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Introduction

Decision-making under uncertainty is a complex cognitive process that plays a crucial role in everyday life. In various situations, individuals are required to make choices without having complete information about the potential outcomes or their probabilities. This uncertainty can arise due to factors such as ambiguity, incomplete information, or conflicting cues. Understanding the neural mechanisms that underlie decision-making under uncertainty is therefore essential for gaining insights into human behavior and decision-making processes.

This thesis aims to analyze the neural mechanisms underlying decision-making under uncertainty. By investigating how the brain processes uncertain information and makes decisions, we can gain a better understanding of the cognitive processes involved in decision-making. This research has implications for fields such as psychology, neuroscience, economics, and decision theory.

Chapter 1: Introduction
1.1 Introduction
1.2 Background of study
1.3 Problem Statement
1.4 Objective of study
1.5 Limitation of study
1.6 Scope of study
1.7 Significance of study
1.8 Structure of the Thesis
1.9 Definition of terms

Chapter 2: Literature Review
2.1 Introduction to decision-making under uncertainty
2.2 Neural mechanisms involved in decision-making
2.3 The role of uncertainty in decision-making
2.4 Computational models of decision-making under uncertainty
2.5 Neuroimaging studies on decision-making under uncertainty
2.6 Behavioral studies on decision-making under uncertainty
2.7 The impact of uncertainty on decision-making
2.8 Individual differences in decision-making under uncertainty
2.9 Neural correlates of risk-taking behavior
2.10 The neural basis of uncertainty processing

Chapter 3: Research Methodology
3.1 Research design
3.2 Participants
3.3 Procedures
3.4 Measures
3.5 Data analysis
3.6 Neuroimaging techniques
3.7 Experimental tasks
3.8 Statistical analyses

Chapter 4: Discussion of Findings
4.1 Neural mechanisms underlying decision-making under uncertainty
4.2 Behavioral correlates of decision-making under uncertainty
4.3 Individual differences in decision-making
4.4 Implications for decision theory
4.5 Comparison with existing models
4.6 Limitations of the study
4.7 Future directions for research
4.8 Practical applications of the findings

Chapter 5: Conclusion and Summary
5.1 Summary of findings
5.2 Contributions to the field
5.3 Recommendations for future research
5.4 Practical implications
5.5 Conclusion

Thesis Overview

Decision-making under uncertainty is a fundamental aspect of human cognition that influences various domains of life, including economics, psychology, and neuroscience. This thesis aims to investigate the neural mechanisms underlying decision-making under uncertainty by reviewing existing literature, conducting empirical research, and analyzing the findings to provide insights into cognitive processes involved in decision-making.

Chapter 1 provides an introduction to the topic, including the background of the study, problem statement, objectives, limitations, scope, significance, structure of the thesis, and definitions of key terms. Chapter 2 presents a comprehensive literature review on decision-making under uncertainty, including the neural mechanisms, computational models, neuroimaging studies, behavioral studies, individual differences, and the impact of uncertainty on decision-making.

Chapter 3 outlines the research methodology, including the research design, participant selection, procedures, measures, data analysis, neuroimaging techniques, experimental tasks, and statistical analyses. Chapter 4 discusses the findings of the study, including the neural mechanisms, behavioral correlates, individual differences, implications for decision theory, comparison with existing models, limitations, and future directions for research.

Chapter 5 concludes the thesis by summarizing the findings, discussing the contributions to the field, recommending future research directions, highlighting practical implications, and providing a conclusion. This thesis aims to contribute to the understanding of decision-making under uncertainty and its implications for various disciplines, providing valuable insights into human cognition and behavior.

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