scholarly journals Distinct temporal difference error signals in dopamine axons in three regions of the striatum in a decision-making task

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Iku Tsutsui-Kimura ◽  
Hideyuki Matsumoto ◽  
Korleki Akiti ◽  
Melissa M Yamada ◽  
Naoshige Uchida ◽  
...  
Keyword(s):  
Decision Making ◽  
Activity Level ◽  
Decision Task ◽  
Prediction Errors ◽  
Temporal Difference ◽  
Dorsolateral Striatum ◽  
Negative Prediction ◽  
Different Types

Different regions of the striatum regulate different types of behavior. However, how dopamine signals differ across striatal regions and how dopamine regulates different behaviors remain unclear. Here, we compared dopamine axon activity in the ventral, dorsomedial, and dorsolateral striatum, while mice performed a perceptual and value-based decision task. Surprisingly, dopamine axon activity was similar across all three areas. At a glance, the activity multiplexed different variables such as stimulus-associated values, confidence, and reward feedback at different phases of the task. Our modeling demonstrates, however, that these modulations can be inclusively explained by moment-by-moment changes in the expected reward, that is the temporal difference error. A major difference between areas was the overall activity level of reward responses: reward responses in dorsolateral striatum were positively shifted, lacking inhibitory responses to negative prediction errors. The differences in dopamine signals put specific constraints on the properties of behaviors controlled by dopamine in these regions.

scholarly journals Distinct temporal difference error signals in dopamine axons in three regions of the striatum in a decision-making task

2020 ◽  
Author(s):  
Iku Tsutsui-Kimura ◽  
Hideyuki Matsumoto ◽  
Naoshige Uchida ◽  
Mitsuko Watabe-Uchida
Keyword(s):  
Decision Making ◽  
Prediction Error ◽  
Activity Level ◽  
Decision Task ◽  
Temporal Difference ◽  
Dorsolateral Striatum ◽  
Negative Prediction ◽  
Different Types ◽  
Dopamine Signal

SUMMARYDifferent regions of the striatum regulate different types of behavior. However, how dopamine signals differ across striatal regions and how dopamine regulates different behaviors remain unclear. Here, we compared dopamine axon activity in the ventral, dorsomedial, and dorsolateral striatum, while mice performed in a perceptual and value-based decision task. Surprisingly, dopamine axon activity was similar across all three areas. At a glance, the activity multiplexed different variables such as stimulus-associated values, confidence and reward feedback at different phases of the task. Our modeling demonstrates, however, that these modulations can be inclusively explained by moment-by-moment changes in the expected reward, i.e. the temporal difference error. A major difference between these areas was the overall activity level of reward responses: reward responses in dorsolateral striatum (DLS) were positively shifted, lacking inhibitory responses to negative prediction error. Tenets of habit and skill can be explained by this positively biased dopamine signal in DLS.

Quota Women Are Threatening to Men

2017 ◽  
Vol 76 (3) ◽  
pp. 107-116 ◽  
Author(s):  
Klea Faniko ◽  
Till Burckhardt ◽  
Oriane Sarrasin ◽  
Fabio Lorenzi-Cioldi ◽  
Siri Øyslebø Sørensen ◽  
...  
Keyword(s):  
Decision Making ◽  
Organizational Performance ◽  
Gender Stereotypes ◽  
Perceived Threat ◽  
Preferential Treatment ◽  
Public Sector Employees ◽  
Different Types ◽  
Low Levels ◽  
Women In Decision Making ◽  
The Impact

