scholarly journals Extracting the Dynamics of Behavior in Decision-Making Experiments

2020 ◽  
Author(s):  
Nicholas A. Roy ◽  
Ji Hyun Bak ◽  
Athena Akrami ◽  
Carlos D. Brody ◽  
Jonathan W. Pillow ◽  
...  
Keyword(s):  
Decision Making ◽  
Visual Detection ◽  
Human Subjects ◽  
Optimal Strategies ◽  
Training Data ◽  
Experimental Population ◽  
Time Varying ◽  
Behavioral Dynamics ◽  
Task Irrelevant ◽  
Decision Making Behavior

AbstractUnderstanding how animals update their decision-making behavior over time is an important problem in neuroscience. Decision-making strategies evolve over the course of learning, and continue to vary even in well-trained animals. However, the standard suite of behavioral analysis tools is ill-equipped to capture the dynamics of these strategies. Here, we present a flexible method for characterizing time-varying behavior during decision-making experiments. We show that it successfully captures trial-to-trial changes in an animal’s sensitivity to not only task-relevant stimuli, but also task-irrelevant covariates such as choice, reward, and stimulus history. We use this method to derive insights from training data collected in mice, rats, and human subjects performing auditory discrimination and visual detection tasks. With this approach, we uncover the detailed evolution of an animal’s strategy during learning, including adaptation to time-varying task statistics, suppression of sub-optimal strategies, and shared behavioral dynamics between subjects within an experimental population.

Torus Destruction and Chaos–Chaos Intermittency in a Commodity Distribution Chain

1997 ◽  
Vol 07 (06) ◽  
pp. 1225-1242 ◽  
Author(s):  
O. Sosnovtseva ◽  
E. Mosekilde
Keyword(s):  
Decision Making ◽  
Human Subjects ◽  
Distribution Model ◽  
High Dimensional ◽  
Two Dimensional ◽  
Dimensional Model ◽  
Production Distribution ◽  
Distribution Chain ◽  
Beer Production ◽  
Decision Making Behavior

The destruction of two-dimensional tori T2 and the transitions to chaos are studied numerically in a high-dimensional model describing the decision making behavior of human subjects in a simulated managerial environment (the beer production-distribution model). Two different routes from quasiperiodicity to chaos can be distinguished. Intermittency transitions between chaotic and hyperchaotic attractors are characterized, and transients in which the "system pursues the ghost" of a vanished hyperchaotic attractor are studied.

scholarly journals Deep Learning-Based Differentiation between Mucinous Cystic Neoplasm and Serous Cystic Neoplasm in the Pancreas Using Endoscopic Ultrasonography

Diagnostics ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1052
Author(s):  
Leang Sim Nguon ◽  
Kangwon Seo ◽  
Jung-Hyun Lim ◽  
Tae-Jun Song ◽  
Sung-Hyun Cho ◽  
...  
Keyword(s):  
Decision Making ◽  
Deep Learning ◽  
Network Model ◽  
Endoscopic Ultrasonography ◽  
Data Augmentation ◽  
Clinical Information ◽  
Training Data ◽  
Fine Tuning ◽  
Cystic Neoplasm ◽  
Cystic Neoplasms

Mucinous cystic neoplasms (MCN) and serous cystic neoplasms (SCN) account for a large portion of solitary pancreatic cystic neoplasms (PCN). In this study we implemented a convolutional neural network (CNN) model using ResNet50 to differentiate between MCN and SCN. The training data were collected retrospectively from 59 MCN and 49 SCN patients from two different hospitals. Data augmentation was used to enhance the size and quality of training datasets. Fine-tuning training approaches were utilized by adopting the pre-trained model from transfer learning while training selected layers. Testing of the network was conducted by varying the endoscopic ultrasonography (EUS) image sizes and positions to evaluate the network performance for differentiation. The proposed network model achieved up to 82.75% accuracy and a 0.88 (95% CI: 0.817–0.930) area under curve (AUC) score. The performance of the implemented deep learning networks in decision-making using only EUS images is comparable to that of traditional manual decision-making using EUS images along with supporting clinical information. Gradient-weighted class activation mapping (Grad-CAM) confirmed that the network model learned the features from the cyst region accurately. This study proves the feasibility of diagnosing MCN and SCN using a deep learning network model. Further improvement using more datasets is needed.

scholarly journals Survival or Mortality: Does Risk Attribute Framing Influence Decision-Making Behavior in a Discrete Choice Experiment?

