scholarly journals On the flexibility of basic risk attitudes in monkeys

2018 ◽  
Author(s):  
Shiva Farashahi ◽  
Habiba Azab ◽  
Benjamin Hayden ◽  
Alireza Soltani
Keyword(s):  
Computational Models ◽  
Weighting Function ◽  
Neural Substrates ◽  
Risk Attitudes ◽  
Economic Choice ◽  
Risky Choices ◽  
Differential Weighting ◽  
Plausible Mechanism ◽  
Linear Probability ◽  
Gains And Losses

ABSTRACTMonkeys and other animals appear to share with humans two risk attitudes predicted by prospect theory: an inverse-S-shaped probability weighting function and a steeper utility curve for losses than for gains. These findings suggest that such preferences are stable traits with common neural substrates. We hypothesized instead that animals tailor their preferences to subtle changes in task contexts, making risk attitudes flexible. Previous studies used a limited number of outcomes, trial types, and contexts. To gain a broader perspective, we examined two large datasets of male macaques’ risky choices: one from a task with real (juice) gains and another from a token task with gains and losses. In contrast to previous findings, monkeys were risk-seeking for both gains and losses (i.e. lacked a reflection effect) and showed steeper gain than loss curves (loss-seeking). Utility curves for gains were substantially different in the two tasks. Monkeys showed nearly linear probability weightings in one task and S-shaped ones in the other; neither task produced a consistent inverse-S-shaped curve. To account for these observations, we developed and tested various computational models of the processes involved in the construction of reward value. We found that adaptive differential weighting of prospective gamble outcomes could partially account for the observed differences in the utility functions across the two experiments and thus, provide a plausible mechanism underlying flexible risk attitudes. Together, our results support the idea that risky choices are flexibly constructed at the time of elicitation and place important constraints on neural models of economic choice.

scholarly journals Shifting uncertainty intolerance: methylphenidate and attention-deficit hyperactivity disorder

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Alekhya Mandali ◽  
Arjun Sethi ◽  
Mara Cercignani ◽  
Neil A. Harrison ◽  
Valerie Voon
Keyword(s):  
Decision Making ◽  
Attention Deficit Hyperactivity Disorder ◽  
Attention Deficit ◽  
Computational Models ◽  
Risky Choice ◽  
Risk Tolerance ◽  
Healthy Population ◽  
Hyperactivity Disorder ◽  
Risky Choices ◽  
Cardinal Symptom

AbstractRisk evaluation is a critical component of decision making. Risk tolerance is relevant in both daily decisions and pathological disorders such as attention-deficit hyperactivity disorder (ADHD), where impulsivity is a cardinal symptom. Methylphenidate, a commonly prescribed drug in ADHD, improves attention but has mixed reports on risk-based decision making. Using a double-blinded placebo protocol, we studied the risk attitudes of ADHD patients and age-matched healthy volunteers while performing the 2-step sequential learning task and examined the effect of methylphenidate on their choices. We then applied a novel computational analysis using the hierarchical drift–diffusion model to extract parameters such as threshold (‘a’—amount of evidence accumulated before making a decision), drift rate (‘v’—information processing speed) and response bias (‘z’ apriori bias towards a specific choice) focusing specifically on risky choice preference. Critically, we show that ADHD patients on placebo have an apriori bias towards risky choices compared to controls. Furthermore, methylphenidate enhanced preference towards risky choices (higher apriori bias) in both groups but had a significantly greater effect in the patient population independent of clinical scores. Thus, methylphenidate appears to shift tolerance towards risky uncertain choices possibly mediated by prefrontal dopaminergic and noradrenergic modulation. We emphasise the utility of computational models in detecting underlying processes. Our findings have implications for subtle yet differential effects of methylphenidate on ADHD compared to healthy population.

scholarly journals Salience-driven value construction for adaptive choice under risk

2018 ◽  
Author(s):  
Mehran Spitmaan ◽  
Emily Chu ◽  
Alireza Soltani
Keyword(s):  
Reward Magnitude ◽  
Human Subjects ◽  
Real Life ◽  
Individual Outcomes ◽  
Single Piece ◽  
Differential Weighting ◽  
Adaptive Choice ◽  
Plausible Mechanism ◽  
Reward Information ◽  
Adaptive Decision Making