Abstract. Two studies carried out among Albanian public-sector employees examined the impact of different types of affirmative action policies (AAPs) on (counter)stereotypical perceptions of women in decision-making positions. Study 1 (N = 178) revealed that participants – especially women – perceived women in decision-making positions as more masculine (i.e., agentic) than feminine (i.e., communal). Study 2 (N = 239) showed that different types of AA had different effects on the attribution of gender stereotypes to AAP beneficiaries: Women benefiting from a quota policy were perceived as being more communal than agentic, while those benefiting from weak preferential treatment were perceived as being more agentic than communal. Furthermore, we examined how the belief that AAPs threaten men’s access to decision-making positions influenced the attribution of these traits to AAP beneficiaries. The results showed that men who reported high levels of perceived threat, as compared to men who reported low levels of perceived threat, attributed more communal than agentic traits to the beneficiaries of quotas. These findings suggest that AAPs may have created a backlash against its beneficiaries by emphasizing gender-stereotypical or counterstereotypical traits. Thus, the framing of AAPs, for instance, as a matter of enhancing organizational performance, in the process of policy making and implementation, may be a crucial tool to countering potential backlash.

A Bird in the Hand Isn’t Good for Long

2018 ◽  
Vol 65 (1) ◽  
pp. 23-31 ◽  
Author(s):  
Stefan Scherbaum ◽  
Simon Frisch ◽  
Maja Dshemuchadse
Keyword(s):  
Decision Making ◽  
Cognitive Control ◽  
The Other ◽  
Decision Task ◽  
Short Term ◽  
Additional Time ◽  
Control Processes ◽  
Folk Wisdom ◽  
Study Participants ◽  
Insight Into

Abstract. Folk wisdom tells us that additional time to make a decision helps us to refrain from the first impulse to take the bird in the hand. However, the question why the time to decide plays an important role is still unanswered. Here we distinguish two explanations, one based on a bias in value accumulation that has to be overcome with time, the other based on cognitive control processes that need time to set in. In an intertemporal decision task, we use mouse tracking to study participants’ responses to options’ values and delays which were presented sequentially. We find that the information about options’ delays does indeed lead to an immediate bias that is controlled afterwards, matching the prediction of control processes needed to counter initial impulses. Hence, by using a dynamic measure, we provide insight into the processes underlying short-term oriented choices in intertemporal decision making.

Design, Development and Comparison of Heuristic Driven Algorithms Based on the Crossed Domain Products’ Reviews for User’s Summarization

2020 ◽  
Vol 13 (5) ◽  
pp. 884-892
Author(s):  
Sartaj Ahmad ◽  
Ashutosh Gupta ◽  
Neeraj Kumar Gupta
Keyword(s):  
Decision Making ◽  
Online Shopping ◽  
Recent Time ◽  
Design Development ◽  
Different Types ◽  
Feature Based ◽  
Use Of Internet ◽  
Day By Day ◽  
Better Than

Background: In recent time, people love online shopping but before any shopping feedbacks or reviews always required. These feedbacks help customers in decision making for buying any product or availing any service. In the country like India this trend of online shopping is increasing very rapidly because awareness and the use of internet which is increasing day by day. As result numbers of customers and their feedbacks are also increasing. It is creating a problem that how to read all reviews manually. So there should be some computerized mechanism that provides customers a summary without spending time in reading feedbacks. Besides big number of reviews another problem is that reviews are not structured. Objective: In this paper, we try to design, implement and compare two algorithms with manual approach for the crossed domain Product’s reviews. Methods: Lexicon based model is used and different types of reviews are tested and analyzed to check the performance of these algorithms. Results: Algorithm based on opinions and feature based opinions are designed, implemented, applied and compared with the manual results and it is found that algorithm # 2 is performing better than algorithm # 1 and near to manual results. Conclusion: Algorithm # 2 is found better on the different product’s reviews and still to be applied on other product’s reviews to enhance its scope. Finally, it will be helpful to automate existing manual process.

