Pain and the Triple Network Model

Frontiers in neurology

Front Neurol. 2022 Mar 7;13:757241. doi: 10.3389/fneur.2022.757241. eCollection 2022.


Acute pain is a physiological response that causes an unpleasant sensory and emotional experience in the presence of actual or potential tissue injury. Anatomically and symptomatically, chronic pathological pain can be divided into three distinct but interconnected pathways, a lateral "painfulness" pathway, a medial "suffering" pathway and a descending pain inhibitory circuit. Pain (fullness) can exist without suffering and suffering can exist without pain (fullness). The triple network model is offering a generic unifying framework that may be used to understand a variety of neuropsychiatric illnesses. It claims that brain disorders are caused by aberrant interactions within and between three cardinal brain networks: the self-representational default mode network, the behavioral relevance encoding salience network and the goal oriented central executive network. A painful stimulus usually leads to a negative cognitive, emotional, and autonomic response, phenomenologically expressed as pain related suffering, processed by the medial pathway. This anatomically overlaps with the salience network, which encodes behavioral relevance of the painful stimuli and the central sympathetic control network. When pain lasts longer than the healing time and becomes chronic, the pain- associated somatosensory cortex activity may become functionally connected to the self-representational default mode network, i.e., it becomes an intrinsic part of the self-percept. This is most likely an evolutionary adaptation to save energy, by separating pain from sympathetic energy-consuming action. By interacting with the frontoparietal central executive network, this can eventually lead to functional impairment. In conclusion, the three well-known pain pathways can be combined into the triple network model explaining the whole range of pain related co-morbidities. This paves the path for the creation of new customized and personalized treatment methods.

PMID:35321511 | PMC:PMC8934778 | DOI:10.3389/fneur.2022.757241


Dirk De Ridder
Sven Vanneste
Mark Smith
Divya Adhia