2016 ◽  
Vol 19 (2) ◽  
pp. 202-209 ◽  
Author(s):  
Jorien Veldwijk ◽  
Brigitte A.B. Essers ◽  
Mattijs S. Lambooij ◽  
Carmen D. Dirksen ◽  
Henriette A. Smit ◽  
...  
Keyword(s):  
Decision Making ◽  
Discrete Choice Experiment ◽  
Discrete Choice ◽  
Choice Experiment ◽  
Decision Making Behavior

scholarly journals Phasic Nucleus Accumbens Dopamine Encodes Risk-Based Decision-Making Behavior

2012 ◽  
Vol 71 (3) ◽  
pp. 199-205 ◽  
Author(s):  
Jonathan A. Sugam ◽  
Jeremy J. Day ◽  
R. Mark Wightman ◽  
Regina M. Carelli
Keyword(s):  
Decision Making ◽  
Nucleus Accumbens ◽  
Decision Making Behavior

Developing a Systematic Decision-Making Framework: Bureaucratic Politics in Perspective

1981 ◽  
Vol 33 (2) ◽  
pp. 234-252 ◽  
Author(s):  
Jerel A. Rosati
Keyword(s):  
Decision Making ◽  
Policy Making ◽  
Executive Branch ◽  
Bureaucratic Politics ◽  
Theory Building ◽  
Decision Making Process ◽  
Decision Context ◽  
Policy Application ◽  
Decision Making Framework ◽  
Decision Making Behavior

The bureaucratic politics model has achieved great popularity in the study of decision making. Yet too often the term “bureaucratic politics” is used by scholars and practitioners without clearly stating its policy application. The decision-making behavior that occurred during the Johnson and Nixon administrations for SALT I serves to illustrate many of the limits of the model. First, the decision-making structure posited by the bureaucratic politics model is not nearly as prevalent within the executive branch as is commonly assumed. Second, even where the bureaucratic politics structure is present, the decision-making process is not always one of bargaining, compromise, and consensus. Finally, the decision context and the decision participants are ignored in the model. To provide a clearer understanding of policy-making behavior, a more systematic decision-making framework is offered, which should contribute to the development of better model- and theory-building.

scholarly journals Characterization of Kentucky dairy producer decision-making behavior

2013 ◽  
Vol 96 (7) ◽  
pp. 4751-4758 ◽  
Author(s):  
R.A. Russell ◽  
J.M. Bewley
Keyword(s):  
Decision Making ◽  
Decision Making Behavior

Operation decision of logistics service supply chain: considering interruption probability in emergencies

Kybernetes ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Guangsheng Zhang ◽  
Xiao Wang ◽  
Zhiqing Meng ◽  
Qirui Zhang ◽  
Kexin Wu
Keyword(s):  
Decision Making ◽  
Supply Chain ◽  
Evolutionary Game ◽  
Optimal Strategies ◽  
Optimal Decision ◽  
Content Type ◽  
Logistics Service ◽  
Social Reputation ◽  
Punishment Intensity ◽  
Optimal Decision Making

PurposeTo remedy the inherent defect in current research that focuses only on a single type of participants, this paper endeavors to look into the situation as an evolutionary game between a representative Logistics Service Integrator (LSI) and a representative Functional Logistics Service Provider (FLSP) in an environment with sudden crisis and tries to analyze how LSI supervises FLSP's operations and how FLSP responds in a recurrent pattern with different interruption probabilities.Design/methodology/approachRegarding the risks of supply chain interruption in emergencies, this paper develops a two-level model of single LSI and single FLSP, using Evolutionary Game theory to analyze their optimal decision-making, as well as their strategic behaviors on different risk levels regarding the interruption probability to achieve the optimal return with bounded rationality.FindingsThe results show that on a low-risk level, if LSI increases the degree of punishment, it will fail to enhance FLSP's operational activeness in the long term; when the risk rises to an intermediate level, a circular game occurs between LSI and FLSP; and on a high level of risk, FLSP will actively take actions, and its functional probability further impacts LSI's strategic choices. Finally, this paper analyzes the moderating impact of punishment intensity and social reputation loss on the evolutionary model in emergencies and provides relevant managerial implications.Originality/valueFirst, by taking both interruption probability and emergencies into consideration, this paper explores the interactions among the factors relevant to LSI's and FLSP's optimal decision-making. Second, this paper analyzes the optimal evolutionary game strategies of LSI and FLSP with different interruption probability and the range of their optimal strategies. Third, the findings of this paper provide valuable implications for relevant practices, such that the punishment intensity and social reputation loss determine the optimal strategies of LSI and FLSP, and thus it is an effective vehicle for LSSC system administrator to achieve the maximum efficiency of the system.

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