Outsourcing Memory to External Tools: A Review of 'Intention Offloading'.

How do we remember delayed intentions? Three decades of research into prospective memory have provided insight into the cognitive and neural mechanisms involved in this form of memory. However, we depend on more than just our brains to remember intentions. We also use external props and tools such as calendars and diaries, strategically placed objects, and technologies such as smartphone alerts. This is known as 'intention offloading'. Despite the progress in our understanding of brain-based prospective memory, we know much less about the role of intention offloading in individuals' ability to fulfil delayed intentions. Here, we review recent research into intention offloading, with a particular focus on how individuals decide between storing intentions in internal memory versus external reminders. We also review studies investigating how intention offloading changes across the lifespan and how it relates to underlying brain mechanisms. We conclude that intention offloading is highly effective, experimentally tractable, and guided by metacognitive processes. Individuals have systematic biases in their offloading strategies that are stable over time. Evidence also suggests that individual differences and developmental changes in offloading strategies are driven at least in part by metacognitive processes. Therefore, metacognitive interventions could play an important role in promoting individuals' adaptive use of cognitive tools.

Partially Overlapping Neural Correlates of Metacognitive Monitoring and Metacognitive Control.

Metacognition describes the process of monitoring one's own mental states, often for the purpose of cognitive control. Previous research has investigated how metacognitive signals are generated (metacognitive monitoring), for example, when people (both female/male) judge their confidence in their decisions and memories. Research has also investigated how metacognitive signals are used to influence behavior (metacognitive control), for example, setting a reminder (i.e., cognitive offloading) for something you are not confident you will remember. However, the mapping between metacognitive monitoring and metacognitive control needs further study on a neural level. We used fMRI to investigate a delayed-intentions task with a reminder element, allowing human participants to use their metacognitive insight to engage metacognitive control. Using multivariate pattern analysis, we found that we could separately decode both monitoring and control, and, to a lesser extent, cross-classify between them. Therefore, brain patterns associated with monitoring and control are partially, but not fully, overlapping.SIGNIFICANCE STATEMENT Models of metacognition commonly distinguish between monitoring (how metacognition is formed) and control (how metacognition is used for behavioral regulation). Research into these facets of metacognition has often happened in isolation. Here, we provide a study which directly investigates the mapping between metacognitive monitoring and metacognitive control at a neural level. We applied multivariate pattern analysis to fMRI data from a novel task in which participants separately rated their confidence (metacognitive monitoring) and how much they would like to use a reminder (metacognitive control). We find support for the notion that the two aspects of metacognition overlap partially but not fully. We argue that future research should focus on how different metacognitive signals are selected for control.

Confidence guides spontaneous cognitive offloading.

BACKGROUND: Cognitive offloading is the use of physical action to reduce the cognitive demands of a task. Everyday memory relies heavily on this practice; for example, when we write down to-be-remembered information or use diaries, alerts, and reminders to trigger delayed intentions. A key goal of recent research has been to investigate the processes that trigger cognitive offloading. This research has demonstrated that individuals decide whether or not to offload based on a potentially erroneous metacognitive evaluation of their mental abilities. Therefore, improving the accuracy of metacognitive evaluations may help to optimise offloading behaviour. However, previous studies typically measure participants' use of an explicitly instructed offloading strategy, in contrast to everyday life where offloading strategies must often be generated spontaneously. RESULTS: We administered a computer-based task requiring participants to remember delayed intentions. One group of participants was explicitly instructed on a method for setting external reminders; another was not. The latter group spontaneously set reminders but did so less often than the instructed group. Offloading improved performance in both groups. Crucially, metacognition (confidence in unaided memory ability) guided both instructed and spontaneous offloading: Participants in both groups set more reminders when they were less confident (regardless of actual memory ability). CONCLUSIONS: These results show that the link between metacognition and cognitive offloading holds even when offloading strategies need to be spontaneously generated. Thus, metacognitive interventions are potentially able to alter offloading behaviour, without requiring offloading strategies to be explicitly instructed.

Confidence predicts speed-accuracy tradeoff for subsequent decisions.

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.

Confidence modulates exploration and exploitation in value-based learning.

