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

Author(s):  
Anne-Marike Schiffer ◽  
Annika Boldt ◽  
Florian Waszak ◽  
Nick Yeung

The decisions we make are usually accompanied by a feeling of being wrong or right – a confidence estimate regarding the correctness of our decisions. The questions which information this confidence estimate is based on, and what confidence is used for, have increasingly become a focus of research into decision-making. This research has largely focused on confidence regarding current or past decisions, and successfully identified for example how characteristics of the stimulus affect confidence, and how communicating confidence can affect group decisions. Here, we report two studies which implemented a color-discrimination task which introduced a novel metacognitive measure: predictions of confidence for future perceptual decisions. Using behavioral measures, computational modeling, and EEG, we tested the hypothesis that experience-based confidence predictions are one source of information which affects how confident we are in future decision-making and that one key purpose of confidence is to prepare future encounters of a task. Results from both studies show that participants develop precise confidence predictions informed by confidence experienced in past trials. Notably, our results show a bi-directional link between predicted and experienced (performance) confidence: confidence predictions are not only informed by, but can also modulate performance confidence; this finding supports our recent proposal that confidence judgments are based on multiple sources of information, including expectations. We found further support for this bi-directional 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.Taken together, our results suggest that confidence integrates information from various sources, and affects neural processing profoundly. The bi-directional link between performance confidence and predicted confidence suggests that confidence signals are exploited to increase precision in preparation and evaluation of future decisions.

2020 ◽  
Vol 44 (4) ◽  
pp. 392-408
Author(s):  
Sasha A. Fleary ◽  
Patrece Joseph

Objective: Adolescents assume increased responsibility for their health, particularly regarding health decision-making for lifestyle behaviors. Prior research suggests a relationship between health literacy (HL) and health behaviors in adolescents. Yet, the specific role of HL in adolescents' health decision-making is unclear. This study qualitatively explored adolescents' use of HL in their health decision-making. Methods: Six focus groups with adolescents (N = 37, Mage = 16.49, 86% girls) were conducted. Adolescents' responses to questions about their HL use were coded using thematic analysis. Results: Adolescents identified passive and active HL engagement and several individual (eg, future orientation, risk perception) and environmental (eg, access to resources/information, media) factors that influenced their use of HL in health decision-making. Feedback from others, subjective health, and ability to navigate multiple sources of information also determined adolescents' confidence in their HL skills. Conclusions: Our results support expanding the types of HL studied/measured in adolescents and provide insight on how HL can be leveraged to improve adolescents' health decision-making. Though there was no guiding theory for this study, results support using the Information-Motivation-Behavior Skills model to assess the HL/health decision-making relationship in adolescence.


2018 ◽  
Vol 5 (7) ◽  
pp. 172143 ◽  
Author(s):  
Alexander Mielke ◽  
Anna Preis ◽  
Liran Samuni ◽  
Jan F. Gogarten ◽  
Roman M. Wittig ◽  
...  

Living in permanent social groups forces animals to make decisions about when, how and with whom to interact, requiring decisions to be made that integrate multiple sources of information. Changing social environments can influence this decision-making process by constraining choice or altering the likelihood of a positive outcome. Here, we conceptualized grooming as a choice situation where an individual chooses one of a number of potential partners. Studying two wild populations of sympatric primate species, sooty mangabeys ( Cercocebus atys atys ) and western chimpanzees ( Pan troglodytes verus ), we tested what properties of potential partners influenced grooming decisions, including their relative value based on available alternatives and the social relationships of potential partners with bystanders who could observe the outcome of the decision. Across 1529 decision events, multiple partner attributes (e.g. dominance ranks, social relationship quality, reproductive state, partner sex) influenced choice. Individuals preferred to initiate grooming with partners of similar global rank, but this effect was driven by a bias towards partners with a high rank compared to other locally available options. Individuals also avoided grooming partners who had strong social relationships with at least one bystander. Results indicated flexible decision-making in grooming interactions in both species, based on a partner's value given the local social environment. Viewing partner choice as a value-based decision-making process allows researchers to compare how different species solve similar social problems.


