Robustness of individual differences in temporal interference effects

Near-optimal integration of the magnitude information of time and numerosity

Magnitude information is often correlated in the external world, providing complementary information about the environment. As if to reflect this relationship, the perceptions of different magnitudes (e.g. time and numerosity) are known to influence one another. Recent studies suggest that such magnitude interaction is similar to cue integration, such as multisensory integration. Here, we tested whether human observers could integrate the magnitudes of two quantities with distinct physical units (i.e. time and numerosity) as abstract magnitude information. The participants compared the magnitudes of two visual stimuli based on time, numerosity, or both. Consistent with the predictions of the maximum-likelihood estimation model, the participants integrated time and numerosity in a near-optimal manner; the weight of each dimension was proportional to their relative reliability, and the integrated estimate was more reliable than either the time or numerosity estimate. Furthermore, the integration approached a statistical optimum as the temporal discrepancy of the acquisition of each piece of information became smaller. These results suggest that magnitude interaction arises through a similar computational mechanism to cue integration. They are also consistent with the idea that different magnitudes are processed by a generalized magnitude system.

Cross-dimensional magnitude interaction is modulated by representational noise: evidence from space-time interaction

Magnitudes along different dimensions (e.g., space and time) tend to interact with each other in perception, with some magnitude dimensions more susceptible to cross-dimensional interference than others. What causes such asymmetries in cross-dimensional magnitude interaction is being debated. The current study investigated whether the representational noise of magnitudes modulates the (a)symmetry in space-time interaction. In three experiments using different formats of length, we showed that dynamic unfilled lengths resulted in a higher representational noise than either static unfilled length or static filled length. Correspondingly, we observed that the time-on-space effect was larger for dynamic unfilled lengths than for static unfilled length or static filled length (and it did not differ between the latter two). Further correlational analyses showed that the susceptibility of a target dimension to the influence of a concurrent dimension increased as a function of participants' representational noise in the target dimension (e.g., the noisier length representations, the larger the time-on-space effect). In all, our study showed that the representational noise of space and time modulates the way the two dimensions interact. These findings suggest that cross-dimensional magnitude interactions arise as a result of memory interference, with noisier magnitudes being more prone to being nudged by concurrent magnitudes in other dimensions. Such memory interference can be seen as a result of Bayesian inference with correlated priors between magnitude dimensions.