Decisions we face in real life are inherently risky and can result in one of many possible outcomes. However, most of what we know about choice under risk is based on studies that use options with only two possible outcomes (simple gambles), so it remains unclear how the brain constructs reward values for more complex risky options faced in real life. To address this question, we combined experimental and modeling approaches to examine choice between pairs of simple gambles and pairs of three-outcome gambles in male and female human subjects. We found that subjects evaluated individual outcomes of three-outcome gambles by multiplying functions of reward magnitude and probability. To construct the overall value of each gamble, however, most subjects differentially weighted possible outcomes based on either reward magnitude or probability. These results reveal a novel dissociation between how reward information is processed when evaluating complex gambles: valuation of each outcome is based on an integrated value whereas combination of possible outcomes relies on a single piece of reward information. We show that differential weighting of possible outcomes enabled subjects to make decisions more easily and quickly. Together, these findings reveal a plausible mechanism for how salience, in terms of possible reward magnitude or probability, can influence the construction of subjective values for complex gambles. They also point to separable neural mechanisms for how reward value controls choice and attention in order to allow for more adaptive decision making.

Video conferencing software selection based on hybrid MCDM and cumulative prospect theory under a major epidemic

2021 ◽  
pp. 1-18
Author(s):  
Jie Xu ◽  
Jian Lv ◽  
Hong-Tai Yang ◽  
Yan-Lai Li
Keyword(s):  
Prospect Theory ◽  
Weighting Function ◽  
Video Conferencing ◽  
Cumulative Prospect Theory ◽  
Reference Points ◽  
Software Selection ◽  
Interval Numbers ◽  
The Matrix ◽  
Selection Decision ◽  
Gains And Losses

The video conferencing software is regarded as a significant tool for social distancing and getting incorporations up and going. Due to the indeterminacy of epidemic evolution and the multiple criteria, this paper proposes a video conferencing software selection method based on hybrid multi-criteria decision making (HMCDM) under risk and cumulative prospect theory (CPT), in which the criteria values are expressed in various mathematical forms (e.g., real numbers, interval numbers, and linguistic terms) and can be changed with natural states of the epidemic. Initially, the detailed description of video conferencing software selection problem under an epidemic are given. Subsequently, a whole procedure for video conferencing software selection is conducted, the approaches for processing and normalizing the multi-format evaluation values are presented. Furthermore, the expectations provided by DMs under different natural states of the epidemic are considered as the corresponding reference points (RP). Based on this, the matrix of gains and losses is constructed. Then, the prospect values of all criteria and the perceived probabilities of natural states are calculated according to the value function and the weighting function in CPT respectively. Finally, the proposed method is illustrated by an empirical case study, and the comparison analysis and the sensitivity analysis for the loss aversion parameter are conducted to prove the effectiveness and robustness. The results show that considering the psychological characteristics of DMs in selection decision is beneficial to avoid the unacceptable and potential loss risks. This study could provide a useful guideline for managers who intend to select appropriate video conferencing software.

scholarly journals A Novel TODIM with Probabilistic Hesitant Fuzzy Information and Its Application in Green Supplier Selection

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-26
Author(s):  
Xiaoli Tian ◽  
Meiling Niu ◽  
Jiangshui Ma ◽  
Zeshui Xu
Keyword(s):  
Weighting Function ◽  
Multiple Criteria Decision Making ◽  
Decision Makers ◽  
Sensitivity Analyses ◽  
Fuzzy Information ◽  
Probability Weighting Function ◽  
The Difference ◽  
The Stability ◽  
Gains And Losses

TODIM is a well-known multiple-criteria decision-making (MCDM) which considers the bounded rationality of decision makers (DMs) based on prospect theory (PT). However, in the classical TODIM, the perceived probability weighting function and the difference of the risk attitudes for gains and losses are not consistent with the original idea of PT. Moreover, probabilistic hesitant fuzzy information shows its superiority in handling the situation that the DMs hesitate among several possible values with different possibilities. Hence, a novel TODIM with probabilistic hesitant fuzzy information is proposed in this paper to simulate the perceptions of the DMs in PT. To show the advantages of the proposed method, a novel TODIM is combined with hesitant fuzzy information. Finally, a case study is carried out to demonstrate the feasibility of the proposed method, and a series of comparative analyses and the sensitivity analyses are used to show the stability of the proposed method.

