PGAM on High Performance Computing: Efficient estimation of neural tuning during naturalistic behavior

Balzani, Edoardo

doi:10.17605/OSF.IO/PCSAV

Title	Authors

PGAM on High Performance Computing: Efficient estimation of neural tuning during naturalistic behavior

Contributors:

Edoardo Balzani

Date created: | Last Updated:

: DOI | ARK

Creating DOI. Please wait...

Create DOI

Category: Project

Description: Singularity image for PGAM, a statistical framework for characterizing tuning functions and selectivity of neural responses to many task-relevant covariates.

Projects
Registrations

Results: All Projects Results: My Projects Results: All Registrations Results: My Registrations

Wiki

Add important information, links, or images here to describe your project.

Files

Files can now be accessed and managed under the Files tab.

Citation

Recent Activity

Loading logs...

OSF does not support the use of Internet Explorer. For optimal performance, please switch to another browser.

This website relies on cookies to help provide a better user experience. By clicking Accept or continuing to use the site, you agree. For more information, see our Privacy Policy and information on cookie use.

Start managing your projects on the OSF today.

Free and easy to use, the Open Science Framework supports the entire research lifecycle: planning, execution, reporting, archiving, and discovery.

Create an Account Learn More Hide this message

Main content

Links to this project

PGAM on High Performance Computing: Efficient estimation of neural tuning during naturalistic behavior

Link other OSF projects

Wiki

Files

Citation

Recent Activity

Start managing your projects on the OSF today.