Evidence accumulation during perceptual decision-making is sensitive to the dynamics of attentional selection

Rangelov, Dragan; Mattingley, Jason B.

doi:10.1016/j.neuroimage.2020.117093

Cited by 33 publications

(56 citation statements)

References 54 publications

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“…Moreover, when the data were split into tertiles of fastest, middle, and slowest RTs, the P300 peak latency did not predict RTs or DTs in the AS task within participants. We also did not find a separate CPP from the P300 that predict RT or DT that better matched the CPP as found in other studies (O'Connell et al 2012; Kelly and O'Connell 2013;Rangelov and Mattingley 2020). This could be due to different task structure and demands.…”

Section: The P300 Does Not Track Decision-making In the Action Selectcontrasting

confidence: 80%

“…These findings in animal models have motivated studies in humans using EEG to identify a signal that ramps to a decision threshold, providing clear information about the rate and timing of decision-making (Kelly and O’Connell 2013; Philiastides et al 2014). A number of studies have focused on the P300, a stimulus-locked evoked potential that increases its positive amplitude over parietal electrodes, reaching a maximum at least 300 milliseconds (ms) after stimulus presentation (Philiastides et al 2006; Ratcliff et al 2009) or the closely related central-parietal positivity (CPP), a label that better accounts for the variability in the timing of the peak of positive potentials across different experiments (O’Connell et al 2012; Kelly and O’Connell 2013; Rangelov and Mattingley 2020). The P300 and CPP amplitudes are sensitive to stimulus probability and stimulus salience (Polich et al 1996; Smith and Ratcliff 2004), such that low-probability and high-salience sensory events elicit higher amplitude signals.…”

Section: Introductionmentioning

confidence: 99%

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Timing of readiness potentials reflect a decision-making process in the human brain

Lui

Nunez

Cassidy

et al. 2018

Preprint

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Perceptual decision making has several underlying components including stimulus encoding, perceptual categorization, response selection, and response execution. Evidence accumulation is believed to be the underlying mechanism of decision-making and plays a decisive role in determining response time. Previous studies in animals and humans have shown parietal cortex activity that exhibits characteristics of evidence accumulation in tasks requiring difficult perceptual categorization to reach a decision. In this study, we made use of a task where the challenge for the participants is to identify the stimulus and then from memory apply an abstract rule to select one of two possible actions. The task was designed so that stimulus identification was easy but response selection required cognitive computations and working memory. In simultaneous EEG recordings, we find a one-to-one relationship between the duration of the readiness potential observed prior to the response over motor areas, and decision-making time estimated by a drift-diffusion model of the response time distribution. This close relationship implies that the readiness potential reflects an evidence accumulation process for response selection, and supports the notion that evidence accumulation is a general neural implementation of decision-making. The evidence accumulation process that captures variability in decision-making time will depend on the location of the bottleneck in information processing.

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Section: The P300 Does Not Track Decision-making In the Action Selectcontrasting

confidence: 80%

Section: Introductionmentioning

confidence: 99%

Timing of readiness potentials reflect a decision-making process in the human brain

Lui

Nunez

Cassidy

et al. 2018

Preprint

View full text Add to dashboard Cite

show abstract

“…To quantify decision weights, a multiple-regression [ordinary least squares (OLS)] model with a term for each of the presented motion directions, expressed as complex numbers, was fitted to the responses, separately per participant and experimental condition. The absolute value of the resulting regression coefficients reflects the influence of each of the presented coherent motion signals on the response (i.e., its decision weight; Rangelov and Mattingley, 2020).…”

Section: Methodsmentioning

confidence: 99%

Stimulus Reliability Automatically Biases Temporal Integration of Discrete Perceptual Targets in the Human Brain

2021

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Many decisions, from crossing a busy street to choosing a profession, require integration of discrete sensory events. Previous studies have shown that integrative decision-making favors more reliable stimuli, mimicking statistically optimal integration. It remains unclear, however, whether reliability biases operate even when they lead to suboptimal performance. To address this issue, we asked human observers to reproduce the average motion direction of two suprathreshold coherent motion signals presented successively and with varying levels of reliability, while simultaneously recording whole-brain activity using electroencephalography. By definition, the averaging task should engender equal weighting of the two component motion signals, but instead we found robust behavioral biases in participants' average decisions that favored the more reliable stimulus. Using population-tuning modeling of brain activity we characterized tuning to the average motion direction. In keeping with the behavioral biases, the neural tuning profiles also exhibited reliability biases. A control experiment revealed that observers were able to reproduce motion directions of low and high reliability with equal precision, suggesting that unbiased integration in this task was not only theoretically optimal but demonstrably possible. Our findings reveal that temporal integration of discrete sensory events in the brain is automatically and suboptimally weighted according to stimulus reliability.

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“…In the case of the linear relationship between alpha power and attention, we were able to test for this tripartite relationship using our mediation analysis and demonstrate that a significant mediation pathway exists linking these three outcomes. It is important to note that as variations in spontaneous alpha power partially determined CPP amplitude, our observation adds to a growing literature that the CPP represents the accumulation of decision likelihood based on internal states, which include the subjective certainty of a decision (Gherman & Philiastides, 2015;Rangelov & Mattingley, 2020;Tagliabue et al, 2019), as opposed to a pure index of physical sensory evidence (e.g. (O'Connell et al, 2012).…”

Section: Prestimulus Alpha Power and Subjective Reportsmentioning

confidence: 67%

Alpha oscillations and stimulus-evoked activity dissociate metacognitive reports of attention, visibility and confidence in a rapid visual detection task

Davidson

Macdonald

Yeung

2021

Preprint

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Variability in the detection and discrimination of weak visual stimuli has been linked to prestimulus neural activity. In particular, the power of oscillatory activity in the alpha-band (8-12 Hz) has been shown to impact upon the objective likelihood of stimulus detection, as well as measures of subjective visibility, attention, and decision confidence. We aimed to clarify how prestimulus alpha influences performance and phenomenology, by recording simultaneous subjective measures of attention and confidence (Experiment 1), or attention and visibility (Experiment 2) on a trial-by-trial basis in a visual detection task. Across both experiments, prestimulus alpha power was negatively and linearly correlated with the intensity of subjective attention. In contrast to this linear relationship, we observed a quadratic relationship between the strength of prestimulus alpha power and subjective ratings of confidence and visibility. We find that this same quadratic relationship links prestimulus alpha power to the strength of stimulus evoked responses. Visibility and confidence judgements corresponded to the strength of evoked responses, but confidence, uniquely, incorporated information about attentional state. As such, our findings reveal distinct psychological and neural correlates of metacognitive judgements of attentional state, stimulus visibility, and decision confidence.

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Evidence accumulation during perceptual decision-making is sensitive to the dynamics of attentional selection

Cited by 33 publications

References 54 publications

Timing of readiness potentials reflect a decision-making process in the human brain

Timing of readiness potentials reflect a decision-making process in the human brain

Stimulus Reliability Automatically Biases Temporal Integration of Discrete Perceptual Targets in the Human Brain

Alpha oscillations and stimulus-evoked activity dissociate metacognitive reports of attention, visibility and confidence in a rapid visual detection task

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