How spatial attention affects the decision process: looking through the lens of Bayesian hierarchical diffusion model & EEG analysis

We explored the underlying latent process of spatial prioritisation in perceptual decision processes, based on the drift-diffusion model, and subsequent nested model comparison. Our hierarchical cognitive modelling analysis revealed that spatial attention changed the non-decision time parameter across experimental conditions, quantified using the deviance information criterion score (DIC) and R-squared. We also constructed joint models with embedded neural covariates to discover which of contralateral and ipsilateral EEG measures could most manipulate spatial attention in perceptual decision making. Using multiple regression analysis, it can be concluded that poststimulus N2nc can predict mean response times and non-decision time parameters related to spatial prioritisation. However, the contralateral minus neutral alpha power at parieto-occipital electrodes can only predict the mean RTs and not the non-decision time relating to spatial prioritisation. Results suggest that individual differences in spatial attention are encoded more by contralateral (and not ipsilateral) N2 oscillations and non-decision times.