This dataset contains annotated interictal epileptiform discharge (IED) from 84 patients (Peking Union Medical College Hospital, China), each contributing 20 minutes of continuous raw EEG recordings, using MAT format. The IEDs are categorized into five types based on occurrence regions. The states of consciousness (wake/sleep) are annotated.
Note on version 2:The dataset has been updated. Specifically, a total of 37 annotations (31 deletions and 6 updates) were adjusted to ensure accuracy and consistency for analysis. These annotations were modified due to their atypical characteristics, differing from conventional interictal epileptiform discharges (IEDs). This refined dataset represents the final version used for training and validation in our associated paper entitled “An EEG dataset for interictal epileptiform discharges with spatial distribution information”.
The specific changes of annotations are listed as follow:MAT_Files:DA00103C.mat  Delete:['305.846', '0', '!']DA00100Z.mat  Delete:['142.686', '0', '!']DA00102T.mat  Delete:['213.124', '0', '!'], ['388.27', '0', '!'], Update:['213.78', '0', '!end'] -> ['211.78', '0', '!end']DA00102W.mat  Delete:['48.274', '0', '!'], ['438.406', '0', '!'], ['516.94', '0', '!'], ['576.554', '0', '!']DA00102Y.mat  Delete:['605.436', '0', '!']DA00103B.mat  Delete:['1173.344', '0', '!']DA00103I.mat  Update:['1128.746', '0', '!end'] -> ['1127.746', '0', '!end']DA00103K.mat  Delete:['485.026', '0', '!']DA00103M.mat  Delete:['45.006', '0', '!'], ['76.166', '0', '!'], ['108.226', '0', '!'], ['189.608', '0', '!'], ['537.642', '0', '!']DA00103N.mat  Update:['1196.27', '0', '!end'] -> ['1195.27', '0', '!end']DA00103Q.mat  Delete:['696.692', '0', '!'], ['1213.206', '0', '!'], Update:['632.1', '0', '!'] -> ['632.2', '0', '!']DA00103U.mat  Delete:['1076.12', '0', '!'], ['1208.146', '0', '!'], ['1210.474', '0', '!'], ['1211.242', '0', '!']DA00100S.mat  Delete:['1204.8', '0', '!']DA00103O.mat  Delete:['12.542', '0', '!']DA00103S.mat  Delete:['1173.22', '0', '!']DA001010.mat  Delete:['1185.496', '0', '!']DA001031.mat  Delete:['0.684', '0', '!'], ['222.106', '0', '!']DA00103E.mat  Delete:['862.716', '0', '!']DA00100V.mat  Delete:['768.154', '0', '!']，['768.532', '0', '!']DA00102R.mat  Update:['552.244', '0', '!end'] →['551.244', '0', '!end']，['704.172', '0', '!end'] →['703.172', '0', '!end']
The changes in MAT_Files result in alterations in the npy_files: DA00103C_152000_154000_500__5.npy(Occipital-IED) -> DA00103C_152000_154000_500__0.npy(Non-IED)DA00100Z_70000_72000_500__2.npy(Frontal-IED) -> DA00100Z_70000_72000_500__0.npy (Non-IED)DA00102W_24000_26000_500__3.npy(Temporal-IED) -> DA00102W_24000_26000_500__0.npy (Non-IED)DA00102W_218000_220000_500__3.npy(Temporal-IED) -> DA00102W_218000_220000_500__0.npy (Non-IED)DA00102W_258000_260000_500__3.npy(Temporal-IED) -> DA00102W_258000_260000_500__0.npy(Non-IED)DA00102Y_302000_304000_500__4.npy(Centro-Parietal-IED) -> DA00102Y_302000_304000_500__0.npy(Non-IED)DA00103M_22000_24000_500__2.npy(Frontal-IED) -> DA00103M_22000_24000_500__0.npy(Non-IED)DA00103M_94000_96000_500__2.npy(Frontal-IED) -> DA00103M_94000_96000_500__0.npy(Non-IED)DA00103M_268000_270000_500__2.npy(Frontal-IED) -> DA00103M_268000_270000_500__0.npy(Non-IED)DA00103U_604000_606000_500__3.npy(Temporal-IED) -> DA00103U_604000_606000_500__0.npy(Non-IED)DA00103C_170000_172000_500__0.npy(Non-IED) -> DA00103C_170000_172000_500__5.npy(Occipital-IED)DA00100Z_0_2000_500__0.npy(Non-IED) -> DA00100Z_0_2000_500__2.npy(Frontal-IED)DA00102W_124000_126000_500__0.npy(Non-IED) -> DA00102W_124000_126000_500__3.npy(Temporal-IED)DA00102W_242000_244000_500__0.npy(Non-IED) -> DA00102W_242000_244000_500__3.npy(Temporal-IED)DA00102W_268000_270000_500__0.npy(Non-IED) -> DA00102W_268000_270000_500__3.npy(Temporal-IED)DA00102Y_612000_614000_500__0.npy(Non-IED) -> DA00102Y_612000_614000_500__4.npy(Centro-Parietal-IED)DA00103M_30000_32000_500__0.npy(Non-IED) -> DA00103M_30000_32000_500__2.npy(Frontal-IED)DA00103M_96000_98000_500__0.npy(Non-IED) -> DA00103M_96000_98000_500__2.npy(Frontal-IED)DA00103M_568000_570000_500__0.npy(Non-IED) -> DA00103M_568000_570000_500__2.npy(Frontal-IED)DA00103U_606000_607500_500__0.npy(Non-IED) -> DA00103U_606000_607500_500__3.npy(Temporal-IED)

