Multiple Diffusion Models to Compare Saccadic and Manual Responses for Inhibition of Return

Neural Computation. 2017. No. 29(3). P. 804–824.

MacInnes W.

Cuing a location in space produces a short-lived advantage in time. This early advantage, however, switches to a reaction time and has been termed inhibition of return (IOR). IOR behaves differently for different response modalities, suggesting that it may not be a unified effect. Ion with random, continuous cue-target Euclidean distance and cue-target onset asynchrony. These data were then used to train multiple diffusion models of saccadic and manual reaction time for these cuing experiments. Diffusion models can generate accurate distributions of reaction time. If saccadic and attentional IOR are based on similar processes, then differences in distribution will be better explained by adjusting parameter values ​​such as signal and noise. Although experimental data show differences in the timing of the IOR, modularity, best-fit models are shown to have similar model parameters for the gradient of IOR, suggesting similar mechanisms for saccadic and manual IOR.

Keywords: spatial attention, diffusion model, inhibition of return (IOR), application of machine learning methods to the analysis of biomedical data, Genetic algorithm