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Several studies have suggested that the centro-parietal positivity (CPP), an EEG potential occurring approximately 500 ms post-stimulus, reflects the accumulation of evidence for making a decision. Yet, most previous studies of the CPP focused exclusively on perceptual decisions with very simple stimuli. In this study, we examined how the dynamics of the CPP depended on the type of decision being made, and whether its slope was related to parameters of an accumulator model of decision making. We show initial evidence that memory- and perceptual decisions about carefully-controlled face stimuli exhibit similar dynamics, but offset by a time difference in decision onset. Importantly, the individual-trial slopes of the CPP are related to the accumulator model's drift parameter. These findings help to further understand the role of the CPP across different kinds of decisions., (Copyright © 2019 The Authors. Published by Elsevier B.V. All rights reserved.)

Background: We assessed whether evidence accumulation could be observed in the BOLD signal during perceptual decision making. This presents a challenge since the hemodynamic response is slow, while perceptual decisions are typically fast., New Method: Guided by theoretical predictions of the drift diffusion model, we slowed down decisions by penalizing participants for incorrect responses. Second, we distinguished BOLD activity related to stimulus detection (modeled using a boxcar) from activity related to integration (modeled using a ramp) by minimizing the collinearity of GLM regressors. This was achieved by dissecting a boxcar into its two most orthogonal components: an "up-ramp" and a "down-ramp." Third, we used a control condition in which stimuli and responses were similar to the experimental condition, but that did not engage evidence accumulation of the stimuli., Results: The results revealed an absence of areas in parietal cortex that have been proposed to drive perceptual decision making but have recently come into question; and newly identified regions that are candidates for involvement in evidence accumulation., Comparison With Existing Methods: Previous fMRI studies have either used fast perceptual decision making, which precludes the measurement of evidence accumulation, or slowed down responses by gradually revealing stimuli. The latter approach confounds perceptual detection with evidence accumulation because accumulation is constrained by perceptual input., Conclusions: We slowed down the decision making process itself while leaving perceptual information intact. This provided a more sensitive and selective observation of brain regions associated with the evidence accumulation processes underlying perceptual decision making than previous methods., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Many perceptual decision making models posit that participants accumulate noisy evidence over time to improve the accuracy of their decisions, and that in free response tasks, participants respond when the accumulated evidence reaches a decision threshold. Research on the neural correlates of these models' components focuses primarily on evidence accumulation. Far less attention has been paid to the neural correlates of decision thresholds, reflecting the final commitment to a decision. Inspired by a model of bistable neural activity that implements a decision threshold, we reinterpret human lateralized readiness potentials (LRPs) as reflecting the crossing of a decision threshold. Interestingly, this threshold crossing preserves signatures of a drift-diffusion process of evidence accumulation that feeds in to the threshold mechanism. We show that, as our model predicts, LRP amplitudes and growth rates recorded while participants performed a motion discrimination task correlate with individual differences in behaviorally-estimated prior beliefs, decision thresholds and evidence accumulation rates. As such LRPs provide a useful measure to test dynamical models of both evidence accumulation and decision commitment processes non-invasively.

Preparing for the future during ongoing activities is an essential skill. Yet it is currently unclear to what extent we can prepare for the future in parallel with another task. In two experiments, we investigated how characteristics of a present task influenced whether and when participants prepared for the future, as well as its usefulness. We focused on the influence of concurrent working memory load, assuming that working memory would interfere most strongly with preparation. In both experiments, participants performed a novel sequential dual-task paradigm, in which they could voluntarily prepare for a second task while performing a first task. We identified task preparation by means of eye tracking, by detecting when participants switched their gaze to information about the second task while performing the first task. The results showed that participants prepared, but also that there were large individual differences in how often they did so. When participants prepared, it was productive, as evidenced by faster RTs on the second task and only a small cost to the present task. The probability of preparation and its productiveness decreased with increases in the difficulty of the first task. In particular, we found that working memory load from the first task interfered with preparation. We conclude from our study that people can productively prepare for the future while performing an ongoing task, and that it is possible to track this preparation process empirically. In addition, we conclude that working memory resources play an important role in task preparation.

Models of evidence accumulation have been very successful at describing human decision making behavior. Recent years have also seen the first reports of neural correlates of this accumulation process. However, these studies have mostly focused on perceptual decision making tasks, ignoring the role of additional cognitive processes like memory retrieval that are crucial in real-world decisions. In this study, we tried to find a neural signature of evidence accumulation during a recognition memory task. To do this, we applied a method we have successfully used to localize evidence accumulation in scalp EEG during a perceptual decision making task. This time, however, we applied it to intracranial EEG recordings, which provide a much higher spatial resolution. We identified several brain areas where activity ramps up over time, but these neural patterns do not appear to be modulated by behavioral variables such as the amount of available evidence or response time. This casts doubt on the idea of evidence accumulation as a general decision-making mechanism underlying different types of decisions. [ABSTRACT FROM AUTHOR]