Uncertainty is ubiquitous in cognitive processing. In this study, we aim to investigate the ability agents possess to track and report the noise inherent in their mental operations, often in the form of confidence judgments. Here, we argue that humans can use uncertainty inherent in their representations of value beliefs to arbitrate between exploration and exploitation. Such uncertainty is reflected in explicit confidence judgments. Using a novel variant of a multi-armed bandit paradigm, we studied how beliefs were formed and how uncertainty in the encoding of these value beliefs (belief confidence) evolved over time. We found that people used uncertainty to arbitrate between exploration and exploitation, reflected in a higher tendency toward exploration when their confidence in their value representations was low. We furthermore found that value uncertainty can be linked to frameworks of metacognition in decision making in two ways. First, belief confidence drives decision confidence, i.e. people's evaluation of their own choices. Second, individuals with higher metacognitive insight into their choices were also better at tracing the uncertainty in their environment. Together, these findings argue that such uncertainty representations play a key role in the context of cognitive control.

Confidence Predictions Affect Performance Confidence and Neural Preparation in Perceptual Decision Making.

Decisions are usually accompanied by a feeling of being wrong or right - a subjective confidence estimate. But what information is this confidence estimate based on, and what is confidence used for? To answer these questions, research has largely focused on confidence regarding current or past decisions, for example identifying how characteristics of the stimulus affect confidence, how confidence can be used as an internally generated feedback signal, and how communicating confidence can affect group decisions. Here, we report two studies which implemented a novel metacognitive measure: predictions of confidence for future perceptual decisions. Using computational modeling of behaviour and EEG, we established that experience-based confidence predictions are one source of information that affects how confident we are in future decision-making, and that learned confidence-expectations affect neural preparation for future decisions. Results from both studies show that participants develop precise confidence predictions informed by past confidence experience. Notably, our results also show that confidence predictions affect performance confidence rated after a decision is made; this finding supports the proposal that confidence judgments are based on multiple sources of information, including expectations. We found strong support for this link in neural correlates of stimulus preparation and processing. EEG measures of preparatory neural activity (contingent negative variation; CNV) and evidence accumulation (centro-parietal positivity; CPP) show that predicted confidence affects neural preparation for stimulus processing, supporting the proposal that one purpose of confidence judgments may be to learn about performance for future encounters and prepare accordingly.

A Postdecisional Neural Marker of Confidence Predicts Information-Seeking in Decision-Making.

Theoretical work predicts that decisions made with low confidence should lead to increased information-seeking. This is an adaptive strategy because it can increase the quality of a decision, and previous behavioral work has shown that decision-makers engage in such confidence-driven information-seeking. The present study aimed to characterize the neural markers that mediate the relationship between confidence and information-seeking. A paradigm was used in which 17 human participants (9 male) made an initial perceptual decision, and then decided whether or not they wanted to sample more evidence before committing to a final decision and confidence judgment. Predecisional and postdecisional event-related potential components were similarly modulated by the level of confidence and by information-seeking choices. Time-resolved multivariate decoding of scalp EEG signals first revealed that both information-seeking choices and decision confidence could be decoded from the time of the initial decision to the time of the subsequent information-seeking choice (within-condition decoding). No above-chance decoding was visible in the preresponse time window. Crucially, a classifier trained to decode high versus low confidence predicted information-seeking choices after the initial perceptual decision (across-condition decoding). This time window corresponds to that of a postdecisional neural marker of confidence. Collectively, our findings demonstrate, for the first time, that neural indices of confidence are functionally involved in information-seeking decisions.SIGNIFICANCE STATEMENT Despite substantial current interest in neural signatures of our sense of confidence, it remains largely unknown how confidence is used to regulate behavior. Here, we devised a task in which human participants could decide whether or not to sample additional decision-relevant information at a small monetary cost. Using neural recordings, we could predict such information-seeking choices based on a neural signature of decision confidence. Our study illuminates a neural link between decision confidence and adaptive behavioral control.

Subjective Confidence Predicts Information Seeking in Decision Making.

There is currently little direct evidence regarding the function of subjective confidence in decision making: The tight correlation between objective accuracy and subjective confidence makes it difficult to distinguish each variable's unique contribution. Here, we created conditions in a perceptual decision task that were matched in accuracy but differed in subjective evaluation of accuracy by orthogonally varying the strength versus variability of evidence. Confidence was reduced with variable (vs. weak) evidence, even across conditions matched for difficulty. Building on this dissociation, we constructed a paradigm in which participants ( N = 20) could choose to seek further information before making their decision. The data provided clear support for the hypothesis that subjective confidence predicts information seeking in decision making: Participants were more likely to sample additional information before giving a response in the condition with low confidence, despite matched accuracy. In a preregistered replication ( N = 50), these findings were replicated with increased task difficulty levels.

The impact of evidence reliability on sensitivity and bias in decision confidence.

