Salience Network

Salience Network

The salience network is a brain network centred on the anterior insula and the dorsal anterior cingulate that triages incoming stimuli and decides which deserve attention. It was named by William Seeley and colleagues in 2007 and has been reproduced across many resting-state datasets, so the network itself is well established. The behavioural claim it is most often invoked to explain, that a phone's mere presence measurably reduces cognitive capacity, does not survive meta-analysis. The plausible mechanism exists and the effect it was recruited to explain mostly does not, which is a pattern worth remembering.

What it is

Seeley and colleagues described dissociable intrinsic connectivity networks for salience processing and executive control in the Journal of Neuroscience in 2007. Seeley is first author, and Vinod Menon and Michael Greicius are among the co-authors.

Menon's later review describes the network as an orchestrator, integrating cognitive, homeostatic, motivational and affective inputs in order to switch between other large-scale networks. That switching role is what makes it interesting for anyone writing about attention: it is the part of the system whose job is deciding what gets the rest of the system's time.

One thing that must not be merged with it is aberrant salience, the dopaminergic account of why a stimulus comes to feel significant, which is Shitij Kapur's construct. One is a signalling account of why a thing feels important; the other is a named network in the connectivity literature. Popular writing uses the word for both.

In effect

The network is most often invoked to explain why a phone is hard to ignore even when it is face-down and silent: a device designed to score highly on novelty and social relevance is competing for a system whose job is exactly to notice those things. That is a plausible story and it needs an effect to explain.

The effect it was recruited for does not hold. Hartanto and colleagues published a four-level meta-analysis in 2024 covering 166 effect sizes across 53 samples and 33 studies, with more than four thousand participants, and found no significant overall effect of a smartphone's mere presence on cognitive function. The original brain-drain study by Adrian Ward and colleagues, published in 2017, is the source of the popular claim. A working-memory exception is sometimes quoted alongside the meta-analysis and was not confirmed in this publication's verification pass, so it is not printed here.

The reading to take away is a general one about mechanism and effect. A network exists whose function makes a story plausible, the story was told widely, and the behavioural finding underneath it did not replicate. The mechanism did not make the effect true.

What it does not say

It does not say that phones capture attention through this network. The network's existence is not evidence for any particular behavioural claim about any particular device.

It does not support the brain-drain claim. Current meta-analysis returns essentially nothing for the mere presence of a phone.

It is not the same construct as aberrant salience. That belongs to the dopamine literature and to a different originator, and merging the two in a graph or an argument is an error.

It does not license imaging shortcuts. Functional magnetic resonance imaging measures blood oxygenation and cannot image dopamine or its receptors.

Sources

  1. Seeley, W. W., Menon, V., Schatzberg, A. F., Keller, J., Glover, G. H., Kenna, H., Reiss, A. L., & Greicius, M. D. (2007). "Dissociable intrinsic connectivity networks for salience processing and executive control." Journal of Neuroscience, 27(9), 2349-2356. Seeley is first author.
  2. Menon, V. (2015). "Salience Network", in Brain Mapping: An Encyclopedic Reference, vol. 2, 597-611. A review.
  3. Hartanto, A., et al. (2024). "The effect of mere presence of smartphone on cognitive functions: a four-level meta-analysis." Technology, Mind, and Behavior. 166 effect sizes, 53 samples, 33 studies, N = 4,368, d = -0.02, 95% CI -0.06 to 0.01. The working-memory exception was not confirmed in this pass.
  4. Ward, A. F., et al. (2017). Journal of the Association for Consumer Research, 2(2), 140-154. The original brain-drain study.
  5. Evidence review, 2026-09-25. Verdict: robust, for the network.