Biology subjects

Aston, S.

Publications and source records attributed to Aston, S..

3 recordsLinked to original sources

bioRxiv2025

Learning new perceptual skills: Individual differences in the computations that integrate novel sensory cues into depth perception

Sensory substitution and augmentation rely on the brains ability to integrate novel sensory cues into its perceptual repertoire. However, the flexibility of the computations that support augmented perception is still not fully known. Here, we contrasted how a novel depth cue is processed, as compared with familiar depth cues, following one hour of training. Observers (N=78) made forced-choice comparisons of surface distances (depths), while we assessed three markers of integration with familiar and newly learned cues: (1) cue combination, predicting precision benefits; (2) re-weighting, predicting reliability-weighted biases; and (3) congruence sensitivity, predicting increased sensitivity for the learned cue mapping. We found that, (1) while familiar cues (size and binocular disparity) were combined near-optimally, there was little evidence for a novel cue (auditory pitch) being combined with binocular disparity. Measures of repeatability across two sessions suggest that this was due to reliable inter-individual differences in combination with the novel cue. In contrast, (2) both familiar and novel cue pairs were re-weighted by their relative reliabilities and (3) showed sensitivity to incongruence. These direct comparisons show that, while a novel cue was rapidly mapped onto depth and weighted in line with its relative reliability, it was not integrated into the native perceptual repertoire by everyone. Reliable individual differences suggest that abilities to combine novel sensory cues may vary between people. These findings provide insight into the flexibility of human sensory processing and suggest that learning to interpret new sensory information depends in part on individual flexibility in perceptual computations. Highlights- We evaluated evidence for integration of novel and familiar cues to depth - After short training, direct comparisons show dissociations in integration - At a group level, novel cues, unlike familiar, were not combined overall - Strong individual differences suggest varied abilities to combine new cues - Individual differences seem to play an important role in integration of new cues

neuroscience↗

bioRxiv2021

Central tendency biases must be accounted for to consistently capture Bayesian cue combination in continuous response data

Observers in perceptual tasks are often reported to combine multiple sensory cues in a weighted average that improves precision - in some studies, approaching statistically-optimal (Bayesian) weighting, but in others departing from optimality, or not benefitting from combined cues at all. To correctly conclude which combination rules observers use, it is crucial to have accurate measures of their sensory precision and cue weighting. Here, we present a new approach for accurately recovering these parameters in perceptual tasks with continuous responses. Continuous responses have many advantages, but are susceptible to a central tendency bias, where responses are biased towards the central stimulus value. We show such biases lead to inaccuracies in estimating both precision gains and cue weightings, two key measures used to assess sensory cue combination. We introduce a method that estimates sensory precision by regressing continuous responses on targets and dividing the variance of the residuals by the squared slope of the regression line, "correcting-out" the error introduced by the central bias and increasing statistical power. We also suggest a complementary analysis that recovers the sensory cue weights. Using both simulations and empirical data, we show that the proposed methods can accurately estimate sensory precision and cue weightings in the presence of central tendency biases. We conclude that central tendency biases should be (and can easily be) accounted for to consistently capture Bayesian cue combination in continuous response data.

neuroscience↗

bioRxiv2019

Bayesian transfer in a complex spatial localisation task

Prior knowledge can help observers in various situations. Adults can simultaneously learn two location priors and integrate these with sensory information to locate hidden objects. Importantly, observers weight prior and sensory (likelihood) information differently depending on their respective reliabilities, in line with principles of Bayesian inference. Yet, there is limited evidence that observers actually perform Bayesian inference, rather than a heuristic, such as forming a look-up table. To distinguish these possibilities, we ask whether previously-learnt priors will be immediately integrated with a new, untrained likelihood. If observers use Bayesian principles, they should immediately put less weight on the new, less reliable, likelihood ("Bayesian transfer"). In an initial experiment, observers estimated the position of a hidden target, drawn from one of two distinct distributions, using sensory and prior information. The sensory cue consisted of dots drawn from a Gaussian distribution centred on the true location with either low, medium, or high variance; the latter introduced after block three of five to test for evidence of Bayesian transfer. Observers did not weight the cue (relative to the prior) significantly less in the high compared to medium variance condition, counter to Bayesian predictions. However, when explicitly informed of the different prior variabilities, observers placed less weight on the new high variance likelihood ("Bayesian transfer"), yet substantially diverged from ideal. Much of this divergence can be captured by a model that weights sensory information, according only to internal noise in using the cue. These results emphasise the limits of Bayesian models in complex tasks.

neuroscience↗