2015 ◽  
Vol 36 (8/9) ◽  
pp. 644-652 ◽  
Author(s):  
Cheryl Stenstrom

Purpose – The purpose of this paper is to explore and describe the decision-making practices of public library managers in the context of interpersonal influence and evidence-based information sources, and to investigate the relationship between models of evidence-based practice and interpersonal influence in the decision-making process of public library managers. Design/methodology/approach – Data were collected through short audio blog posts participants made about their everyday decisions and coded considering the facets of three existing evidence-based library and information practice (EBLIP) models as well as the facets of interpersonal influence. Findings – The findings show that public library CEOs decision-making behaviours reflect the use of a variety of practices from analytical to intuitive as is expected of managers in any sector; however, a stronger reliance on gathering objective information may be present than in other sectors. Seeking multiple sources of information and a tendency towards rationalism may indicate a more sophisticated approach to decision making, but be less indicative of the practices employed more broadly. A possible outcome of these tendencies may result in discordance with external partners and collaborators. Practical implications – The findings from this study may inform the work of associations, library and information science (LIS) educators, and library managers in developing strategic directions and instructional strategies within their organisations. It is also the first study to jointly examine models of interpersonal influence and evidence-based decision-making practices in any field. Originality/value – While the study of the decision-making practices of various groups is growing, little previous research has been conducted with public library managers, and none has been undertaken in Canada.


2005 ◽  
Vol 58 (5) ◽  
pp. 865-886 ◽  
Author(s):  
Patricia R. DeLucia

Previous studies indicate that non-tau sources of depth information, such as pictorial depth cues, can influence judgements of time to contact (TTC). The effect of relative size on such judgements, the size-arrival effect, is particularly robust. However, earlier studies of the size-arrival effect did not include binocular disparity or familiar size information. The effects of these cues on relative TTC judgements were measured. Results suggested that disparity can eliminate the size-arrival effect but that the amount of disparity needed to do so is greater than typical stereoacuity thresholds. In contrast, familiar size eliminated the size-arrival effect even when disparity information was not available. Furthermore, disparity contributed more to performance when familiar size was present than when it was absent. Consistent with previous studies, TTC judgements were influenced by multiple sources of information. The present results suggested further that familiar size is one such source of information and that familiar size moderates the influence of binocular disparity information.


2017 ◽  
Author(s):  
Vickie Li ◽  
Santiago Herce Castañón ◽  
Joshua A Solomon ◽  
Hildward Vandormael ◽  
Christopher Summerfield

AbstractAn ideal observer will give equivalent weight to sources of information that are equally reliable. However, when averaging visual information, human observers tend to downweight or discount features that are relatively outlying or deviant (‘robust averaging’). Why humans adopt an integration policy that discards important decision information remains unknown. Here, observers were asked to judge the average tilt in a circular array of high-contrast gratings, relative to an orientation boundary defined by a central reference grating. Observers showed robust averaging of orientation, but the extent to which they did so was a positive predictor of their overall performance. Using computational simulations, we show that although robust averaging is suboptimal for a perfect integrator, it paradoxically enhances performance in the presence of “late” noise, i.e. which corrupts decisions during integration. In other words, robust decision strategies increase the brain’s resilience to noise arising in neural computations during decision-making.Author SummaryHumans often make decisions by averaging information from multiple sources. When all the sources are equally reliable, they should all have equivalent impact (or weight) on the decisions of an “ideal” observer, i.e. one with perfect memory. However, recent experiments have suggested that humans give unequal weight to sources that are deviant or unusual, a phenomenon called “robust averaging”. Here, we use computer simulations to try to understand why humans do this. Our simulations show that under the assumption that information processing is limited by a source of internal uncertainty that we call “late” noise, robust averaging actually leads to improved performance. Using behavioural testing, we replicate the finding of robust averaging in a cohort of healthy humans, and show that those participants that engage in robust averaging perform better on the task. This study thus provides new information about the limitations on human decision-making.


