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Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...
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Decision Making01:20

Decision Making

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Decision-making is a fundamental cognitive process that involves evaluating alternatives and selecting among them. This process can range from simple choices, such as deciding what to wear, to complex decisions, like choosing a major in college or a career path. The complexity of the decision often dictates the approach we use, which can be broadly categorized into two types: automatic and controlled decision-making.
Automatic decision-making is fast, intuitive, and relies on gut feelings...
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Reason and Intuition01:37

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The human brain processes information for decision-making using one of two routes: an intuitive system and a rational system (Epstein, 1994; popularized by Kahneman, 2011 as System 1 and System 2, respectively). The intuitive system is quick, impulsive, and operates with minimal effort, relying on emotions or habits to provide cues for what to do next, while the rational system is logical, analytical, deliberate, and methodical. Research in neuropsychology suggests that the...
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Decision Making: P-value Method01:09

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The process of hypothesis testing based on the P-value method includes calculating the P- value using the sample data and interpreting it.
First, a specific claim about the population parameter is proposed. The claim is based on the research question and is stated in a simple form. Further, an opposing statement to the claim  is also stated. These statements can act as null and alternative hypotheses:  a null hypothesis would be a neutral statement while the alternative hypothesis can...
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Relationship Formation02:12

Relationship Formation

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What do you think is the single most influential factor in determining with whom you become friends and whom you form romantic relationships? You might be surprised to learn that the answer is simple: the people with whom you have the most contact. This most important factor is proximity. You are more likely to be friends with people you have regular contact with. For example, there are decades of research that shows that you are more likely to become friends with people who live in your dorm,...
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Levels of Communication II: Organizational, Public, and Group Dynamics01:27

Levels of Communication II: Organizational, Public, and Group Dynamics

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Effective communication is the foundation of a good organization. Communication is the lifeblood of an organization that connects the group with messages. In an organization, communication occurs in upward, downward, and horizontal lines. Downward communication travels from the administrative and senior levels to the staff through official channels such as manuals, rules and regulations, and organizational charts. Staff members initiate upward communication, which is addressed to executives and...
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Related Experiment Video

Updated: Mar 21, 2026

The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies
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The Joint Effect of Social Comparison and Social Distance on Evaluation of Intertemporal Choice Outcomes in Event-related Potential Studies

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Tuning the Brake While Raising the Stake: Network Dynamics during Sequential Decision-Making.

David Meder1, Brian Numelin Haagensen1, Oliver Hulme1

  • 1Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital Hvidovre, Hvidovre, 2650, Denmark.

The Journal of Neuroscience : the Official Journal of the Society for Neuroscience
|May 13, 2016
PubMed
Summary

The human brain balances escalating reward and risk using a "braking" network, including the subthalamic nucleus (STN) and pre-SMA. Dorsal anterior cingulate cortex (ACC) activity reflects choice tendencies, not uncertainty, during sequential decisions.

Keywords:
ACCaction selectionconflictinhibitionpre-SMA

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Area of Science:

  • Neuroscience
  • Cognitive Science
  • Decision Science

Background:

  • Sequential decision-making involves balancing escalating reward with increasing risk.
  • Understanding the neural mechanisms of risk-reward tradeoffs is crucial for explaining behaviors like foraging, trading, and gambling.

Purpose of the Study:

  • To investigate how the human brain dynamically computes tradeoffs between escalating reward and risk during sequential decision-making.
  • To identify specific brain regions and networks involved in this computation and their relation to risk attitudes and choice uncertainty.

Main Methods:

  • Whole-brain functional magnetic resonance imaging (fMRI) was used while healthy young adults performed a sequential gambling task.
  • Participants chose between continuing to gamble for higher rewards under escalating risk or stopping to bank their current winnings.
  • Reaction times and neural activity were analyzed in relation to accumulated gains and risk levels.

Main Results:

  • Increased reaction times for 'continue' choices indicated growing decision uncertainty as gains accumulated.
  • Neural activity in a cortico-subcortical 'braking' network (pre-SMA, inferior frontal gyrus, caudate, STN) scaled with accumulated gains.
  • Subthalamic nucleus (STN) influence on pre-SMA activity predicted individual risk aversion.
  • Dorsal anterior cingulate cortex (ACC) activity reflected non-default choice tendencies rather than subjective choice uncertainty.

Conclusions:

  • A cortico-subcortical 'braking' network, including the STN and pre-SMA, plays a key role in managing escalating reward and risk.
  • The dorsal ACC is involved in reflecting choice tendencies during sequential decision-making, independent of choice uncertainty.
  • These findings elucidate the neural basis of dynamic risk-reward computations in the human brain.