Back

Individual risk attitudes arise from noise in neurocognitive magnitude representations

Barretto Garcia, M.; de Hollander, G.; Grueschow, M.; Polania, R.; Woodford, M.; Ruff, C.

2022-08-22 neuroscience
10.1101/2022.08.22.504413 bioRxiv
Show abstract

Humans are generally risk averse: they prefer options with smaller certain outcomes over those with larger uncertain ones. This risk aversion is classically explained with a concave utility function, meaning that successive increases in monetary payoffs should increase subjective valuations by progressively smaller amounts. Here, we provide neural and behavioural evidence that risk aversion may also arise from a purely perceptual bias: The noisy logarithmic coding of numerical magnitudes can lead individuals to underestimate the size of larger monetary payoffs, leading to apparent risk aversion even when subjective valuation increases linearly with the estimated amount. A formal model of this process predicts that risk aversion should systematically increase when individuals represent numerical magnitudes more noisily. We confirmed this prediction by measuring both the mental and neural acuity of magnitude representations during a purely perceptual task and relating these measures to individual risk attitudes during separate financial decisions. Computational model fitting suggested that subjects based both types of choices on similar mental magnitude representations, with correlated precision across the separate perceptual and risky choices. Increased stimulus noise due to the presentation format of risky outcomes led to increased risk aversion, just as predicted by the model. The precision of the underlying neural magnitude representations was estimated with a numerical population receptive field model fitted to the fMRI data of the perceptual task. Subjects with more precise magnitude representations in parietal cortex indeed showed less variable behaviour and less risk-aversion in the separate financial choices. Our results highlight that individual patterns of economic behaviour may, at least partially, be determined by capacity limitations in perceptual processing rather than by processes that assign subjective values to monetary rewards.

Matching journals

The top 2 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.