6 research outputs found
Evidence accumulator or decision threshold - which cortical mechanism are we observing?
No full textMost psychological models of perceptual decision making are of the accumulation-to-threshold variety. The neural basis of accumulation in parietal and prefrontal cortex is therefore a topic of great interest in neuroscience. In contrast, threshold mechanisms have received less attention, and their neural basis has usually been sought in subcortical structures. Here I analyze a model of a decision threshold that can be implemented in the same cortical areas as evidence accumulators, and whose behavior bears on two open questions in decision neuroscience: 1) When ramping activity is observed in a brain region during decision making, does it reflect evidence accumulation? 2) Are changes in speed-accuracy tradeoffs and response biases more likely to be achieved by changes in thresholds, or in accumulation rates and starting points? The analysis suggests that task-modulated ramping activity, by itself, is weak evidence that a brain area mediates evidence accumulation as opposed to threshold readout; and that signs of modulated accumulation are as likely to indicate threshold adaptation as adaptation of starting points and accumulation rates. These conclusions imply that how thresholds are modeled can dramatically impact accumulator-based interpretations of this data
Speed Accuracy Trade-off Under Response Deadlines
No full textPerceptual decision making has been successfully modeled as a process of evidence accumulation up to a threshold. In order to maximize the rewards earned for correct responses in tasks with response deadlines, participants should collapse decision thresholds dynamically during each trial so that a decision is reached before the deadline. This strategy ensures on-time responding, though at the cost of reduced accuracy, since slower decisions are based on lower thresholds and less net evidence later in a trial (compared to a constant threshold). Frazier & Yu (2008) showed that the normative rate of threshold reduction depends on deadline delays and on participants’ uncertainty about these delays. Participants should start collapsing decision thresholds earlier when making decisions under shorter deadlines (for a given level of timing uncertainty) or when timing uncertainty is higher (for a given deadline). We tested these predictions using human participants in a random dot motion discrimination task. Each participant was tested in free-response, short deadline (800 ms), and long deadline conditions (1000 ms). Contrary to optimal-performance predictions, the resulting empirical function relating accuracy to response time (RT) in deadline conditions did not decline to chance level near the deadline; nor did the slight decline we typically observed relate to measures of endogenous timing uncertainty. Further, although this function did decline slightly with increasing RT, the decline was explainable by the best-fitting parameterization of Ratcliff's diffusion model (Ratcliff, 1978), whose parameters are constant within trials. Our findings suggest that at the very least, typical decision durations are too short for participants to adapt decision parameters within trials
Optimal Temporal Risk Assessment
No full textTime is an essential feature of most decisions. Keeping track of time is adaptive because the reward earned from decisions frequently depends on the temporal statistics of the environment. Accordingly, evolution appears to have favored a mechanism that predicts intervals in the seconds-to-minutes range with high accuracy on average, but significant variability from trial to trial. Importantly, the subjective sense of time that results is sufficiently imprecise that maximizing rewards can require substantial behavioral adjustments in response to this temporal uncertainty. Reward-maximization in many daily decisions therefore requires optimal temporal risk assessment. Using tasks that entail different decisions and that impose different time constraints on the reward function, we examine temporal risk assessment ability in terms of the degree to which it approaches optimality. We review recent literature and present human and rodent data that strongly support the hypothesis that these animals take normative account of their endogenous timing uncertainty. By incorporating the psychophysics of interval timing into the study of reward maximization, our approach bridges empirical and theoretical gaps between the interval timing and decision making literatures
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EEG oscillations reveal neural correlates of evidence accumulation
No full textRecent studies have begun to elucidate the neural correlates of evidence accumulation in perceptual decision making, but few of them have used a combined modeling-electrophysiological approach to studying evidence accumulation. We introduce a multivariate approach to EEG analysis with which we can perform a comprehensive search for the neural correlate of dynamics predicted by accumulator models. We show that the dynamics of evidence accumulation are most strongly correlated with ramping of oscillatory power in the 4-9 Hz theta band over the course of a trial, although it also correlates with oscillatory power in other frequency bands. The rate of power decrease in the theta band correlates with individual differences in the parameters of drift diffusion models fitted to individuals' behavioral data
