Rebecca P. Lawson
Cambridge cognitive neuroscientist working in the predictive-processing tradition, best known for computational accounts of how the brain estimates environmental volatility and how that estimation goes wrong — most influentially in autism, where her hierarchical-Bayesian modelling put aberrant precision-weighting of prediction errors on the map as a candidate core mechanism.
In the wiki
She is the middle author on Nord, Lawson & Dalgleish (2021), and the predictive-coding reading of that paper — the mid-insula as a site of interoceptive prediction-error encoding, with pathology framed as mis-weighted errors or over-precise priors — is squarely in her theoretical idiom. Her exteroceptive volatility work is the autism-precision story that runs parallel to the interoceptive one on computational-psychiatry and feedforward-vs-predictive-interoception; the wiki also meets the same aberrant-precision phenotype from the visual side in Parr et al. (2019). Thin page: one paper in raw/.