Default Mode Network Activity in Psychopathology

The default mode network (DMN) refers to an interconnected group of brain structures that are hypothesized to be part of a functional system. The default network is a relatively recent concept, and because of this, there is not yet a complete consensus on which brain regions should be included in the definition. Regardless, some structures that are generally included are the medial prefrontal cortex, posterior cingulate cortex and, the inferior parietal lobule. A few of the other structures that are being considered are the lateral temporal cortex, hippocampal formation, and the precuneus . These brain regions are considered to be the brain’s default mode network .

When the brain is not engaged in a specific attention-demanding or stimulus dependent task, it switches gears into a default mode of stimulus-independent thought that is detached from the external environment and is characterized by mental explorations based on personal introspection, autobiographical memories, and thoughts of the future . The DMN offers a new window into the neural basis of spontaneous human thoughts and feelings, and correspondingly, how this differs in neuropsychiatric diseases . Neuropsychiatric disorders are associated with abnormal function of the DMN, a distributed network of brain regions more active during rest than during performance of many attention demanding tasks and characterized by a high degree of functional connectivity . Functional magnetic resonance imaging studies have revealed that the DMN in the healthy brain is associated with stimulus-independent thought and self-reflection and that greater suppression of the DMN is associated with better performance on attention-demanding tasks . In schizophrenia and depression, the DMN is often found to be hyperactivated and hyperconnected. In schizophrenia this may relate to overly intensive self-reference and impairments in attention and working memory . In depression, DMN hyperactivity may be related to negative rumination .  Role of Psychedelics in Psychology

## Computational Model

Understanding the structure of the Default Mode Network has been facilitated by computational models and topographical organization of the cortex. The role of the DMN in cognition might arise from its position at one extreme of a hierarchy, allowing it to process transmodal information that is unrelated to immediate sensory input . Computational modeling of behavior has revolutionized psychology and neuroscience. By fitting models to experimental data, we can probe the algorithms underlying behavior, find neural correlates of computational variables and better understand the effects of drugs, illness and interventions . A principal advantage of computational modeling is that we are forced to specify all parts of a theory. Interoception is the process by which the nervous system senses the internal state of the body. It provides the brain with important information to adaptively guide the regulation of both internal body states and behavior . Interoceptive dysfunction is thought to play a role in multiple psychiatric disorders. Theoretical models propose that the computational mechanisms of interoceptive dysfunction are caused by overly precise prior beliefs about body states or underestimates the reliability of the information carried by ascending signals from the body .

1. ↑ Buckner RL, Andrews-Hanna JR, Schacter DL. The brain's default network: anatomy, function, and relevance to disease. Ann N Y Acad Sci. 2008 Mar;1124:1-38. doi: 10.1196/annals.1440.011. PMID: 18400922.
2. ↑ 2.0 2.1 2.2 Buckner RL, Andrews-Hanna JR, Schacter DL. 2008. The brain’s default network: anatomy, function, and relevance to disease. Ann. N. Y. Acad. Sci. 1124:1–38
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4. ↑ 4.0 4.1 Calhoun VD, Maciejewski PK, Pearlson GD, Kiehl KA. 2008. Temporal lobe and “default” hemodynamic brain modes discriminate between schizophrenia and bipolar disorder. Hum. Brain Mapp. 29:1265–75
5. ↑ Daniel S. Margulies, Satrajit S. Ghosh, Alexandros Goulas, Marcel Falkiewicz, Julia M. Huntenburg, Georg Langs, Gleb Bezgin, Simon B. Eickhoff, F. Xavier Castellanos, Michael Petrides, Elizabeth Jefferies, Jonathan Smallwood
6. ↑ Proceedings of the National Academy of Sciences Nov 2016, 113 (44) 12574-12579; DOI: 10.1073/pnas.1608282113
7. ↑ Wilson, R. C., & Collins, A. G. (2019). Ten simple rules for the computational modeling of behavioral data. *Elife*, *8*, e49547.
8. ↑ Smith R, Kuplicki R, Feinstein J, Forthman KL, Stewart JL, Paulus MP, et al. (2020) A Bayesian computational model reveals a failure to adapt interoceptive precision estimates across depression, anxiety, eating, and substance use disorders. PLoS Comput Biol 16(12): e1008484. https://doi.org/10.1371/journal.pcbi.1008484