Understanding neural signals of post-decisional performance monitoring: An integrative review.

Kobe Desender,K Richard Ridderinkhof,Peter R Murphy

doi:10.7554/elife.67556

Kobe Desender, K Richard Ridderinkhof + Show 1 more

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https://doi.org/10.7554/elife.67556

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Abstract

Performance monitoring is a key cognitive function, allowing to detect mistakes and adapt future behavior. Post-decisional neural signals have been identified that are sensitive to decision accuracy, decision confidence and subsequent adaptation. Here, we review recent work that supports an understanding of late error/confidence signals in terms of the computational process of post-decisional evidence accumulation. We argue that the error positivity, a positive-going centro-parietal potential measured through scalp electrophysiology, reflects the post-decisional evidence accumulation process itself, which follows a boundary crossing event corresponding to initial decision commitment. This proposal provides a powerful explanation for both the morphological characteristics of the signal and its relation to various expressions of performance monitoring. Moreover, it suggests that the error positivity –a signal with thus far unique properties in cognitive neuroscience – can be leveraged to furnish key new insights into the inputs to, adaptation, and consequences of the post-decisional accumulation process.

Highlights

Many of the choices that we make every day are based on noisy information, generated in environments that are complex and subject to change
We argue that the Pe reflects the computational process of postdecisional evidence accumulation: a proposal that accounts for the classical association of this signal with error detection (Dhar et al, 2011; Endrass et al, 2007; Nieuwenhuis et al, 2001; O’Connell et al, 2007; Steinhauser and Yeung, 2010; Wessel et al, 2011), and specific aspects of its morphology (Murphy et al, 2015) and more recent links with graded confidence judgments (Boldt and Yeung, 2015) and future behavioral adjustments (e.g. Desender et al, 2019a)
Single-trial, error-related fronto-central theta power was found to predict successful error detection and to correlate with both detection response time (RT) and the build-up rate of the Pe (Murphy et al, 2015) – all properties expected of an error evidence signal providing input to a post-decisional accumulation process that we propose is reflected in the Pe

Summary

Main text

Many of the choices that we make every day are based on noisy information, generated in environments that are complex and subject to change. Single-trial, error-related fronto-central theta power was found to predict successful error detection and to correlate with both detection RT and the build-up rate of the Pe (Murphy et al, 2015) – all properties expected of an error evidence signal providing input to a post-decisional accumulation process that we propose is reflected in the Pe. As outlined at the outset of our review, the ultimate goal of performance monitoring is to facilitate adjustments to behavior that are adaptive (Botvinick et al, 2001; Fernandez-Duque et al, 2000; Ridderinkhof et al, 2004; Shimamura, 2008): If a monitoring system detects that several errors have been made in a row, this likely calls for a change in the decision policy or model of the world that produced those errors (Purcell and Kiani, 2016a; Sarafyazd and Jazayeri, 2019). Recent advances in finger tracking might allow new light to be cast on the question of whether metacognitive experiences such as error awareness and confidence can emerge prior to choice commitment (Dotan et al, 2018; Dotan et al, 2019)

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Funding Funder KU Leuven