Brain stuff

Brain networks

Brain networks are connected regions of the brain that become active and interact dynamically over the course of particular cognitive functions. There are a number of brain networks that might be relevant to the practice of reflection.

Default mode network (DMN)

The DMN is most active when we are awake but either resting or engaged in undemanding tasks.

It is linked to spontaneous cognition (daydreaming and mind-wandering), introspection (thinking about self), social understanding (thinking about others) and temporal reasoning (thinking about cause and effect). (See Incubation.)

Spreng, R. N., Mar, R. A., & Kim, A. S. N. (2009). The common neural basis of autobiographical memory, prospection, navigation, theory of mind, and the default mode: A quantitative meta-analysis. Journal of Cognitive Neuroscience, 21(3), 489–510. https://doi.org/10.1162/jocn.2008.21029

Central executive network (CEN)

The CEN is active when we are engaged in demanding, externally-focused, goal-oriented tasks which involve rules-based reasoning.

Dorsal attention network (DAN)

The DAN is involved in focusing and maintaining our attention (particularly visual attention). 

Salience network (SN)

The SN is thought to be involved in integrating sensory and emotional information in order to prioritise the balance between introspective (DMN) and extrospective (CEN) processing and redirecting our attention (DAN) in response to new significant stimuli.

Iraji, A., Deramus, T. P., Lewis, N., Yaesoubi, M., Stephen, J. M., Erhardt, E., Belger, A., Ford, J. M., McEwen, S., Mathalon, D. H., Mueller, B. A., Pearlson, G. D., Potkin, S. G., Preda, A., Turner, J. A., Vaidya, J. G., van Erp, T. G. M., & Calhoun, V. D. (2019). The spatial chronnectome reveals a dynamic interplay between functional segregation and integration. Human Brain Mapping, 40(10), 3058–3077. https://doi.org/10.1002/hbm.24580

Predictive coding

Predictive coding is a neuroscience theory which proposes that one of the primary functions of the cortical regions of the brain is to minimize "prediction error" — the discrepancy between the predicted input (from our mental model of the world — meaning schemas) and the actual input from our senses.

Millidge, B., Seth, A., & Buckley, C. L. (2022). Predictive coding: A theoretical and experimental review (arXiv:2107.12979). arXiv. https://doi.org/10.48550/arXiv.2107.12979

Aitchison, L., & Lengyel, M. (2017). With or without you: Predictive coding and Bayesian inference in the brain. Current Opinion in Neurobiology, 46, 219–227. https://doi.org/10.1016/j.conb.2017.08.010

Rauss, K., & Pourtois, G. (2013). What is bottom-up and what is top-down in predictive coding? Frontiers in Psychology, 4. https://doi.org/10.3389/fpsyg.2013.00276

See also Conscious and non-conscious mechanisms