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Related Concept Videos

Decision Making01:20

Decision Making

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...
Decision Making: P-value Method01:09

Decision Making: P-value Method

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 have a...
Reason and Intuition01:37

Reason and Intuition

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 brain can only use...
Timing and Consequences on Behavior01:08

Timing and Consequences on Behavior

In operant conditioning, the timing of reinforcement is crucial. For animals like rats and cats, immediate reinforcement (within a few seconds) is much more effective than delayed reinforcement. For example, a food reward for a rat needs to follow within 30 seconds of pressing a bar to be effective. 
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Decision Making: Traditional Method01:14

Decision Making: Traditional Method

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...
Optimal Arousal Theory01:23

Optimal Arousal Theory

The optimal arousal theory suggests that performance is maximized when an individual experiences a moderate level of arousal. This theory is closely tied to the Yerkes-Dodson law, which illustrates an inverted U-shaped relationship between arousal and performance. The law, formulated by psychologists Robert Yerkes and John Dodson, implies an ideal arousal level for optimal performance, and deviations from this level can lead to declines in effectiveness.
Inverted U-Shaped Performance Curve
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Related Experiment Video

Updated: May 31, 2026

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods
13:04

Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

Alpha and Theta Oscillations Differentiate Escalating Risk Levels During Reward Anticipation in Sequential Decision

Eszter Tóth-Fáber1, Andrea Kóbor1,2

  • 1Brain, Memory and Language Research Group, Institute of Cognitive Neuroscience and Psychology, HUN-REN Research Centre for Natural Sciences, Budapest, Hungary.

Psychophysiology
|May 29, 2026
PubMed
Summary

Brain oscillations reveal how risk and uncertainty influence reward anticipation during decision-making. Alpha and theta power changes track escalating risk, offering insights into neural dynamics guiding choices.

Keywords:
Balloon Analogue Risk Taskalpha powerambiguous decision makingreward anticipationtheta powertime–frequency analysis

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Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

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Last Updated: May 31, 2026

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Measuring the Subjective Value of Risky and Ambiguous Options using Experimental Economics and Functional MRI Methods

Published on: September 19, 2012

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Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents

Published on: September 10, 2018

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Decision Science

Background:

  • Reward anticipation is crucial for sequential decision-making.
  • Neural mechanisms underlying reward anticipation under varying risk and uncertainty are not fully understood.

Purpose of the Study:

  • To investigate how within-trial escalating risk and contextual uncertainty modulate oscillatory brain activity (EEG) during reward anticipation.
  • To elucidate the neural dynamics of decision-making under risk.

Main Methods:

  • Electroencephalography (EEG) was recorded from 44 participants performing a modified Balloon Analogue Risk Task.
  • Time-frequency decomposition (Morlet wavelets) analyzed spectral power, focusing on alpha and theta bands.
  • Analysis was time-locked to different within-trial risk levels (no-risk, high-risk successful, unsuccessful pumps).

Main Results:

  • Parieto-occipital alpha power increased after no-risk pumps, indicating reduced deliberation for certain rewards.
  • Centroparietal alpha suppression and frontocentral theta power decrease occurred after high-risk successful pumps, suggesting increased attention and reduced monitoring.
  • Theta power reduction was more pronounced with shallower burst probability functions, indicating modulation by contextual uncertainty.

Conclusions:

  • Both alpha and theta brain oscillations dynamically track escalating within-trial risk during reward anticipation.
  • Theta activity is further modulated by contextual uncertainty across different task phases.
  • These findings provide novel insights into the neural oscillatory mechanisms governing reward anticipation in sequential decision-making environments.