Human observers effortlessly and accurately judge their probability of being correct in their decisions, suggesting that metacognitive evaluation is an integral part of decision making. It remains a challenge for most models of confidence, however, to explain how metacognitive judgments are formed and which internal signals influence them. While the decision-making literature has suggested that confidence is based on privileged access to the evidence that gives rise to the decision itself, other lines of research on confidence have commonly taken the view of a multicue model of confidence. The present study aims at manipulating one such cue: the perceived reliability of evidence supporting an initial decision. Participants made a categorical judgment of the average color of an array of eight colored shapes, for which we critically manipulated both the distance of the mean color from the category boundary (evidence strength) and the variability of colors across the eight shapes (evidence reliability). Our results indicate that evidence reliability has a stronger impact on confidence than evidence strength. Specifically, we found that evidence reliability affects metacognitive readout, the mapping from subjectively experienced certainty to expressed confidence, allowing participants to adequately adjust their confidence ratings to match changes in objective task performance across conditions. (PsycINFO Database Record

Shared neural markers of decision confidence and error detection.

Empirical evidence indicates that people can provide accurate evaluations of their own thoughts and actions by means of both error detection and confidence judgments. This study investigates the foundations of these metacognitive abilities, specifically focusing on the relationship between confidence and error judgments in human perceptual decision making. Electroencephalography studies have identified the error positivity (Pe)--an event-related component observed following incorrect choices--as a robust neural index of participants' awareness of their errors in simple decision tasks. Here we assessed whether the Pe also varies in a graded way with participants' subjective ratings of decision confidence, as expressed on a 6-point scale after each trial of a dot count perceptual decision task. We observed clear, graded modulation of the Pe by confidence, with monotonic reduction in Pe amplitude associated with increasing confidence in the preceding choice. This effect was independent of objective accuracy. Multivariate decoding analyses indicated that neural markers of error detection were predictive of varying levels of confidence in correct decisions, including subtle shifts in high-confidence trials. These results suggest that shared mechanisms underlie two forms of metacognitive evaluation that are often treated separately, with consequent implications for current theories of their neurocognitive basis.

Supra-personal cognitive control and metacognition.

The human mind is extraordinary in its ability not merely to respond to events as they unfold but also to adapt its own operation in pursuit of its agenda. This 'cognitive control' can be achieved through simple interactions among sensorimotor processes, and through interactions in which one sensorimotor process represents a property of another in an implicit, unconscious way. So why does the human mind also represent properties of cognitive processes in an explicit way, enabling us to think and say 'I'm sure' or 'I'm doubtful'? We suggest that 'system 2 metacognition' is for supra-personal cognitive control. It allows metacognitive information to be broadcast, and thereby to coordinate the sensorimotor systems of two or more agents involved in a shared task.

Get out of here, quick! Problems with transparent labels on glass doors.

We studied the case of transparent word labels (e.g., "push") placed on glass doors, when viewed from the other side as mirror-reversed script, hence requiring an action opposite to word meaning. As compared with a regular view, labels seen "from the other side" in the glass door situation caused strong delays of actions and a tripling of error rates. This problem is unrelated to mirror reading but is at least partially due to the need to act opposite to word meaning. The glass door effect was not related to practice and age and showed no adaptation effect after incompatible trials. Distribution analyses showed an increased correct reaction time (RT) effect for slower responses, whereas accuracy effects were specific for fast responses. In the literature, problems with such mixed mappings have often been interpreted in the sense of competing action tendencies. Experiments 1 to 4, however, demonstrated that this might merely be a task difficulty effect due to the necessity for a mental transformation in case of mirror-reversed labels. Moreover, our results strongly advocate against using transparent labels because they may pose a considerable risk.

Separating stimulus-driven and response-related LRP components with Residue Iteration Decomposition (RIDE).

When the lateralized readiness potential (LRP) is recorded in stimulus-response compatibility (SRC) tasks, two processes may overlap in the LRP, stimulus-driven response priming and activation based on response selection rules. These overlapping processes are hard to disentangle with standard analytical tools. Here, we show that Residue Iteration Decomposition (RIDE), based on latency variability, separates the overlapping LRP components from a Simon task into stimulus-driven and response-related components. SRC affected LRP amplitudes only in the stimulus-driven component, whereas LRP onsets were affected only in the response-locked component. Importantly, the compatibility effect in reaction times was more similar to the effect in the onsets of the RIDE-derived response-locked LRP component than in the unseparated LRP. Thus, RIDE-separated LRP components are devoid of distortions inherent to standard LRPs.