Institute of Neuroscience and Medicine – Cognitive Neuroscience (INM-3)

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1 to 6 of 6 Results

Spatial Cognition Dataverse(INM-3) Oct 10, 2024
Attention and Prediction Dataverse(INM-3) Oct 10, 2024
Replication Data for: Robustness of individualized inferences from longitudinal resting state EEG dynamics Mar 1, 2023 - Computational Neurology Dataverse Hommelsen, Max, 2023, "Replication Data for: Robustness of individualized inferences from longitudinal resting state EEG dynamics", https://doi.org/10.26165/JUELICH-DATA/PV2LY1, Jülich DATA, V1 This dataset contains EEG scalp recordings of 27 young healthy participants (11 female, 27.9 +- 3.4 years, 22-34 years). Scalp-EEG was acquired with a 64-channel active Ag/AgCl electrode system (actiCap, Brain Products, Germany) with a standard 10–20 spherical array layout (groun...
Dynamic Synchronization Toolbox May 11, 2022 - Computational Neurology Dataverse Rosjat, Nils, 2021, "Dynamic Synchronization Toolbox", https://doi.org/10.26165/JUELICH-DATA/BRXHZ9, Jülich DATA, V2 Implementation of generalized scripts as they were used for analysis of: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects", https://doi.org/10.26165/JUELICH-DATA/T1PKNZ, Jülich...
Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects Dec 9, 2020 - Computational Neurology Dataverse Rosjat, Nils; Wang, Bin A.; Liu, Liqing; Fink, Gereon R.; Daun, Silvia, 2020, "Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects", https://doi.org/10.26165/JUELICH-DATA/T1PKNZ, Jülich DATA, V1 Data description This dataset includes EEG recordings of 18 younger healthy subjects (18-35yrs) and 24 older healthy subjects (60+yrs) while they performed a visually cued finger tapping task. The task includes a visually-cued index finger tapping task and a vision-only control c...
Computational Neurology Dataverse(Forschungszentrum Jülich) Sep 10, 2020

Spatial Cognition Dataverse(INM-3)

Oct 10, 2024

Attention and Prediction Dataverse(INM-3)

Oct 10, 2024

Replication Data for: Robustness of individualized inferences from longitudinal resting state EEG dynamics

Mar 1, 2023 - Computational Neurology Dataverse

Hommelsen, Max, 2023, "Replication Data for: Robustness of individualized inferences from longitudinal resting state EEG dynamics", https://doi.org/10.26165/JUELICH-DATA/PV2LY1, Jülich DATA, V1

This dataset contains EEG scalp recordings of 27 young healthy participants (11 female, 27.9 +- 3.4 years, 22-34 years). Scalp-EEG was acquired with a 64-channel active Ag/AgCl electrode system (actiCap, Brain Products, Germany) with a standard 10–20 spherical array layout (groun...

Dynamic Synchronization Toolbox

May 11, 2022 - Computational Neurology Dataverse

Rosjat, Nils, 2021, "Dynamic Synchronization Toolbox", https://doi.org/10.26165/JUELICH-DATA/BRXHZ9, Jülich DATA, V2

Implementation of generalized scripts as they were used for analysis of: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects", https://doi.org/10.26165/JUELICH-DATA/T1PKNZ, Jülich...

Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects

Dec 9, 2020 - Computational Neurology Dataverse

Rosjat, Nils; Wang, Bin A.; Liu, Liqing; Fink, Gereon R.; Daun, Silvia, 2020, "Data for: Stimulus transformation into motor action: dynamic graph analysis reveals a posterior-to-anterior shift in brain network communication of older subjects", https://doi.org/10.26165/JUELICH-DATA/T1PKNZ, Jülich DATA, V1

Data description This dataset includes EEG recordings of 18 younger healthy subjects (18-35yrs) and 24 older healthy subjects (60+yrs) while they performed a visually cued finger tapping task. The task includes a visually-cued index finger tapping task and a vision-only control c...

Computational Neurology Dataverse(Forschungszentrum Jülich)

Sep 10, 2020

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