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

This repository supports the publication “Electrically Modulated Photothermal Force Microscopy for Revealing Molecular Configuration Changes During Polarization Switching at the Nanoscale”. It contain all the data for each figure in manuscript and supplementary materials.

This repository supports the publication “Electrically Modulated Photothermal Force Microscopy for Revealing Molecular Configuration Changes During Polarization Switching at the Nanoscale”. It contain all the data for each figure in manuscript and supplementary materials.

Elemental composition analysis, anisotropic magnetoresistance, the determination of the Gilbert damping constant, time-resolved magneto-optical Kerr effect measurements, and calculations of the nonlinearity coefficient.

Elemental composition analysis, anisotropic magnetoresistance, the determination of the Gilbert damping constant, time-resolved magneto-optical Kerr effect measurements, and calculations of the nonlinearity coefficient.

All data are provided in NIfTI format, registered to the MNI reference space, with an isotropic resolution of 1.0 mm³. The dataset is organized into two subfolders: “CBF-atlases”, which contains the mean and standard deviation maps of the age- and sex-specific CBF atlases (CBF_[age group][sex][mean or std].nii.gz, units: ml/100g/min), and “T1w-template”, which includes the corresponding age-specific T1-weighted structural templates (T1w-template-[age group]-brain.nii.gz). The age groups include CH (children), YO (youth), YA (young adults), MA (middle-aged adults), and OA (older adults), while the sex categories consist of Male, Female, and All (combined Male and Female). All images are saved with floating-point values. The original datasets used for atlas generation are available from the corresponding author upon reasonable request.In addition to the age-specific templates, we have generated a common template that serves as a central reference across all age groups. This template was created by applying the same methodology used for the age-specific templates but using the generated age-specific templates as inputs instead of individual T1 images. The common T1w template is publicly available in “T1w-template” folder with name of [T1w-template-Allage-brain.nii.gz]. and the common CBF atlases are publicly available in “CBF-atlases” folder with name of [CBF_Allage_mean.nii.gz].

An entry from the Cambridge Structural Database, the world’s repository for small molecule crystal structures. The entry contains experimental data from a crystal diffraction study. The deposited dataset for this entry is freely available from the CCDC and typically includes 3D coordinates, cell parameters, space group, experimental conditions and quality measures.

All data are provided in NIfTI format, registered to the MNI reference space, with an isotropic resolution of 1.0 mm³. The dataset is organized into two subfolders: “CBF-atlases”, which contains the mean and standard deviation maps of the age- and sex-specific CBF atlases (CBF_[age group][sex][mean or std].nii.gz, units: ml/100g/min), and “T1w-template”, which includes the corresponding age-specific T1-weighted structural templates (T1w-template-[age group]-brain.nii.gz). The age groups include CH (children), YO (youth), YA (young adults), MA (middle-aged adults), and OA (older adults), while the sex categories consist of Male, Female, and All (combined Male and Female). All images are saved with floating-point values. The original datasets used for atlas generation are available from the corresponding author upon reasonable request.In addition to the age-specific templates, we have generated a common template that serves as a central reference across all age groups. This template was created by applying the same methodology used for the age-specific templates but using the generated age-specific templates as inputs instead of individual T1 images. The common T1w template is publicly available in “T1w-template” folder with name of [T1w-template-Allage-brain.nii.gz]. and the common CBF atlases are publicly available in “CBF-atlases” folder with name of [CBF_Allage_mean.nii.gz].