scholarly journals Robust Averaging Protects Decisions from Noise in Neural Computations

2017 ◽  
Author(s):  
Vickie Li ◽  
Santiago Herce Castañón ◽  
Joshua A Solomon ◽  
Hildward Vandormael ◽  
Christopher Summerfield
Keyword(s):  
Decision Making ◽  
Visual Information ◽  
Ideal Observer ◽  
Sources Of Information ◽  
Integration Policy ◽  
Multiple Sources ◽  
Healthy Humans ◽  
Neural Computations ◽  
Improved Performance ◽  
Orientation Boundary

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.

scholarly journals Adolescents' Health Literacy and Decision-making: A Qualitative Study

2020 ◽  
Vol 44 (4) ◽  
pp. 392-408
Author(s):  
Sasha A. Fleary ◽  
Patrece Joseph
Keyword(s):  
Decision Making ◽  
Health Literacy ◽  
Future Orientation ◽  
Subjective Health ◽  
Lifestyle Behaviors ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Health Decision Making ◽  
Study Results ◽  
Health Decision

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.

scholarly journals Flexible decision-making in grooming partner choice in sooty mangabeys and chimpanzees

2018 ◽  
Vol 5 (7) ◽  
pp. 172143 ◽  
Author(s):  
Alexander Mielke ◽  
Anna Preis ◽  
Liran Samuni ◽  
Jan F. Gogarten ◽  
Roman M. Wittig ◽  
...  
Keyword(s):  
Decision Making ◽  
Social Relationships ◽  
Partner Choice ◽  
Primate Species ◽  
Choice Situation ◽  
Decision Making Process ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Multiple Partner ◽  
Sooty Mangabeys

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.

Top-Down Predictions Determine Perceptions

2017 ◽  
Author(s):  
Martin V. Butz ◽  
Esther F. Kutter
Keyword(s):  
Graphical Models ◽  
Information Integration ◽  
Visual Processing ◽  
Visual Information ◽  
Generative Models ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Top Down ◽  
Bottom Up ◽  
The Brain

While bottom-up visual processing is important, the brain integrates this information with top-down, generative expectations from very early on in the visual processing hierarchy. Indeed, our brain should not be viewed as a classification system, but rather as a generative system, which perceives something by integrating sensory evidence with the available, learned, predictive knowledge about that thing. The involved generative models continuously produce expectations over time, across space, and from abstracted encodings to more concrete encodings. Bayesian information processing is the key to understand how information integration must work computationally – at least in approximation – also in the brain. Bayesian networks in the form of graphical models allow the modularization of information and the factorization of interactions, which can strongly improve the efficiency of generative models. The resulting generative models essentially produce state estimations in the form of probability densities, which are very well-suited to integrate multiple sources of information, including top-down and bottom-up ones. A hierarchical neural visual processing architecture illustrates this point even further. Finally, some well-known visual illusions are shown and the perceptions are explained by means of generative, information integrating, perceptual processes, which in all cases combine top-down prior knowledge and expectations about objects and environments with the available, bottom-up visual information.

Decision-making experiences of public library CEOs

2015 ◽  
Vol 36 (8/9) ◽  
pp. 644-652 ◽  
Author(s):  
Cheryl Stenstrom
Keyword(s):  
Decision Making ◽  
Information Science ◽  
Public Library ◽  
Library And Information Science ◽  
Evidence Based ◽  
Interpersonal Influence ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Content Type ◽  
The Relationship

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.

Perception of Synthesized Audible and Visible Speech

1990 ◽  
Vol 1 (1) ◽  
pp. 55-63 ◽  
Author(s):  
Dominic W. Massaro ◽  
Michael M. Cohen
Keyword(s):  
Speech Perception ◽  
Visual Information ◽  
Optimal Algorithm ◽  
Sources Of Information ◽  
Visible Speech ◽  
Multiple Sources ◽  
Categorical Information ◽  
Fuzzy Logical Model ◽  
Jaw Position ◽  
Combining Information

The research reported in this paper uses novel stimuli to study how speech perception is influenced by information presented to ear and eye. Auditory and visual sources of information (syllables) were synthesized and presented in isolation or in factorial combination. A five-step continuum between the syllables ibal and idal was synthesized along both auditory and visual dimensions, by varying properties of the syllable at its onset. The onsets of the second and third formants were manipulated in the audible speech. For the visible speech, the shape of the lips and the jaw position at the onset of the syllable were manipulated. Subjects’ identification judgments of the test syllables presented on videotape were influenced by both auditory and visual information. The results were used to test between a fuzzy logical model of speech perception (FLMP) and a categorical model of perception (CMP). These tests indicate that evaluation and integration of the two sources of information makes available continuous as opposed to just categorical information. In addition, the integration of the two sources appears to be nonadditive in that the least ambiguous source has the largest impact on the judgment. The two sources of information appear to be evaluated, integrated, and identified as described by the FLMP-an optimal algorithm for combining information from multiple sources. The research provides a theoretical framework for understanding the improvement in speech perception by hearing-impaired listeners when auditory speech is supplemented with other sources of information.

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

2017 ◽  
Author(s):  
Anne-Marike Schiffer ◽  
Annika Boldt ◽  
Florian Waszak ◽  
Nick Yeung
Keyword(s):  
Decision Making ◽  
Color Discrimination ◽  
Sources Of Information ◽  
Perceptual Decision Making ◽  
Multiple Sources ◽  
Behavioral Measures ◽  
Confidence Judgments ◽  
Source Of Information ◽  
Preparation And Evaluation ◽  
Confidence Estimate

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.

Impact Mapping for Geospatial Reasoning and Decision Making

2021 ◽  
pp. 001872082199902
Author(s):  
David A. Illingworth ◽  
Karen M. Feigh
Keyword(s):  
Decision Making ◽  
Dynamic Decision Making ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Cognitive Demands ◽  
Information Display ◽  
Planning Decisions ◽  
Novel Approach ◽  
Anchoring Bias ◽  
Visualization Techniques

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.

scholarly journals A Decision Method for Construction Safety Risk Management Based on Ontology and Improved CBR: Example of a Subway Project

2020 ◽  
Vol 17 (11) ◽  
pp. 3928 ◽  
Author(s):  
Xiaoyan Jiang ◽  
Sai Wang ◽  
Jie Wang ◽  
Sainan Lyu ◽  
Martin Skitmore
Keyword(s):  
Decision Making ◽  
Risk Management ◽  
Academic Research ◽  
Construction Safety ◽  
Management Decision ◽  
Case Based Reasoning ◽  
Sources Of Information ◽  
Multiple Sources ◽  
Safety Risk ◽  
Safety Risks

Early decision-making and the prevention of construction safety risks are very important for the safety, quality, and cost of construction projects. In the field of construction safety risk management, in the face of a loose, chaotic, and huge information environments, how to design an efficient construction safety risk management decision support method has long been the focus of academic research. An effective approach to safety management is to structuralize safety risk knowledge, then identify and reuse it, and establish a scientific and systematic construction safety risk management decision system. Based on ontology and improved case-based reasoning (CBR) methods, this paper proposes a decision-making approach for construction safety risk management in which the reasoning process is improved by integrating a similarity algorithm and correlation algorithm. Compared to the traditional CBR approach in which only the similarity of information is considered, this method can avoid missing important correlated information by making inferences from multiple sources of information. Finally, the method is applied to the safety risks of subway construction for verification to show that the method is effective and easy to implement.

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