A dual-subsystem model of the brain's default network: self-referential processing, memory retrieval processes, and autobiographical memory retrieval.

Most internally oriented mental activities are known to strongly activate the default network, which includes remembering the past, future thinking and social cognition, and are heavily self-referential, and demanding of memory retrieval processes. Based on these observations and building on related findings from the literature, the present article proposed a simple, dual-subsystem model of the default network. The ability of the model to estimate brain activity during autobiographical memory (AM) retrieval and related reference conditions was then tested by performing a quantitative meta-analysis of relevant literature. The model divided the default network into two subsystems. The first, called the 'cortical midline subsystem (CMS)', was comprised of the anteromedial prefrontal cortex and posterior cingulate cortex, and primarily mediates self-referential processing. The other, termed the 'parieto-temporal subsystem (PTS)', included the inferior parietal lobule, medial temporal lobe and lateral temporal cortex, and mainly supports memory retrieval processes. The meta-analysis of AM retrieval contrasts yielded a double dissociation that was consistent with this model. First, CMS regions associated more with an AM>laboratory-based memory (LM) contrast than with an AM>rest contrast, confirming that these regions play more critical roles in self-referential processing than memory retrieval processes. Second, all three PTS regions showed a greater association with an AM>rest contrast than with an AM>LM contrast, confirming that their role in memory retrieval processes is greater than in self-referential processing. Although the present model is limited in scope, both in terms of anatomical and functional specifications, it integrates diverse processes such as self-referential processing, episodic and semantic memory and subsystem interface, and provides useful heuristics that can guide further research on fractionation of the default network.