scholarly journals Neural encoding of perceived patch value during competitive and hazardous virtual foraging

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Brian Silston ◽  
Toby Wise ◽  
Song Qi ◽  
Xin Sui ◽  
Peter Dayan ◽  
...  
Keyword(s):  
Decision Making ◽  
Social Foraging ◽  
Survival Strategy ◽  
Neural Encoding ◽  
Individual Level ◽  
Hazardous Environments ◽  
Predatory Attack ◽  
Multidimensional Information ◽  
Human Participants ◽  
Foraging Task

AbstractNatural observations suggest that in safe environments, organisms avoid competition to maximize gain, while in hazardous environments the most effective survival strategy is to congregate with competition to reduce the likelihood of predatory attack. We probed the extent to which survival decisions in humans follow these patterns, and examined the factors that determined individual-level decision-making. In a virtual foraging task containing changing levels of competition in safe and hazardous patches with virtual predators, we demonstrate that human participants inversely select competition avoidant and risk diluting strategies depending on perceived patch value (PPV), a computation dependent on reward, threat, and competition. We formulate a mathematically grounded quantification of PPV in social foraging environments and show using multivariate fMRI analyses that PPV is encoded by mid-cingulate cortex (MCC) and ventromedial prefrontal cortices (vMPFC), regions that integrate action and value signals. Together, these results suggest humans utilize and integrate multidimensional information to adaptively select patches highest in PPV, and that MCC and vMPFC play a role in adapting to both competitive and predatory threats in a virtual foraging setting.

scholarly journals The neural encoding of information prediction errors during non-instrumental information seeking

2017 ◽  
Author(s):  
Maja Brydevall ◽  
Daniel Bennett ◽  
Carsten Murawski ◽  
Stefan Bode
Keyword(s):  
Decision Making ◽  
Information Seeking ◽  
Prediction Error ◽  
Reward Processing ◽  
Event Related Potential ◽  
Recent Theory ◽  
Prediction Errors ◽  
Neural Encoding ◽  
New Information ◽  
Human Participants

ABSTRACTIn a dynamic world, accurate beliefs about the environment are vital for survival, and individuals should therefore regularly seek out new information with which to update their beliefs. This aspect of behaviour is not well captured by standard theories of decision making, and the neural mechanisms of information seeking remain unclear. One recent theory posits that valuation of information results from representation of informative stimuli within canonical neural reward-processing circuits, even if that information lacks instrumental use. We investigated this question by recording EEG from twenty-three human participants performing a non-instrumental information-seeking task. In this task, participants could pay a monetary cost to receive advance information about the likelihood of receiving reward in a lottery at the end of each trial. Behavioural results showed that participants were willing to incur considerable monetary costs to acquire early but non-instrumental information. Analysis of the event-related potential elicited by informative cues revealed that the feedback-related negativity independently encoded both an information prediction error and a reward prediction error. These findings are consistent with the hypothesis that information seeking results from processing of information within neural reward circuits, and suggests that information may represent a distinct dimension of valuation in decision making under uncertainty.

The value of sociality

foresight ◽  
2014 ◽  
Vol 16 (4) ◽  
pp. 309-328 ◽  
Author(s):  
Evgeniya Lukinova ◽  
Mikhail Myagkov ◽  
Pavel Shishkin
Keyword(s):  
Decision Making ◽  
Utility Function ◽  
Social Relationship ◽  
Social Utility ◽  
Content Type ◽  
Individual Level ◽  
Know How ◽  
General Utility ◽  
The Social ◽  
Individual Decisions

Purpose – This paper aims to study the value of sociality. Recent experimental evidence has brought to light that the assumptions of the Prospect Theory by Kahneman and Tversky do not hold in the proposed substantive domain of “sociality”. In particular, the desire to be a part of the social environment, i.e. the environment where individuals make decisions among their peers, is not contingent on the framing. Evolutionary psychologists suggest that humans are “social animals” for adaptive reasons. However, entering a social relationship is inherently risky. Therefore, it is extremely important to know how much people value “sociality”, when the social outcomes are valued more than material outcomes and what kinds of adaptations people use. Design/methodology/approach – We develop a new theory and propose the general utility function that features “sociality” component. We test the theory in the laboratory experiments carried out in several countries. Findings – Our results suggest that when stakes are low the theory of “sociality” is successful in predicting individual decisions: on average, people do value “sociality” and it surpasses the monetary loss. Originality/value – The main contribution of this paper is the breakdown of the risk attitudes under low stakes and individual level of decision-making. Another advancement is the ability to formalize the social utility or the theory of “sociality” in an economic model; we use general utility function that we define both on the outcomes and on the process of the decision-making itself and test in laboratory studies.

scholarly journals Performance-based Social Comparisons in Humans and Long-tailed Macaques

2021 ◽  
Vol 8 (3) ◽  
pp. 325-350
Author(s):  
Stefanie Keupp ◽  
Farhan Abedin ◽  
Lena Jeanson ◽  
Carolin Kade ◽  
Josefine Kalbitz ◽  
...  
Keyword(s):  
Social Comparison ◽  
Task Performance ◽  
Social Comparisons ◽  
Task Type ◽  
Fine Grained ◽  
Evolutionary Origins ◽  
Human Thinking ◽  
Human Participants ◽  
Set Up ◽  
Foraging Task

