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Related Concept Videos

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

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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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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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Related Experiment Video

Updated: Aug 30, 2025

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions
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Reproducing a decision-making network in a virtual visual discrimination task.

Alessandra Trapani1, Francesco Jamal Sheiban1, Elisa Bertone1

  • 1NearLab, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milan, Italy.

Frontiers in Integrative Neuroscience
|August 29, 2022
PubMed
Summary
This summary is machine-generated.

Researchers replicated a decision-making network model in a virtual robot using NEST simulation software. This work ensures replicability in neuroscience, successfully reproducing neural processes for binary decisions and controlling a robot in a visual task.

Keywords:
NESTdecision-makingnetwork modelneurorobotreproducibilityworking memory

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Area of Science:

  • Computational Neuroscience
  • Robotics
  • Neuroscience

Background:

  • Replicability is crucial for scientific progress in neuroscience.
  • Existing computational models require validation across different software platforms.
  • Simulated robotic agents offer a platform for testing neural network models.

Purpose of the Study:

  • To reproduce a spiking neural network decision-making model using the NEST simulator.
  • To validate the model's computational properties and decision-making capabilities.
  • To integrate the model into a virtual robotic agent for behavioral tasks.

Main Methods:

  • Utilized the NEST (Neural Simulation Tool) software.
  • Embedded a spiking neural network into a virtual robotic agent.
  • Developed a simulated visual discrimination task for the agent.

Main Results:

  • Successfully reproduced the original model's results and key features of neural processes for binary decisions.
  • The implemented network effectively controlled the virtual robot in the simulated task.
  • The implementation is openly available on the EBRAINS neuro-robotics platform (NRP).

Conclusions:

  • The study demonstrates successful replication of a decision-making network model using a different software tool.
  • The validated model can control robotic agents in simulated cognitive tasks.
  • Open availability on EBRAINS promotes further research in computational neuroscience and neuro-robotics.