The science underneath
Precision: how much weight each signal gets
In shortThe brain decides how much weight each signal gets, and much of what we call attention is this.
The idea
Not all information counts the same. The brain estimates how reliable each signal is and gives it more or less weight. A noise in a quiet room weighs a lot; the same noise at a party barely counts. Much of what we call attention is this: deciding which differences deserve to change what we think or do. People differ in this weighting, but from situation to situation, not in a fixed way.
What to try
- Say what matters now and what can be ignored, especially when the rules change.
- When a child reacts to a detail, ask why that signal seems reliable or important to them.
- Withdraw these supports as they learn to decide what counts.
The common mistake
Talking about ‘a child’s precision’ as a single trait. It varies with the problem, the processing level and the context.
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Short, plain pieces by the researchers and good writers.
The science behind itHow strong the evidence is, the model, videos and references.
How strong the evidence is
Promising Good studies, but little tested with children at home or school, or the step to daily life is our interpretation.
Precision modulates the gain of prediction errors (and, in neural models, postsynaptic excitability via neuromodulation). Distinguishing sensory precision, prior precision and precision over policies gives different hypotheses for the same behaviour. Under task uncertainty, relevant and irrelevant representations can become entangled (Xue, Markman, Chen et al., 2026), adding a question of differentiation to detection and weighting: do the dimensions stay separable as uncertainty rises? Assess by explicitly manipulating certainty about the relevant rule.
More technical books
The fullest account of predictive processing, with body and action at the centre.
See on Amazon ›The technical textbook on active inference, for those who want the formal model.
See on Amazon ›Amazon links are affiliate links: if you buy, Bounded Uncertainty receives a small commission at no cost to you.
External videos, chosen because they agree with these ideas. Bounded Uncertainty has no link to the channels.
References
- Feldman, H., & Friston, K. J. (2010). Attention, uncertainty, and free-energy. Frontiers in Human Neuroscience, 4, 215.
- Lawson, R. P., Rees, G., & Friston, K. J. (2014). An aberrant precision account of autism. Frontiers in Human Neuroscience, 8, 302.
- Van de Cruys, S., Evers, K., Van der Hallen, R., et al. (2014). Precise minds in uncertain worlds: predictive coding in autism. Psychological Review, 121(4), 649–675.
- Xue, Markman, Chen et al. (2026). Feature interference underlies a neuronal basis for the behavioural cost of task uncertainty. Nature Neuroscience.
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