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communicationsurprise_datacode

https://github.com/tatiabu/communicationsurprise_datacode

Science Score: 13.0%

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    Low similarity (12.9%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

Basic Info
  • Host: GitHub
  • Owner: TatiaBu
  • Language: MATLAB
  • Default Branch: main
  • Size: 72.6 MB
Statistics
  • Stars: 1
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 1
Created almost 2 years ago · Last pushed about 1 year ago
Metadata Files
Readme Citation

README.md

CommunicationSurprise_DataCode

Welcome to the CommunicationSurprise_DataCode repository. This repository is dedicated to storing the data and code that support the analyses and figures featured in our recent manuscript on Expectation Violations Signal Goals in Novel Human Communication. Each folder contains specific parts of the work, as outlined below.

Repository Contents

  • Comparative Evaluation of Model Performances/ - Contains scripts and data for evaluating the performance of different models as discussed in the manuscript.

  • Model-based PDR Analysis/ - Here, you'll find the code and datasets used for Pupillary Dilation Response (PDR) analysis based on our models.

  • Model-based EEG Analysis/ - This folder houses the scripts and datasets for Electroencephalogram (EEG) analysis performed using our computational models.

  • Participants-generated and Model-simulated .../ - This directory encompasses the datasets generated by the participants in the study, alongside the datasets simulated by our computational models. Additionally, it includes scripts for visualizing the messages communicated during the study, providing a visual representation of the communication patterns and any surprising elements observed.

  • manuscript figures/ - Includes high-resolution versions of the figures that are incorporated into the manuscript.

How to Use This Repository

To use the scripts and data provided:

  1. Clone the repository to your local machine.
  2. Navigate to the folder of interest.
  3. Detailed instructions are provided within a folder, refer to the specific README within that directory for guidance.

Software Requirements

The majority of scripts are designed to run on MATLAB. It is advisable to ensure you have a compatible version of MATLAB installed. Model-based PDR analysis and Bayesian factor analyssi require R.

Contributions and Issues

Feel free to suggest improvements or report issues by opening a new issue on the GitHub repository page. We welcome contributions and ask that you provide a detailed description of your proposed changes and the reasons for them.

Contact

For any additional questions or comments regarding this repository, please open an issue, and we will respond as promptly as possible.Contact email: ta.buidze@uke.de

Owner

  • Name: Tatia Buidze
  • Login: TatiaBu
  • Kind: user
  • Company: Univercity Medical Center Eppendorf (UKE) , Institute of systems neuroscience (ISN)

GitHub Events

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  • Release event: 1
  • Push event: 4
  • Create event: 1
Last Year
  • Release event: 1
  • Push event: 4
  • Create event: 1