We provided an OPA-building pipeline for the optimal coil pose and the data from the simulation results are openly available in Science Data Bank

• Function1: Coil Pose Conversion Tool
• Function2: Coil Pose mapping tool

1. Install and create a python environment, such as conda
2. To install the dependency library, see requirements.txt

• Convert HAC coil coordinate system to MNI coordinate system inferior pose

cd ./TMS_OPA
python ./tms_convert.py -p {a} {b}

• MNI coordinates of the position of the center point of the coil

• Statistical analysis of simulation results to generate group coil pose mapping

• The subject of the simulation results and the directory where the results are stored
  • Modify the corresponding content in the file analysis_config.py
  • Example：

  subjectnum_result = [
        {
            'subject': '003', # The first subject
            'simu_result_path': 'simu_result20201226232724_21443' # Corresponding simulation results catalog
        },
        {
            'subject': '004',
            'simu_result_path': 'simu_result20210124015948_33635'
        }
    ]

• Evaluation index parameters
  • Modify the contents of the file analysis_config.py accordingly, see the comments for details
• Objective function
  • Modify the corresponding content in the file tms_evaluation.py
  • Example：

  # func(x) = 3.0/resultA_x + 1.0 / resultB_B2/B1_x
  func = lambda all_csv, area_index : 3.0 / all_csv['resultA_' + str(area_index)] + 1.0 / all_csv['resultB_B2/B1_' + str(area_index)]

• Modify dataPath
  • Modify the path where the file data file is located

May take longer for statistical analysis

cd ./TMS_OPA
python ./tms_opa.py -o {path_to_save_result}

If you use TMS_OPA in an academic work, please cite:

@article{TMS_OPA,
  title={Stimulation Effects Mapping for Optimal Coil Pose Atlas of Transcranial Magnetic Stimulation},
  author={Gangliang Zhong, Liang Ma, Yongfeng Yang, Baogui Zhang, Xuefeng Lu, Dan Cao, Jin Li, Nianming Zuo, Lingzhong Fan, Zhengyi Yang, Tianzi Jiang},
  journal={under review}, 
  volume={under review},
  number={under review},
  pages={under review},
  year={2022}
 }