scholarly journals Probing the decision-making mechanisms underlying choice between drug and nondrug rewards in rats

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Youna Vandaele ◽  
Magalie Lenoir ◽  
Caroline Vouillac-Mendoza ◽  
Karine Guillem ◽  
Serge H Ahmed

Delineating the decision-making mechanisms underlying choice between drug and nondrug rewards remains a challenge. This study adopts an original approach to probe these mechanisms by comparing response latencies during sampling versus choice trials. While lengthening of latencies during choice is predicted in a deliberative choice model (DCM), the race-like response competition mechanism postulated by the Sequential choice model (SCM) predicts a shortening of latencies during choice compared to sampling. Here, we tested these predictions by conducting a retrospective analysis of cocaine-versus-saccharin choice experiments conducted in our laboratory. We found that rats engage deliberative decision-making mechanisms after limited training, but adopt a SCM-like response selection mechanism after more extended training, while their behavior is presumably habitual. Thus, the DCM and SCM may not be general models of choice, as initially formulated, but could be dynamically engaged to control choice behavior across early and extended training.

2020 ◽  
Author(s):  
Youna Vandaele ◽  
Magalie Lenoir ◽  
Caroline Vouillac-Mendoza ◽  
Karine Guillem ◽  
S.H. Ahmed

AbstractInvestigating the decision-making mechanisms underlying choice between drug and nondrug rewards is essential to understand how their alterations can contribute to substance use disorders. However, despite some recent effort, this investigation remains a challenge in a drug choice setting, notably when it comes to delineate the role of goal-directed versus habitual control mechanisms. The goal of this study was to try probing these different mechanisms by comparing response latencies measured during sampling (i.e., only one option is available) and choice trials. A deliberative goal-directed control mechanism predicts a lengthening of latencies during choice whereas a habitual control mechanism predicts no change in latencies. Alternatively, a race-like response competition mechanism, such as that postulated by the behavioral ecology-inspired Sequential Choice Model (SCM), predicts instead a shortening of response latencies during choice compared to sampling. Here we tested the predictions of these different mechanisms by conducting a systematic retrospective analysis of all cocaine versus saccharin choice experiments conducted in rats in our laboratory over the past 12 years. Overall, we found that rats engage a deliberative goal-directed mechanism after limited training, but shift to a SCM-like response selection mechanism after more extended training. The latter finding suggests that habitual control is engaged in a choice setting via a race-like response competition mechanism, and thus, that the SCM is not a general model of choice, as formulated initially, but a specific model of habitual choice.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Martina Manns ◽  
Tobias Otto ◽  
Laurenz Salm

AbstractIn situations where the left and right brain sides receive conflicting information that leads to incompatible response options, the brain requires efficient problem-solving mechanisms. This problem is particularly significant in lateralized brains, in which the hemispheres differ in encoding strategies or attention focus and hence, consider different information for decision-making. Meta-control, in which one hemisphere dominates ambiguous decisions, can be a mechanism that ensures fast behavioral reactions. We therefore confronted pigeons with a task in which two stimulus classes were brought into conflict. To this end, we trained pigeons simultaneously on two categories (cats or dogs) whereby each hemisphere learnt only one of the categories respectively. After learning, the birds were confronted with stimulus pairs that combined a picture with a cat (positive for one hemisphere) and a picture with a dog (positive for the other hemisphere). Pecking responses indicated the hemisphere dominating response selection. Pigeons displayed individual meta-control despite equal categorization performances of both brain hemispheres. This means that hemispheric dominance only emerged in interhemispheric conflict situations. The analysis of response latencies indicate that conflict decisions relied on intrahemispheric processes. Interhemispheric components played a role for more complex decisions. This flexibility could be a crucial building block for the evolutionary success of a lateralized brain.


Author(s):  
Robin Markwica

In coercive diplomacy, states threaten military action to persuade opponents to change their behavior. The goal is to achieve a target’s compliance without incurring the cost in blood and treasure of military intervention. Coercers typically employ this strategy toward weaker actors, but targets often refuse to submit and the parties enter into war. To explain these puzzling failures of coercive diplomacy, existing accounts generally refer to coercers’ perceived lack of resolve or targets’ social norms and identities. What these approaches either neglect or do not examine systematically is the role that emotions play in these encounters. The present book contends that target leaders’ affective experience can shape their decision-making in significant ways. Drawing on research in psychology and sociology, the study introduces an additional, emotion-based action model besides the traditional logics of consequences and appropriateness. This logic of affect, or emotional choice theory, posits that target leaders’ choice behavior is influenced by the dynamic interplay between their norms, identities, and five key emotions, namely fear, anger, hope, pride, and humiliation. The core of the action model consists of a series of propositions that specify the emotional conditions under which target leaders are likely to accept or reject a coercer’s demands. The book applies the logic of affect to Nikita Khrushchev’s decision-making during the Cuban missile crisis in 1962 and Saddam Hussein’s choice behavior in the Gulf conflict in 1990–91, offering a novel explanation for why coercive diplomacy succeeded in one case but not in the other.