Social comparisons are a fundamental feature of human thinking and affect self-evaluations and task performance. Little is known about the evolutionary origins of social comparison processes, however. Previous studies that investigated performance-based social comparisons in nonhuman primates yielded mixed results. We report three experiments that aimed (a) to explore how the task type may contribute to performance in monkeys, and (b) how a competitive set-up affects monkeys compared to humans. In a co-action touchscreen task, monkeys were neither influenced by nor interested in the performance of the partner. This may indicate that the experimental set-up was not sufficiently relevant to trigger social comparisons. In a novel co-action foraging task, monkeys increased their feeding speed in competitive and co-active conditions, but not in relation to the degree of competition. In an analogue of the foraging task, human participants were affected by partner performance and experimental context, indicating that the task is suitable to elicit social comparisons in humans. Our studies indicate that specifics of task and experimental setting are relevant to draw the monkeys’ attention to a co-actor and that, in line with previous research, a competitive element was crucial. We highlight the need to explore what constitutes “relevant” social comparison situations for monkeys as well as nonhuman animals in general, and point out factors that we think are crucial in this respect (e.g., task type, physical closeness, and the species’ ecology). We discuss that early forms of social comparisons evolved in purely competitive environments with increasing social tolerance and cooperative motivations allowing for more fine-grained processing of social information. Competition driven effects on task performance might constitute the foundation for the more elaborate social comparison processes found in humans, which may involve context-dependent information processing and metacognitive monitoring.

scholarly journals Cyborg Groups Enhance Face Recognition in Crowded Environments

2018 ◽  
Author(s):  
Davide Valeriani ◽  
Riccardo Poli
Keyword(s):  
Decision Making ◽  
Face Recognition ◽  
Machine Vision ◽  
Decision Confidence ◽  
Computer Interfaces ◽  
Recognition Experiment ◽  
Or Groups ◽  
Individual Decisions ◽  
Human Participants ◽  
Crowded Environments

AbstractRecognizing a person in a crowded environment is a challenging, yet critical, visual-search task for both humans and machine-vision algorithms. This paper explores the possibility of combining a residual neural network (ResNet), brain-computer interfaces (BCIs) and human participants to create “cyborgs” that improve decision making. Human participants and a ResNet undertook the same face-recognition experiment. BCIs were used to decode the decision confidence of humans from their EEG signals. Different types of cyborg groups were created, including either only humans (with or without the BCI) or groups of humans and the ResNet. Cyborg groups decisions were obtained weighing individual decisions by confidence estimates. Results show that groups of cyborgs are significantly more accurate (up to 35%) than the ResNet, the average participant, and equally-sized groups of humans not assisted by technology. These results suggest that melding humans, BCI, and machine-vision technology could significantly improve decision-making in realistic scenarios.

scholarly journals High-Fidelity Agent-Based Modeling to Support Prevention Decision-Making: an Open Science Approach

2021 ◽  
Author(s):  
Wouter H. Vermeer ◽  
Justin D. Smith ◽  
Uri Wilensky ◽  
C. Hendricks Brown
Keyword(s):  
Decision Making ◽  
Social Systems ◽  
Open Science ◽  
Model Verification ◽  
High Fidelity ◽  
Agent Based ◽  
Individual Level ◽  
Adverse Health Outcomes ◽  
Modeling Process ◽  
Novel Method

AbstractPreventing adverse health outcomes is complex due to the multi-level contexts and social systems in which these phenomena occur. To capture both the systemic effects, local determinants, and individual-level risks and protective factors simultaneously, the prevention field has called for adoption of system science methods in general and agent-based models (ABMs) specifically. While these models can provide unique and timely insight into the potential of prevention strategies, an ABM’s ability to do so depends strongly on its accuracy in capturing the phenomenon. Furthermore, for ABMs to be useful, they need to be accepted by and available to decision-makers and other stakeholders. These two attributes of accuracy and acceptability are key components of open science. To ensure the creation of high-fidelity models and reliability in their outcomes and consequent model-based decision-making, we present a set of recommendations for adopting and using this novel method. We recommend ways to include stakeholders throughout the modeling process, as well as ways to conduct model verification, validation, and replication. Examples from HIV and overdose prevention work illustrate how these recommendations can be applied.

The Importance of Bystanders in Threat Assessment and Management

2021 ◽  
pp. 423-436
Author(s):  
Randy Borum ◽  
Mary Rowe
Keyword(s):  
Decision Making ◽  
Family Members ◽  
Empirical Support ◽  
Threat Assessment ◽  
School Shootings ◽  
Mass Shootings ◽  
Individual Level ◽  
Targeted Violence ◽  
Intentional Acts ◽  
Common Barriers

Bystanders—those who observe or come to know about potential wrongdoing—are often the best source of preattack intelligence, including indicators of intent and “warning” behaviors. They are the reason that some planned attacks are foiled before they occur. Numerous studies of targeted violence (e.g., mass shootings and school shootings) have demonstrated that peers and bystanders often have knowledge of an attacker’s intentions, concerning communication, and troubling behavior before the attack occurs. This chapter describes—with empirical support—why threat assessment professionals should consider bystanders; outlines a model for understanding bystander decision-making; reviews common barriers to bystander reporting; and suggests ways to mitigate those barriers, to engage bystanders at an individual level, and to improve reporting. The principal aim of threat assessment is to prevent (primarily) intentional acts of harm. When tragic incidents of planned violence occur, however, it is almost always uncovered “that someone knew something” about the attack before it happened. This happens because, as attack plans unfold, people in several different roles may know, or come to know, something about what is happening before harm occurs. The perpetrators know, and so might others, including targets, family members, friends, coworkers, or even casual observers.

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