Deriving Effective Decision-Making Strategies of Prosthetists: Using Hidden Markov Modeling and Qualitative Analysis to Compare Experts and Novices

2021 ◽  
pp. 001872082110328
Author(s):  
Pratima Saravanan ◽  
Jessica Menold
Keyword(s):  
Decision Making ◽  
Qualitative Analysis ◽  
Clinical Decision Making ◽  
Hidden Markov ◽  
Activity Level ◽  
Markov Modeling ◽  
Support Tool ◽  
Case Complexity ◽  
Hidden Markov Modeling ◽  
Expert And Novice

Objective This research focuses on studying the clinical decision-making strategies of expert and novice prosthetists for different case complexities. Background With an increasing global amputee population, there is an urgent need for improved amputee care. However, current prosthetic prescription standards are based on subjective expertise, making the process challenging for novices, specifically during complex patient cases. Hence, there is a need for studying the decision-making strategies of prosthetists. Method An interactive web-based survey was developed with two case studies of varying complexities. Navigation between survey pages and time spent were recorded for 28 participants including experts ( n = 20) and novices ( n = 8). Using these data, decision-making strategies, or patterns of decisions, during prosthetic prescription were derived using hidden Markov modeling. A qualitative analysis of participants’ rationale regarding decisions was used to add a deep contextualized understanding of decision-making strategies derived from the quantitative analysis. Results Unique decision-making strategies were observed across expert and novice participants. Experts tended to focus on the personal details, activity level, and state of the residual limb prior to prescription, and this strategy was independent of case complexity. Novices tended to change strategies dependent upon case complexity, fixating on certain factors when case complexity was high. Conclusion The decision-making strategies of experts stayed the same across the two cases, whereas the novices exhibited mixed strategies. Application By modeling the decision-making strategies of experts and novices, this study builds a foundation for development of an automated decision-support tool for prosthetic prescription, advancing novice training, and amputee care.

Evaluating Risk-Propensity Assessment Methods: Patterns in Repeated Exposure to Emotional Stimuli

2020 ◽  
Vol 64 (1) ◽  
pp. 283-287
Author(s):  
Sahinya Susindar ◽  
Harrison Wissel-Littmann ◽  
Terry Ho ◽  
Thomas K. Ferris
Keyword(s):  
Decision Making ◽  
Emotion Regulation ◽  
Assessment Method ◽  
Decision Makers ◽  
Decision Task ◽  
Emotional States ◽  
Affective States ◽  
Risk Propensity ◽  
Emotional Stimuli ◽  
Comparison Results

In studying naturalistic human decision-making, it is important to understand how emotional states shape decision-making processes and outcomes. Emotion regulation techniques can improve the quality of decisions, but there are several challenges to evaluating these techniques in a controlled research context. Determining the effectiveness of emotion regulation techniques requires methodology that can: 1) reliably elicit desired emotions in decision-makers; 2) include decision tasks with response measures that are sensitive to emotional loading; and 3) support repeated exposures/trials with relatively-consistent emotional loading and response sensitivity. The current study investigates one common method, the Balloon Analog Risk Task (BART), for its consistency and reliability in measuring the risk-propensity of decision-makers, and specifically how the method’s effectiveness might change over the course of repeated exposures. With the PANASX subjective assessment serving for comparison, results suggest the BART assessment method, when applied over repeated exposures, is reduced in its sensitivity to emotional stimuli and exhibits decision task-related learning effects which influence the observed trends in response data in complex ways. This work is valuable for researchers in decision-making and to guide design for humans with consideration for their affective states.

scholarly journals Decision Making for Treatment After ACL Injury From an Orthopaedic Surgeon and Patient Perspective: Results From the NACOX Study

2021 ◽  
Vol 9 (4) ◽  
pp. 232596712110050
Author(s):  
Hanna Tigerstrand Grevnerts ◽  
Sofi Sonesson ◽  
Håkan Gauffin ◽  
Clare L. Ardern ◽  
Anders Stålman ◽  
...  
Keyword(s):  
Decision Making ◽  
High Activity ◽  
Treatment Decision ◽  
Acl Injury ◽  
Treatment Decisions ◽  
Activity Level ◽  
Knee Instability ◽  
Acl Injuries ◽  
Patient Reported ◽  
And Function