scholarly journals Computational Models of Neuromodulation

1998 ◽  
Vol 10 (4) ◽  
pp. 771-805 ◽  
Author(s):  
Jean-Marc Fellous ◽  
Christiane Linster
Keyword(s):  
Sensory Processing ◽  
Information Integration ◽  
Computational Models ◽  
Neural Substrates ◽  
Pattern Generation ◽  
Neural Models ◽  
Functional Roles ◽  
Modeling Studies ◽  
And Control

Computational modeling of neural substrates provides an excellent theoretical framework for the understanding of the computational roles of neuromodulation. In this review, we illustrate, with a large number of modeling studies, the specific computations performed by neuromodulation in the context of various neural models of invertebrate and vertebrate preparations. We base our characterization of neuromodulations on their computational and functional roles rather than on anatomical or chemical criteria. We review the main framework in which neuromodulation has been studied theoretically (central pattern generation and oscillations, sensory processing, memory and information integration). Finally, we present a detailed mathematical overview of how neuromodulation has been implemented at the single cell and network levels in modeling studies. Overall, neuromodulation is found to increase and control computational complexity.

Information Transfer Between Rhythmically Coupled Networks: Reading the Hippocampal Phase Code

2001 ◽  
Vol 13 (12) ◽  
pp. 2743-2761 ◽  
Author(s):  
Ole Jensen
Keyword(s):  
Information Transfer ◽  
Computational Models ◽  
Brain Networks ◽  
Place Cells ◽  
Phase Code ◽  
Current Location ◽  
Coupled Networks ◽  
Plausible Mechanism ◽  
Theta Phase ◽  
Oscillatory Network

There are numerous reports on rhythmic coupling between separate brain networks. It has been proposed that this rhythmic coupling indicates exchange of information. So far, few computational models have been proposed that explore this principle and its potential computational benefits. Recent results on hippocampal place cells of the rat provide new insight; it has been shown that information about space is encoded by the firing of place cells with respect to the phase of the ongoing theta rhythm. This principle is termed phase coding and suggests that upcoming locations (predicted by the hippocampus) are encoded by cells firing late in the theta cycle, whereas current location is encoded by early firing in the theta cycle. A network reading the hippocampal output must inevitably also receive an oscillatory theta input in order to decipher the phase-coded firing patterns. In this article, I propose a simple physiologically plausible mechanism implemented as an oscillatory network that can decode the hippocampal output. By changing only the phase of the theta input to the decoder, qualitatively different information is transferred: the theta phase determines whether representations of current or upcoming locations are read by the decoder. The proposed mechanism provides a computational principle for information transfer between oscillatory networks and might generalize to brain networks beyond the hippocampal region.

Decision Models to Find a Promising Start-Up Firm with Qualiflex under Probabilistic Linguistic Circumstance

2019 ◽  
Vol 18 (04) ◽  
pp. 1379-1402 ◽  
Author(s):  
Xiaoli Tian ◽  
Zeshui Xu ◽  
Xinxin Wang ◽  
Jing Gu ◽  
Fawaz E. Alsaadi
Keyword(s):  
Decision Makers ◽  
Decision Models ◽  
Risk Attitudes ◽  
Multi Criteria Decision Making ◽  
Linguistic Information ◽  
Start Up ◽  
Decision Making Problem ◽  
Linguistic Term ◽  
Simulated Analysis ◽  
Gains And Losses

QUALIFLEX is a flexible method to solve the multi-criteria decision-making problem with a few alternatives. Moreover, the linguistic term is a very general way used by decision makers (DMs) to express their real perceptions. In particular, the probabilistic linguistic information, including the probability of each linguistic term, can simulate the vague perceptions of the DMs well. Therefore, the main contributions of this paper are constructing two novel QUALIFLEX with probabilistic linguistic information. First, based on the classical QUALIFLEX, it has been extended under probabilistic linguistic circumstance. Secondly, it is common for the DMs to have different risk attitudes for gains and losses when making their decisions under uncertainty, which is well explained by prospect theory (PT). Hence, PT has been integrated into the extended QUALIFLEX. Then, in this paper, a prospect QUALIFLEX is proposed as well. The feasibility and validity of the proposed methods have been verified by a numerical example in venture capital. The comparative and simulated analysis shows that the latter method with prospect framework is more appropriate than the former one because of the inherent psychological behaviors of the DMs and its excellent ability in identifying the similar alternatives. Furthermore, the ranking results derived from the prospect QUALIFLEX do not change with the different values of parameters. It reveals that the prospect QUALIFLEX is stable and reliable.

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