Evidence Accumulation & Neuroscience

Breaking down the nature and speed of information processing stages that occur between a stimulus and a response (i.e. reaction time, RT), has been a problem in psychology and neuroscience for more than a century. In decision-making, the RT is classically considered as a composite measure of at least the time required to encode the alternatives and the time required to decide upon them. In the present study, we used a perceptual manipulation that aimed at simultaneously decreasing this encoding time and increasing the decision time, together with a speed accuracy trade-off manipulation. We first show, that a drift diffusion model with a relationship between drift rates and the Weber-Fechner law accounts for these data, despite the fact that our manipulation should also decrease non-decision time. We then estimate the trial-by-trial duration of each RT component using the hidden multivariate pattern method on electroencephalographic data. This method uses the assumption of a recurrent sequence of multivariate patterns in the neural time-series across trials to estimate the onset of these patterns. Among other things, we recover the expected opposite effect between encoding and decision time and show that the speed accuracy trade-off is more than a simple speed modulation of the RT and its components. This demonstration will show the value of detecting single-trial events in neural time series for answering research questions on mental chronometry and cognition in general.

This is an in-person presentation on July 21, 2024 (10:40 ~ 11:00 CEST).