Data deposited here includes 60 image sets (30 individual participants, and 2 eyes per individual) consisting of raw fluorescence images, diffuse reflection images using ambient lighting, images used for correction, and calibration, and metadata. Images are split into two wavelength bands as described in the methodology. Raw images are stored in Hierarchical Data Format 5 (HDF5) file nodes (one file per eye) and each image node contains a tag for frame rate, exposure duration, and timestamp (stored in ImageData.zip).
Summary statistics including demographic data, participant-reported diseases (e.g., diabetes, keratoconus), and pupil size are also stored in a text-based comma-separated table and as an Excel spreadsheet. Finally, 2-channel pseudocolor images and ratiometric grayscale images combining the two fully-processed image bands are stored as portable network graphics (PNG) files (stored in PseudocolorImages.zip).
Herzog, Joshua M., Verkade, Angela, and Sick, Volker. "Corneal shadowgraphy: a simple, low-cost, rapid, and quantitative tool with potential clinical utility." Manuscript in review. 2024. and Herzog, Joshua M., Verkade, Angela, and Sick, Volker. "Quantitative and rapid in vivo imaging of human lenticular fluorescence." Manuscript in review. 2024.
This is data from Wallace, Benyamini et al., 2023, Journal of Neural Engineering. There are two sets of data included:
1. Neural features and error labels used to train error classifiers for each day used in the study
2. Trial data from an example experiment day (Monkey N, Day 6), with runs for offline calibration, online brain control, error monitoring, and error correction.
The purpose of this study was to investigate the use of error signals in motor cortex to improve brain-machine interface (BMI) performance for control of two finger groups. All data is contained in .mat files, which can be opened using MATLAB or the Python SciPy library.
Wallace, D. M., Benyamini, M., Nason-Tomaszewski, S. R., Costello, J. T., Cubillos, L. H., Mender, M. J., Temmar, H., Willsey, M. S., Patil, P. G., Chestek, C. A., & Zacksenhouse, M. (2023). Error detection and correction in intracortical brain–machine interfaces controlling two finger groups. Journal of Neural Engineering, 20(4), 046037. https://doi.org/10.1088/1741-2552/acef95
The IN were sampled during and after ICB and sequenced to identify gene expression signatures that correlated with sensitivity or resistance. We also analyzed gene expression at the IN prior to ICB treatment to identify markers predicting therapeutic response. Longitudinally interrogating an IN, to monitor changes associated with ICB response, presents a new opportunity to personalize care and investigate mechanisms underlying treatment resistance.
The data and scripts are meant to show how burster dynamics determine response to a single biphasic stimulus. The files include data which show trends in the propensity of termination for different burster types and the MATLAB scripts used to generate this data. The MATLAB scripts also allow the user to generate their own data sets for alternative bursting paths and stimulus parameter combinations. Furthermore, they allow the user to visually examine the effects of single stimuli in the voltage timeseries and in state space. How the user can access these features of the script is described in the file "ReadMe.pdf."
The data and the scripts are to show that seizure onset dynamics and evoked responses change over the progression of epileptogenesis defined in this intrahippocampal tetanus toxin rat model. All tests explored in this study can be repeated with the data and scripts included in this repository. and Dataset citation: Crisp, D.N., Cheung, W., Gliske, S.V., Lai, A., Freestone, D.R., Grayden, D.B., Cook, MJ., Stacey, W.C. (2019). Epileptogenesis modulates spontaneous and responsive brain state dynamics [Data set]. University of Michigan Deep Blue Data Repository. https://doi.org/10.7302/r6vg-9658
Crisp, D. N., Cheung, W., Gliske, S. V., Lai, A., Freestone, D. R., Grayden, D. B., Cook, M. J., & Stacey, W. C. (2020). Quantifying epileptogenesis in rats with spontaneous and responsive brain state dynamics. Brain Communications, 2(1). https://doi.org/10.1093/braincomms/fcaa048
Please refer to the "README.txt" for more details., MATLAB R2018a (Mathworks, Natick, MA, USA) was used to process this data., and Excel (Microsoft Office) was used to store survey data on the comfort of both systems and also to provide absolute and relative intraobserver variablities for the DM device.
Comparison of anorectal function measured using wearable digital manometry and a high resolution manometry system Attari A, Chey WD, Baker JR, Ashton-Miller JA (2020) Comparison of anorectal function measured using wearable digital manometry and a high resolution manometry system. PLOS ONE 15(9): e0228761. https://doi.org/10.1371/journal.pone.0228761
This data repository includes the quantitative features of high frequency, intracranial EEG along with all necessary scripts to reproduce the figures of the accompanying manuscript.
We evaluated PM levels at the Agbogbloshie e-waste and scrap yard site in Accra, Ghana, and at upwind and downwind locations. This monitoring forms part of the West Africa-Michigan Charter II for GEOHealth cohort study, which is analyzing occupational exposures and health risks at this site.
Kwarteng, L., Baiden, E. A., Fobil, J., Arko-Mensah, J., Robins, T., & Batterman, S. (2020). Air Quality Impacts at an E-Waste Site in Ghana Using Flexible, Moderate-Cost and Quality-Assured Measurements. GeoHealth, 4(8), e2020GH000247. https://doi.org/10.1029/2020GH000247
Investigating minimum human reaction times is often confounded by the motivation, training, and state of arousal of the subjects. We used the reaction times of athletes competing in the shorter sprint events in the Athletics competitions in recent Olympics (2004-2016) to determine minimum human reaction times because there's little question as to their motivation, training, or state of arousal.
The reaction times of sprinters however are only available on the IAAF web page for each individual heat, in each event, at each Olympic. Therefore we compiled all these data into two separate excel sheets which can be used for further analyses.
Mirshams Shahshahani P, Lipps DB, Galecki AT, Ashton-Miller JA (2018) On the apparent decrease in Olympic sprinter reaction times. PLoS ONE 13(6): e0198633. https://doi.org/10.1371/journal.pone.0198633
This data is part of a large program to translate detection and interpretation of HFOs into clinical use. A zip file is included which contains hfo detections, metadata, and Matlab scripts. The matlab scripts analyze this input data and produce figures as in the referenced paper (note: the blind source separation method is stochastic, and so the figures may not be exactly the same). A file "README.txt" provides more detail about each individual file within the zip file.
Stephen V. Gliske, Zachary T. Irwin, Cynthia Chestek, Garnett L. Hegeman, Benjamin Brinkmann, Oren Sagher, Hugh J. L. Garton, Greg A. Worrell, William C. Stacey. "Variability in the location of High Frequency Oscillations during prolonged intracranial EEG recordings." Nature Communications. https://doi.org/10.1038/s41467-018-04549-2