Publications

33 Publications

2014

van Vugt, M. K., Simen, P., Nystrom, L. E., Holmes, P. J., & Cohen, J. D. (2014). Lateralized Readiness Potentials Reveal Properties of a Neural Mechanism for Implementing a Decision Threshold. PLoS ONE, 9, e90943. https://doi.org/10.1371/journal.pone.0090943
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.

2015

Field, B. A., Buck, C. L., McClure, S. M., Nystrom, L. E., Kahneman, D., & Cohen, J. D. (2015). Attentional Modulation of Brain Responses to Primary Appetitive and Aversive Stimuli. PLoS ONE, 10, e0130880. https://doi.org/10.1371/journal.pone.0130880
Studies of subjective well-being have conventionally relied upon self-report, which directs subjects’ attention to their emotional experiences. This method presumes that attention itself does not influence emotional processes, which could bias sampling. We tested whether attention influences experienced utility (the moment-by-moment experience of pleasure) by using functional magnetic resonance imaging (fMRI) to measure the activity of brain systems thought to represent hedonic value while manipulating attentional load. Subjects received appetitive or aversive solutions orally while alternatively executing a low or high attentional load task. Brain regions associated with hedonic processing, including the ventral striatum, showed a response to both juice and quinine. This response decreased during the high-load task relative to the low-load task. Thus, attentional allocation may influence experienced utility by modulating (either directly or indirectly) the activity of brain mechanisms thought to represent hedonic value.

2017

Krueger, P. M., van Vugt, M. K., Simen, P., Nystrom, L. E., Holmes, P. J., & Cohen, J. D. (2017). Evidence accumulation detected in BOLD signal using slow perceptual decision making. Journal of Neuroscience Methods, 281, 21–32. https://doi.org/10.1016/j.jneumeth.2017.01.012
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.