This readme.txt file was generated on 20210317 by DRUM curator ------------------- GENERAL INFORMATION ------------------- 1. Title of Dataset Data from: Individual Magnetoencephalography Response Profiles to Short-Duration L-Dopa in Parkinson’s Disease 2. Author Information Peña, Edgar Mohammad, Tareq M Almohammed, Fedaa AlOtaibi, Tahani Nahrir, Shahpar Khan, Sheraz Poghosyan, Vahe Johnson, Matthew D Bajwa, Jawad A Principal Investigator Contact Information Name: Jawad A Bajwa Institution: National Neuroscience Institute, King Fahad Medical City, As Sulimaniyah, Riyadh 12231, Saudi Arabia Address: National Neuroscience Institute, King Fahad Medical City, As Sulimaniyah, Riyadh 12231, Saudi Arabia Email: drbajwa@gmail.com ORCID: N/A 3. Date of data collection (single date, range, approximate date) 20131026-20151102 4. Geographic location of data collection (where was data collected?): Riyadh, Saudi Arabia 5. Information about funding sources that supported the collection of the data: King Fahad Medical City; National Science Foundation (00039202 to E.P.); National Institutes of Health (R01-NS094206 and P50-NS098573) -------------------------- SHARING/ACCESS INFORMATION -------------------------- 1. Licenses/restrictions placed on the data: CC0 1.0 Universal https://creativecommons.org/publicdomain/zero/1.0/ 2. Links to publications that cite or use the data: Peña, E., Mohammad, T. M., Almohammed, F., AlOtaibi, T., Nahrir, S., Khan, S., Poghosyan, V., Johnson, M. D., and Bajwa, J. A. (2021). Individual Magnetoencephalography Response Profiles to Short-Duration L-Dopa in Parkinson’s Disease. Frontiers in Human Neuroscience, 15, 127. doi 10.3389/fnhum.2021.640591 3. Links to other publicly accessible locations of the data: The MATLAB code used to train and test the SVMs is available at the following GitHub repository: https://github.com/eurypt/MEG-UPDRS. 4. Recommended citation for the data: Peña, Edgar; Mohammad, Tareq M; Almohammed, Fedaa; AlOtaibi, Tahani; Nahrir, Shahpar; Khan, Sheraz; Poghosyan, Vahe; Johnson, Matthew D; Bajwa, Jawad A. (2021). Data from: Individual Magnetoencephalography Response Profiles to Short-Duration L-Dopa in Parkinson’s Disease. Retrieved from the Data Repository for the University of Minnesota, https://doi.org/10.13020/r6af-pj55. --------------------- DATA & FILE OVERVIEW --------------------- 1. File List A. Filename: motor_factor_scores.csv Short description: Source data for Figure 1 of publication. Data consists of motor factor scores in the LEVODOPA-OFF and LEVODOPA-ON conditions, as well as the total MDS-UPDRS III score. B. Filename: feature_weights.csv Short description: Source data for Figure 2B of publication. Data consists of SVM feature weights acros all subjects included in SVM analysis and for all classification folds and feature bands. C. Filename: SVM_accuracies.csv Short description: Source data for Figure 2A of publication. Data consists of SVM accuracy values (from 0 to 1; 0.5 is chance accuracy) across all subjects included in SVM analysis and for all classification folds. 2. Additional related data collected that was not included in the current data package: N/A -------------------------- METHODOLOGICAL INFORMATION -------------------------- 1. Description of methods used for collection/generation of data: A detailed description of methods used to collect and generate the data are available in the Open Access publication entitled "Individual Magnetoencephalography Response Profiles to Short- Duration L-Dopa in Parkinson's Disease" (Peña et al 2021 Frontiers in Human Neuroscience, DOI: 10.3389/fnhum.2021.640591). Briefly, clinical scores and electrophysiological recordings were obtained from Parkinson's Disease subjects. Full details are available in the publication, which is freely accessible at the following link: https://www.frontiersin.org/articles/10.3389/fnhum.2021.640591/full 2. Methods for processing the data: Details of the data processing are described in the Open Access publication (cited above). Briefly, machine learning was used to classify subject medication state using the electrophysiological recordings. The shared data includes severity of subject motor impairment, classifier parameters, and classifier accuracy. 3. Instrument- or software-specific information needed to interpret the data: The data are in .csv format, which can be opened by any text editor. 4. Standards and calibration information, if appropriate: N/A 5. Environmental/experimental conditions: N/A 6. Describe any quality-assurance procedures performed on the data: N/A 7. People involved with sample collection, processing, analysis and/or submission: All people involved were listed as authors. Details of author contributions are described in the Open Access publication cited above. ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: motor_factor_scores.csv ----------------------------------------- 1. Number of variables: 10 2. Number of cases/rows: 40 3. Missing data codes: N/A 4. Variable List A. Name: subject_number Description: Unique subject number Number 1 to 20 B. Name: factor_1 Description: Motor factor #1 Number >= 0 indicating severity of factor #1 C. Name: factor_2 Description: Motor factor #2 Number >= 0 indicating severity of factor #2 D. Name: factor_3 Description: Motor factor #3 Number >= 0 indicating severity of factor #3 E. Name: factor_4 Description: Motor factor #4 Number >= 0 indicating severity of factor #4 F. Name: factor_5 Description: Motor factor #5 Number >= 0 indicating severity of factor #5 G. Name: factor_6 Description: Motor factor #6 Number >= 0 indicating severity of factor #6 H. Name: factor_7 Description: Motor factor #7 Number >= 0 indicating severity of factor #7 I. Name: med_condition Description: Medication condition off - Before taking medication on - After taking medication J. Name: total Description: Total motor severity (sum of all factors) Number >= 0 indicating total severity ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: feature_weights.csv ----------------------------------------- 1. Number of variables: 4 2. Number of cases/rows: 680 3. Missing data codes: N/A 4. Variable List A. Name: subject_number Description: Unique subject number Number 1 to 20 B. Name: fold_index Description: Fold of cross validation used to train the classifier Number 1 to 10 C. Name: feature_band Description: Frequency range over which spectral power was calculated Four possible values: 7-13 Hz, 13-20 Hz, 20-30 Hz, 35-45 Hz D. Name: weight Description: Weight of the frequency range within classifier Floating-point number ----------------------------------------- DATA-SPECIFIC INFORMATION FOR: SVM_accuracies.csv ----------------------------------------- 1. Number of variables: 3 2. Number of cases/rows: 170 3. Missing data codes: N/A 4. Variable List A. Name: subject_number Description: Unique subject number Number 1 to 20 B. Name: fold_index Description: Fold of cross validation used to train the classifier Number 1 to 10 C. Name: accuracy Description: Accuracy of classifier Floating-point number from 0 to 1