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2026
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English
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- Description:
- The provided Bash scripts are used to convert raw magnetic resonance imaging (Magnetic Resonance Imaging, MRI) data from the Digital Imaging and Communications in Medicine (DICOM) standard format into a Brain Imaging Data Structure (BIDS)-compliant dataset. The scripts convert DICOM files into the Neuroimaging Informatics Technology Initiative (NIfTI) format, which can be used for preprocessing MRI data. In addition to the NIfTI files, the conversion also generates the metadata required by the BIDS standard. Dataset quality and compliance can be checked using a BIDS validator (e.g., https://bids-standard.github.io/bids-validator/). The two scripts are adapted for different experimental sessions: script_dcm2nii_S1.sh is used for data from the first session (S1), while script_dcm2nii_S2.sh is used for the second session (S2). The scripts differ in that S2 additionally processes diffusion-weighted imaging (DWI) data. Both scripts were developed as part of my own work with my individual MRI data. If you want to use them on your own data, you may need to adjust the scripts to match your raw data’s naming conventions. For more information, see the ReadMe file.
- Keyword:
- NIfTI (Neuroimaging Informatics Technology Initiative), conversion, Bash script, DICOM (Digital Imaging and Communications in Medicine), and BIDS (Brain Imaging Data Structure)
- Publisher:
- Language:
- English
- Date Uploaded:
- 2026-01-14
- Date Modified:
- 2026-01-19
- License:
- MIT License
- Resource Type:
- Software
-
- Description:
- This R script was developed to “translate” movement log files from a navigation task (path integration) experiment into so-called 'event tables'. These event tables summarize the recorded movements and can be used for further analyses, for example, to synchronize movement logs with brain activity. The script processes all CSV log files in a specified folder, classifies movement types, groups consecutive events, calculates onset, duration, and angles, and generates both individual and combined master event tables. Sample data are provided to test the script, though path adjustments are required. For more information, see the ReadMe file.
- Keyword:
- RStudio script, Movement log, and Event Table
- Publisher:
- Language:
- English
- Date Uploaded:
- 2026-01-14
- Date Modified:
- 2026-01-19
- License:
- MIT License
- Resource Type:
- Software
-
- Description:
- Generates configurable path integration (PI) patterns for Virtual Reality (VR) navigation experiments with RStudio. Creates 4-point configurations (Spawn→Start→Distractor→Goal→back to Start) optimized for maximum path length while respecting geometric constraints. The script was developed out of the need for rapid randomized generation of path integration patterns that can be easily adapted to the respective experimental conditions. In addition to the actual RStudio script, the package also contains an accompanying ReadMe file, sample input data, and the corresponding output files.
- Keyword:
- Virtual Experiments, Path Integration, RStudio script, and Virtual Environments
- Publisher:
- Language:
- English
- Date Uploaded:
- 2026-01-14
- Date Modified:
- 2026-01-19
- License:
- MIT License
- Resource Type:
- Dataset
-
- Description:
- Visualizes participant navigation trajectories from Virtual Reality (VR) path integration (PI) experiments, showing target locations, traversed paths, orientation arrows, and drop error distances in RStudio. The script was developed to check whether participants performed the task correctly or whether other problems occurred during a trial (e.g., path integration marker was not deactivated correctly). Such trials were successfully excluded from further data analysis using the visualization script. In addition to the actual RStudio script, the package also includes an accompanying ReadMe file, sample input data, and the corresponding output visualizations.
- Keyword:
- RStudio script, path visualization, and path integration
- Publisher:
- Language:
- English
- Date Uploaded:
- 2026-01-14
- Date Modified:
- 2026-01-19
- License:
- MIT License
- Resource Type:
- Dataset
