFC, pointing to a situation that needs to be addressed right away, DMN should go “offline”; in its stead, we should expect the activation of problem-solving EN.

Unfortunately, a different sequence plays out in depression. Emotional information from sgACC—presumably, conveying feelings of sadness, dejection, and anxiety—short circuits, with the DMN becoming a subject for rumination. Sheline et al have noted a sgACC intrusion: hyper-connectedness between sgACC and the most prominent components of DMN, dmPFC, and PCC in individuals with MDD. 6  Moreover, a quantified resting state connectivity between sgACC and the hubs of the DMN network significantly correlated with the duration of an MDD episode, hinting that it may be considered as a measure of “refractoriness” of depression.

Another group made a very intricate observation by combining the Ruminative Responses Scale (RRS)—a self-report measure of rumination—and Beck Depression Inventory-II (BDI-II) with functional magnetic resonance imaging findings. Hamilton et al reported that individuals with MDD had a greater activation of PCC and dmPFC (DMN components), which coincided with high levels of maladaptive rumination, such as recall of miserable autobiographical memories, mind-wandering, and lower levels of adaptive self-reflection compared to healthy control participants. 7  Further extending these findings, another group noted an increased connectivity between sgACC and PCC in a resting state, but not during task engagement, which was significantly correlated with brooding and ruminations in patients with MDD as assessed by RRS. 8-9  Studies have also reported an association between depressive ruminations and increased PCC connectivity in participants suffering from their first depressive episode compared to healthy controls, 10  and correlation between elevated PCC and vmPFC activity and the measures of the severity of depression and feelings of hopelessness. 11  Extending these findings regarding rumination in MDD, aberrant PCC activity was even observed in individuals who are unhappy in love relative to the ones who have happy romantic attachments. 12

In conclusion, it appears that there is an aberrant connectivity between DMN and SN networks in depression, accompanied by a relative lack of EN involvement. This altered network dynamic may keep our patients with depression stuck in a ruminative loop of misery without ability to adequately engage the problem-solving EN.

—Vladimir Maletic, MD, MS



1.    Menon V . Large-scale brain networks and psychopathology: a unifying triple network model.  Trends Cogn Sci.  2011;15(10):483-506.
2.    Bressler SL, Menon V . Large-scale brain networks in cognition: emerging methods and principles.  Trends Cogn Sci.  2010;14(6):277-290.
3.    Seeley WW, Menon V, Schatzberg AF, et al . Dissociable intrinsic connectivity networks for salience processing and executive control.  J Neurosci.  2007;27(9):2349-2356.
4.    Wiebking C, de Greck M, Duncan NW, Heinzel A, Tempelmann C, Northoff G . Are emotions associated with activity during rest or interoception? An exploratory fMRI study in healthy subjects.  Neurosci Lett.  2011;491(1):87-92.
5.    Buckner RL, Andrews-Hanna JR, Schacter DL . The brain's default network: anatomy, function, and relevance to disease.  Ann N Y Acad Sci.  2008;1124:1-38.
6.    Sheline YI, Price JL, Yan Z, Mintun MA . Resting-state functional MRI in depression unmasks increased connectivity between networks via the dorsal nexus.  Proc Natl Acad Sci U S A.  2010;107(24):11020-11025.
7.    Hamilton JP, Furman DJ, Chang C, Thomason ME, Dennis E, Gotlib IH . Default-mode and task-positive network activity in major depressive disorder: implications for adaptive and maladaptive rumination.  Biol Psychiatry.  2011;70(4):327-333.
8.    Berman MG, Peltier S, Nee DE, Kross E, Deldin PJ, Jonides J . Depression, rumination and the default network.  Soc Cogn Affect Neurosci.  2011;6(5):548-555.
9.    Berman MG, Nee DE, Casement M, et al . Neural and behavioral effects of interference resolution in depression and rumination.  Cogn Affect Behav Neurosci. 2011;11(1):85-96.
10.    Zhu X, Wang X, Xiao J, et al . Evidence of a Dissociation Pattern in Resting-State Default Mode Network Connectivity in First-Episode, Treatment-Naive Major Depression Patients.  Biol Psychiatry.  Dec 15 2011.
11.    Grimm S, Boesiger P, Beck J, et al . Altered negative BOLD responses in the default-mode network during emotion processing in depressed subjects. Neuropsychopharmacology.  2009;34(4):932-843.
12.    Stoessel C, Stiller J, Bleich S, et al . Differences and similarities on neuronal activities of people being happily and unhappily in love: a functional magnetic resonance imaging study.  Neuropsychobiology.  2011;64(1):52-60.