Author(s):  
David A. Illingworth ◽  
Karen M. Feigh

Objective The reported study evaluated a novel approach to aiding geospatial reasoning and decision making. Background Impact mapping aims to alleviate the cognitive demands of geospatial tasks in part by externalizing data in the form of an integrated decision surface. This is achieved by aggregating data across multiple sources of information and visualizing their combined utility rather than objective measurements or individual utility. Previous research has shown that geospatial decisions improve when aided in this manner, but it remains unknown if dynamic decision making, often plagued by fatigue and anchoring bias, would benefit similarly. Method The experiment implemented a systematic manipulation of the presence of a composite impact map and the number of attributes present in a two-stage disaster relief, resource allocation task to investigate when and how impact mapping is beneficial or deleterious to decision makers. Results The presence of the composite impact map increased the utility of selected sites, increased re-planning decisions, reduced information display views, and reduced workload. Generally, the effect of the composite impact map was greater when participants were asked to evaluate more attributes. Conclusion Composite impact maps appear to improve repeated geospatial reasoning and minimize anchoring bias because they alleviate the cognitive demands otherwise necessary to interpret and maintain information from multiple attributes. Application Data visualization techniques, such as impact mapping, can improve repeated geospatial decision making in environments that include high cognitive demand.


2016 ◽  
Author(s):  
Casimir Johannes Hendrikus Ludwig ◽  
David R. Evens

We tested an information foraging framework to characterise the mechanisms that drive active (visual) sampling behaviour in decision problems that involve multiple sources of information. Experiments 1-3 involved participants making an absolute judgement about the direction of motion of a single random dot motion pattern. In Experiment 4, participants made a relative comparison between two motion patterns that could only be sampled sequentially. Our results show that: (i) Information (about noisy motion information) grows to an asymptotic level that depends on the quality of the information source; (ii) The limited growth is due to unequal weighting of the incoming sensory evidence, with early samples being weighted more heavily; (iii) Little information is lost once a new source of information is being sampled; (iv) The point at which the observer switches from one source to another is governed by on-line monitoring of his or her degree of (un)certainty about the sampled source. These findings demonstrate that the sampling strategy in perceptual decision-making is under some direct control by ongoing cognitive processing. More specifically, participants are able to track a measure of (un)certainty and use this information to guide their sampling behaviour.


2019 ◽  
Author(s):  
Brian Maniscalco ◽  
Brian Odegaard ◽  
Piercesare Grimaldi ◽  
Seong Hah Cho ◽  
Michele A. Basso ◽  
...  

AbstractCurrent dominant views hold that perceptual confidence reflects the probability that a decision is correct. Although these views have enjoyed some empirical support, recent behavioral results indicate that confidence and the probability of being correct can be dissociated. An alternative hypothesis suggests that confidence instead reflects the magnitude of evidence in favor of a decision while being relatively insensitive to the evidence opposing the decision. We considered how this alternative hypothesis might be biologically instantiated by developing a simple leaky competing accumulator neural network model incorporating a known property of sensory neurons: tuned normalization. The key idea of the model is that each accumulator neuron’s normalization ‘tuning’ dictates its contribution to perceptual decisions versus confidence judgments. We demonstrate that this biologically plausible model can account for several counterintuitive findings reported in the literature, where confidence and decision accuracy were shown to dissociate -- and that the differential contribution a neuron makes to decisions versus confidence judgments based on its normalization tuning is vital to capturing some of these effects. One critical prediction of the model is that systematic variability in normalization tuning exists not only in sensory cortices but also in the decision-making circuitry. We tested and validated this prediction in macaque superior colliculus (SC; a region implicated in decision-making). The confirmation of this novel prediction provides direct support for our model. These findings suggest that the brain has developed and implements this alternative, heuristic theory of perceptual confidence computation by capitalizing on the diversity of neural resources available.SignificanceThe dominant view of perceptual confidence proposes that confidence optimally reflects the probability that a decision is correct. But recent empirical evidence suggests that perceptual confidence exhibits a suboptimal ‘confirmation bias’, just as in human decision-making in general. We tested how this ‘bias’ might be neurally implemented by building a biologically plausible neural network model, and showed that the ‘bias’ emerges when each neuron’s degree of divisive normalization dictates how it drives decisions versus confidence judgments. We confirmed the model’s biological substrate using electrophysiological recordings in monkeys. These results challenge the dominant model, suggesting that the brain instead capitalizes on the diversity of available machinery (i.e., neuronal resources) to implement heuristic -- not optimal -- strategies to compute subjective confidence.


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