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

2020 ◽  
Author(s):  
Youna Vandaele ◽  
Magalie Lenoir ◽  
Caroline Vouillac-Mendoza ◽  
Karine Guillem ◽  
S.H. Ahmed
Keyword(s):  
Decision Making ◽  
Behavioral Ecology ◽  
Control Mechanism ◽  
Response Selection ◽  
Choice Model ◽  
Response Competition ◽  
Recent Effort ◽  
Response Latencies ◽  
Competition Mechanism ◽  
Choice Setting

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.

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
Keyword(s):  
Decision Making ◽  
Choice Behavior ◽  
Response Selection ◽  
Choice Model ◽  
Response Competition ◽  
Response Latencies ◽  
Competition Mechanism ◽  
Extended Training ◽  
Sequential Choice Model ◽  
Original Approach

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.

scholarly journals Pigeons show how meta-control enables decision-making in an ambiguous world

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Martina Manns ◽  
Tobias Otto ◽  
Laurenz Salm
Keyword(s):  
Decision Making ◽  
Response Selection ◽  
Hemispheric Dominance ◽  
Response Latencies ◽  
Response Options ◽  
Brain Hemispheres ◽  
Conflicting Information ◽  
Attention Focus ◽  
Conflict Situations ◽  
Encoding Strategies

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.

A Crime Decision-Making Model Based on AHP

2011 ◽  
Vol 50-51 ◽  
pp. 885-889 ◽  
Author(s):  
Fei Xue Yan ◽  
Jing Xia ◽  
Guan Qun Shen ◽  
Xu Sheng Kang
Keyword(s):  
Decision Making ◽  
Computer Simulation ◽  
Hazard Rate ◽  
Prediction Models ◽  
Choice Model ◽  
Ahp Method ◽  
Spatial Choice ◽  
Crime Prediction ◽  
Models Comparison ◽  
Decision Making Model

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.

scholarly journals Multi-route choice modelling in a metropolitan context: A comparative analysis using Multinomial Logit and Fuzzy Logic based approaches

2020 ◽  
Vol 79 (ET.2020) ◽  
pp. 1-17
Author(s):  
Sowjanya Dhulipala
Keyword(s):  
Decision Making ◽  
Fuzzy Logic ◽  
Choice Model ◽  
Route Choice ◽  
Fuzzy Rule ◽  
Multinomial Logit ◽  
Choice Modelling ◽  
Choice Behaviour ◽  
Linguistic Rules ◽  
Mnl Model

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.

Estimating Local Decision-Making Behavior in Complex Evolutionary Systems

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Zhenghui Sha ◽  
Jitesh H. Panchal
Keyword(s):  
Decision Making ◽  
Systems Engineering ◽  
Choice Model ◽  
Preferential Attachment ◽  
Network Evolution ◽  
System Structure ◽  
Statistical Regression ◽  
Evolutionary Systems ◽  
Local Decision ◽  
Local Decision Making

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.

An Approach for Assessing Demographic and Price Influences on Brand Purchase Behavior

1982 ◽  
Vol 46 (1) ◽  
pp. 36-46 ◽  
Author(s):  
J. Morgan Jones ◽  
Fred S. Zufryden
Keyword(s):  
Decision Making ◽  
Empirical Data ◽  
Choice Model ◽  
Brand Choice ◽  
Purchase Behavior ◽  
Explanatory Variables ◽  
Consumer Demographics ◽  
Marketing Decision

A new brand choice model that has the capacity to include explanatory variables is described and its use illustrated in an application to a particular brand. In this application, pricing and certain consumer demographics provide an explanation of the purchase behavior for the brand studied. The model provides a good fit to empirical data as well as some important insights for marketing decision making.

scholarly journals Operational decision-making for cyber operations: In Search of a Model

2019 ◽  
Author(s):  
Max Smeets ◽  
JD Work
Keyword(s):  
Decision Making ◽  
Complex Dynamics ◽  
Choice Model ◽  
Black Scholes Model ◽  
Black Scholes ◽  
Unique Nature ◽  
Operational Decision Making ◽  
Decision Dynamics ◽  
Mating Choice ◽  
Cyber Conflict

The decision-making behind cyber operations is complex. Dynamics around issues such as cyber arsenal management, target assessment, and the timing of dropping a destructive payload are still ill-understood. Yet, limited published research has thus far explored formal theoretic constructs for better understanding decisionmaking in cyber operations. Multiple models may offer utility to understand and explain the courses of action through which state cyber missions are executed, including conduct or restraint of cyber effects operations against target systems and networks. This paper evaluates four models - surprise model, duelist model, mating- choice model, and the Black-Scholes model. Each model offers specific advantages, and suffers characteristic drawbacks; and while these models differ in application and complexity each may provide insights into how the unique nature of cyber operations impact the decision dynamics of cyber conflict.

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