2011 ◽  
Vol 50-51 ◽  
pp. 885-889 ◽  
Author(s):  
Fei Xue Yan ◽  
Jing Xia ◽  
Guan Qun Shen ◽  
Xu Sheng Kang

As time goes by, hazard rate of the society would increase if crime prediction was not implemented. Based on objective factors of offenders and victims characteristics, AHP method can be established to get a quantitative and qualitative analysis on crime prediction. Crime prediction is a strategic and tactical measure for crime prevention. According to AHP analysis, two prediction models of the optimal predictive crime locations are put forward. Standard Deviational Ellipses Model and Key Feature adjusted Spatial Choice Model were formulated to account for the anticipated position with various elements from AHP method. These models could be applied in a computer simulation of situation tests of the series murders. Besides, applying those models in certain real case demonstrates how the models work. Through models comparison, the results are summarized that Key Feature adjusted Spatial Choice Model is more conducive in confirming the guilty place. In conclusion, the suggested models, including detailed criminal map, are easy to implement.


2020 ◽  
Vol 79 (ET.2020) ◽  
pp. 1-17
Author(s):  
Sowjanya Dhulipala

Route choice plays a vital role in the traffic assignment and network building, as it involves decision making on part of riders. The vagueness in travellers’ perceptions of attributes of the available routes between any two locations adds to the complexities in modelling the route choice behaviour. Conventional Logit models fail to address the uncertainty in travellers’ perceptions of route characteristics (especially qualitative attributes, such as environmental effects), which can be better addressed through the theory of fuzzy sets and linguistic variables. This study thus attempts to model travellers’ route choice behaviour, using a fuzzy logic approach that is based on simple and logical ‘if-then’ linguistic rules. This approach takes into consideration the uncertainty in travellers’ perceptions of route characteristics, resembling humans’ decision-making process. Three attributes – travel time, traffic congestion, and road-side environment are adopted as factors driving people’s choice of routes, and three alternative routes between two typical locations in an Indian metropolitan city, Surat, are considered in the study. The approach to deal with multiple routes is shown by analyzing two-wheeler riders’ (e.g. motorcyclists’ and scooter drivers’) route choice behaviour during the peak-traffic time. Further, a Multinomial Logit (MNL) model is estimated, to enable a comparison of the two modelling approaches. The estimated Fuzzy Rule-Based Route Choice Model outperformed the conventional MNL model, accounting for the uncertain behaviour of travellers.


2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Zhenghui Sha ◽  
Jitesh H. Panchal

Research in systems engineering and design is increasingly focused on complex sociotechnical systems whose structures are not directly controlled by the designers, but evolve endogenously as a result of decisions and behaviors of self-directed entities. Examples of such systems include smart electric grids, Internet, smart transportation networks, and open source product development communities. To influence the structure and performance of such systems, it is crucial to understand the local decisions that result in observed system structures. This paper presents three approaches to estimate the local behaviors and preferences in complex evolutionary systems, modeled as networks, from its structure at different time steps. The first approach is based on the generalized preferential attachment model of network evolution. In the second approach, statistical regression-based models are used to estimate the local decision-making behaviors from consecutive snapshots of the system structure. In the third approach, the entities are modeled as rational decision-making agents who make linking decisions based on the maximization of their payoffs. Within the decision-centric framework, the multinomial logit choice model is adopted to estimate the preferences of decision-making nodes. The approaches are illustrated and compared using an example of the autonomous system (AS) level Internet. The approaches are generally applicable to a variety of complex systems that can be modeled as networks. The insights gained are expected to direct researchers in choosing the most applicable estimation approach to get the node-level behaviors in the context of different scenarios.


2003 ◽  
Vol 17 (1) ◽  
pp. 63-83 ◽  
Author(s):  
Patrick R. Wheeler ◽  
Donald R. Jones

Decision Support Systems (DSS) frequently have multiple decision aid (DA) features, causing users to engage in exclusive choice behavior; i.e., choice between alternative DA features that results in one feature being used to the exclusion of all others. We hypothesize that: (1) users choose the least effective (least accurate) DA feature in certain predictability environments; (2) users choose the DA feature that they believe they are most competent with; and (3) choice between DA features improves performance compared to those assigned the same DA feature. We test these hypotheses in an experiment in which 164 participants act as loan officers who chose between two decision aids (a database aid and a regression aid). The results support our hypotheses. Users employed a choice heuristic that caused them to choose the least effective DA feature for the task more than or as often as the most effective DA feature. Results also indicate a positive relationship between perceived competence and DA feature choice, and the positive effect of DA choice. We conclude by describing the insights provided by the results into the heuristics of information technology choice.


2020 ◽  
Vol 6 (45) ◽  
pp. eabc9321
Author(s):  
David J. Ottenheimer ◽  
Karen Wang ◽  
Xiao Tong ◽  
Kurt M. Fraser ◽  
Jocelyn M. Richard ◽  
...  

A key function of the nervous system is producing adaptive behavior across changing conditions, like physiological state. Although states like thirst and hunger are known to impact decision-making, the neurobiology of this phenomenon has been studied minimally. Here, we tracked evolving preference for sucrose and water as rats proceeded from a thirsty to sated state. As rats shifted from water choices to sucrose choices across the session, the activity of a majority of neurons in the ventral pallidum, a region crucial for reward-related behaviors, closely matched the evolving behavioral preference. The timing of this signal followed the pattern of a reward prediction error, occurring at the cue or the reward depending on when reward identity was revealed. Additionally, optogenetic stimulation of ventral pallidum neurons at the time of reward was able to reverse behavioral preference. Our results suggest that ventral pallidum neurons guide reward-related decisions across changing physiological states.


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