IRCCS.San Camillo Hospital
Published June 20, 2023 | Version v1
Dataset Open

The importance of ROI extraction method for MEG connectivity estimation. Practical recommendations for the study of resting state functional connectivity.

Creators

  • 1. 9.\tFaculty of Psychology and Educational Sciences, Department of Data Analysis, University of Ghent, Ghent, Belgium
  • 2. 8.\tCoAx Lab, Carnegie Mellon University, Pittsburgh, USA
  • 3. 3.\tMax Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
  • 4. 10.\tDepartment of Clinical Neurological Sciences, Western University, London, Ontario, Canada
  • 5. 7.\tPhilips, Milan, Italy
  • 6. 2.\tSuPerconducting and Other INnovative Materials and Devices Institute, Consiglio Nazionale delle Ricerche (CNR-SPIN), Genova, Italy
  • 7. 6.\tNext Lab, Campus Biomedico University of Rome, Rome, Italy 7.\tPhilips, Milan, Italy
  • 8. 4.\tIstituto per le Applicazioni del Calcolo \"M. Picone\", National Research Council, Via dei Taurini 19, 00185, Rome, Italy
  • 9. IRCCS San Camillo Hospital; Venice, Italy
  • 10. 5.\tCIMeC, University of Trento, Trento, Italy

Description

The zipped file contains all the t-maps of the contrasts across extraction methods, ROIs, frequency bands. Maps relative to different connectivity measurements are grouped in folders. Each folder also contains the .gii file for the reference cortex surface. You may use several softwares to visualize these maps. 

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If you wish to visualize the maps with Brainstorm:

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1) Go to Default Anatomy. Right Click -> Import surface. Select Group_analysis_cortex.gii.

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2) Go to the Group_analysis data folder (you should create one if not present). Go to Common Files. Right Click -> File -> Import Source Maps. Select the t-maps to be visualized.

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For any additional info, please get in touch with the corresponding author.

Files

t-maps.zip

Files (73.8 MB)

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md5:97e3753320006857483528062984ad86
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Additional details

Identifiers

DOI
10.15161/oar.it/77043

INFN OAR

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