Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Decision Making: P-value Method01:09

Decision Making: P-value Method

5.3K
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...
5.3K
Decision Making01:20

Decision Making

110
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...
110
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

4.0K
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...
4.0K
The Anchoring-and-Adjustment Heuristic01:25

The Anchoring-and-Adjustment Heuristic

7.2K
In order to make good decisions, we use our knowledge and our reasoning. Often, this knowledge and reasoning is sound and solid. However, sometimes, we are swayed by biases or by others manipulating a situation. For example, let’s say you and three friends wanted to rent a house and had a combined target budget of $1,600. The realtor shows you only very run-down houses for $1,600 and then shows you a very nice house for $2,000. Might you ask each person to pay more in rent to get the...
7.2K
The Availability Heuristic01:08

The Availability Heuristic

6.0K
A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
6.0K
Reason and Intuition01:37

Reason and Intuition

6.5K
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...
6.5K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

GABAergic neurons in medial prefrontal cortex and ventral hippocampus encode information about reward history in male mice.

Cell reports·2026
Same author

Decoherence via Demyelination Hypothesis (DDH): A Mechanism of Cognitive Decline During Aging.

bioRxiv : the preprint server for biology·2026
Same author

Internal state dynamically gates task-specific attractor dynamics in prefrontal cortex.

bioRxiv : the preprint server for biology·2026
Same author

AI-Discovered Cognitive Models Reveal Novel Insights into Human and Animal Learning.

bioRxiv : the preprint server for biology·2026
Same author

Developmental Change in Structure Learning Reflects a Shift From Recency-Based to Relational Prediction.

Developmental science·2026
Same author

Persistent decision-making in mice, monkeys and humans.

Proceedings. Biological sciences·2026
Same journal

Co-option of lysosomal machinery shapes the evolution of the intracellular photosymbiosis supporting coral reefs.

Cell·2026
Same journal

LEF1 and niche factors determine T cell stemness across chronic diseases.

Cell·2026
Same journal

Recurrent patterns of TOP1-mediated neuronal genomic damage shared by major neurodegenerative disorders.

Cell·2026
Same journal

Four-dimensional molecular mapping from a spatial snapshot reveals the dynamics of hair follicle organogenesis.

Cell·2026
Same journal

Whole-cell particle-based digital twin simulations from 4D lattice light-sheet microscopy data.

Cell·2026
Same journal

Systematic discovery of pathogen effector functions across human pathogens and pathways.

Cell·2026
See all related articles

Related Experiment Video

Updated: Jul 2, 2025

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients
05:48

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients

Published on: June 12, 2020

5.7K

Learning attentional templates for value-based decision-making.

Caroline I Jahn1, Nikola T Markov1, Britney Morea1

  • 1Princeton Neuroscience Institute, Princeton University, Princeton, NJ 08540, USA.

Cell
|February 24, 2024
PubMed
Summary
This summary is machine-generated.

The brain learns new attentional templates by adjusting neural representations in the prefrontal and parietal cortex. These templates enable flexible attention deployment across tasks by transforming stimulus features into a common value.

Keywords:
attentioncognitive controldecision-makingparietal cortexprefrontal cortexreinforcement learningreward learningvisual search

More Related Videos

Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

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

Published on: September 10, 2018

6.0K
Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model
06:30

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Published on: May 24, 2019

5.3K

Related Experiment Videos

Last Updated: Jul 2, 2025

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients
05:48

The Adventures of Fundi Intervention Based on the Cognitive and Emotional Processing in Attention Deficit Hyperactive Disorder Patients

Published on: June 12, 2020

5.7K
Operant Protocols for Assessing the Cost-benefit Analysis During Reinforced Decision Making by Rodents
07:05

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

Published on: September 10, 2018

6.0K
Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model
06:30

Spotlighting Customers' Visual Attention at the Stock, Shelf and Store Levels with the 3S Model

Published on: May 24, 2019

5.3K

Area of Science:

  • Neuroscience
  • Cognitive Science
  • Computational Neuroscience

Background:

  • Attention selectively filters sensory information to prioritize task-relevant stimuli.
  • Attentional control relies on internal "attentional templates" representing currently relevant stimulus features.

Purpose of the Study:

  • To investigate the neural mechanisms underlying the learning and flexible deployment of attentional templates.
  • To understand how the brain adapts to new attentional demands.

Main Methods:

  • Monkeys were trained on a visual search task requiring repeated learning of new attentional templates.
  • Neural recordings were used to analyze template representations in the prefrontal and parietal cortex.

Main Results:

  • Attentional templates are represented in a structured manner across the prefrontal and parietal cortex, with similar representations for perceptually neighboring templates.
  • Learning new templates involved incremental shifts toward rewarded features.
  • Templates transform stimulus features into a common value representation for decision-making.

Conclusions:

  • The findings reveal how the brain learns to control attention through structured neural representations.
  • Attentional templates facilitate flexible attention deployment by creating a unified value signal.
  • This research provides insights into the neural basis of adaptive attentional control.