Confidence predicts speed-accuracy tradeoff for subsequent decisions

Abstract

When external feedback about decision outcomes is lacking, agents need to adapt their decision policies based on an internal estimate of the correctness of their choices (i.e., decision confidence). We hypothesized that agents use confidence to continuously update the tradeoff between the speed and accuracy of their decisions: When confidence is low in one decision, the agent needs more evidence before committing to a choice in the next decision, leading to slower but more accurate decisions. We tested this hypothesis by fitting a bounded accumulation decision model to behavioral data from three different perceptual choice tasks. Decision bounds indeed depended on the reported confidence on the previous trial, independent of objective accuracy. This increase in decision bound was predicted by a centro-parietal EEG component sensitive to confidence. We conclude that internally computed neural signals of confidence predict the ongoing adjustment of decision policies.

Trading accuracy for speed over the course of a decision

“…Several studies have now revealed the flexibility with which humans can adapt their choice SAT at different time-scales, including from one context to another (Forstmann et al, 2008;Herz et al, 2016Herz et al, , 2017 and from one decision to another (Desender et al, 2019;Fischer et al, 2018;Purcell & Kiani, 2016). The current findings offer a unique extension of this work, by showing that the SAT can be modulated on an even shorter time-scalei.e., over the course of a single decision.…”

“…Fast decisions involve low criteria, reducing the amount of evidence required for neural activity to reach the threshold, while longer and accurate deliberations imply higher criteria. Such adaptations were shown to occur both from one SAT context to another (Forstmann et al, 2008;Herz et al, 2016Herz et al, , 2017 and from one decision to another within the same context (Desender et al, 2019;Fischer et al, 2018;Purcell & Kiani, 2016), providing a key mechanism to trade speed with accuracy at different time-scales. About a decade ago, different studies revealed that the amount of evidence required to commit to a choice decreases over the course of a decision, indicative of an accuracy criterion that wanes as time elapses (i.e., rather than being fixed over time; e.g., Cisek et al, 2009).…”

Partially overlapping neural correlates of metacognitive monitoring and metacognitive control

“…Similarly, Yeung & Summerfield (2012 (Drescher, Van Den Bussche, & Desender, 2018) and that confidence modulates the speed accuracy tradeoff on a trial-by-trial basis with participants prioritizing accuracy over response speed after a previous low-confidence decision (Desender et al, 2019). The latter effect is reminiscent of post-error slowing (Rabbitt, 1966;Danielmeier & Ullsperger, 2011;Jentzsch & Dudschig, 2009), one of the most extensively studied effects of the cognitive control literature.…”

“…Research on MetaC, on the other hand, has focused on the many situations in which metacognitive experiences are utilized. Examples include learning (Metcalfe & Finn, 2008;Guggenmos, Wilbertz, Hebart, & Sterzer, 2016;Lak et al, 2020), communication (Shea et al, 2014;Bahrami, Olsen, Latham, Roepstorff, Rees, & Frith, 2010), and trial-by-trial adaptations in response speed (Desender, Boldt, Verguts, & Donner, 2019). One ubiquitous example of how confidence guides our behavior in everyday life is the above-mentioned example of setting a reminder to take a vitamin D supplement: Many situations require us to fulfill intentions not straight-away after they are formed but instead after some temporal delay or when they are triggered by another event.…”

The cognition/metacognition tradeoff

“…While cognition is the set of processes in which we make judgments about the world (e.g., deciding if a moving dot stimulus has mostly right/left motion), metacognition involves judgments we make about our own cognition (e.g., how confident we are of our decision). Taking confidence as a canonical example of a metacognitive judgment, humans can signal their decision-confidence in a way that is reliably related to their cognitive performance, and rely on confidence to modulate further cognition (Bahrami et al, 2010;Balsdon, Wyart & Mamassian, 2020;Carlebach & Yeung, 2020;Desender, Boldt, Verguts & Donner, 2019;Hainguerlot, Vergnaud & de Gardelle, 2018;Rollwage et al, 2020;Sanders, Hangya & Kepecs, 2016;van den Berg, Zylberberg, Kiani, Shadlen & Wolpert, 2016).…”