Background: In the treatment of anterior cruciate ligament (ACL) injuries, there is little evidence of when and why a decision for ACL reconstruction (ACLR) or nonoperative treatment (non-ACLR) is made. Purpose: To (1) describe the key characteristics of ACL injury treatment decisions and (2) compare patient-reported knee instability, function, and preinjury activity level between patients with non-ACLR and ACLR treatment decisions. Study Design: Cohort study; Level of evidence, 2. Methods: A total of 216 patients with acute ACL injury were evaluated during the first year after injury. The treatment decision was non-ACLR in 73 patients and ACLR in 143. Reasons guiding treatment decision were obtained from medical charts and questionnaires to patients and orthopaedic surgeons. Patient-reported instability and function were obtained via questionnaires and compared between patients with non-ACLR and ACLR treatment decisions. The ACLR treatment group was classified retrospectively by decision phase: acute phase (decision made between injury day and 31 days after injury), subacute phase (decision made between 32 days and up to 5 months after injury), and late phase (decision made 5-12 months after injury). Data were evaluated using descriptive statistics, and group comparisons were made using parametric or nonparametric tests as appropriate. Results: The main reasons for a non-ACLR treatment decision were no knee instability and no problems with knee function. The main reasons for an ACLR treatment decision were high activity demands and knee instability. Patients in the non-ACLR group were significantly older ( P = .031) and had a lower preinjury activity level than did those in the acute-phase ( P < .01) and subacute-phase ( P = .006) ACLR decision groups. There were no differences in patient-reported instability and function between treatment decision groups at baseline, 4 weeks after injury, or 3 months after injury. Conclusion: Activity demands, not patient-reported knee instability, may be the most important factor in the decision-making process for treatment after ACL injury. We suggest a decision-making algorithm for patients with ACL injuries and no high activity demands; waiting for >3 months can help distinguish those who need surgical intervention from those who can undergo nonoperative management. Registration: NCT02931084 ( ClinicalTrials.gov identifier).

An algebraic approach to N-soft sets with application in decision-making using TOPSIS

2021 ◽  
pp. 1-21
Author(s):  
Muhammad Shabir ◽  
Rimsha Mushtaq ◽  
Munazza Naz
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Real World ◽  
Algebraic Approach ◽  
Multi Criteria Decision Making ◽  
Commutative Monoids ◽  
Soft Sets ◽  
Algebraic Properties ◽  
Different Types ◽  
Selection Of

In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop.

scholarly journals Active Inference: Applicability to Different Types of Social Organization Explained through Reference to Industrial Engineering and Quality Management

Entropy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 198
Author(s):  
Stephen Fox
Keyword(s):  
Artificial Intelligence ◽  
Quality Management ◽  
Social Organization ◽  
Generative Models ◽  
Industrial Engineering ◽  
Prediction Errors ◽  
Active Inference ◽  
For Profit ◽  
Different Types ◽  
Inference Theory

Active inference is a physics of life process theory of perception, action and learning that is applicable to natural and artificial agents. In this paper, active inference theory is related to different types of practice in social organization. Here, the term social organization is used to clarify that this paper does not encompass organization in biological systems. Rather, the paper addresses active inference in social organization that utilizes industrial engineering, quality management, and artificial intelligence alongside human intelligence. Social organization referred to in this paper can be in private companies, public institutions, other for-profit or not-for-profit organizations, and any combination of them. The relevance of active inference theory is explained in terms of variational free energy, prediction errors, generative models, and Markov blankets. Active inference theory is most relevant to the social organization of work that is highly repetitive. By contrast, there are more challenges involved in applying active inference theory for social organization of less repetitive endeavors such as one-of-a-kind projects. These challenges need to be addressed in order for active inference to provide a unifying framework for different types of social organization employing human and artificial intelligence.

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