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 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."
This data and scripts are meant to test and show that seizure onset dynamics can be modulated using anti-epileptic drugs. A zip file is included that contains all waveform data, MATLAB processing scripts, and metadata. The MATLAB scripts allow for visual review validation and objective feature analysis. The file includes various README files explaining the scripts and their relationships in greater detail.
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
The two R codes are related to the feasible balance region calculations for Figures 2, 3, and 4 in the paper.
The MATLAB codes are related to the simulations of the recoverable initial quasi-static states, the results of which are shown in Figure 5 of the paper.
Shahshahani, P. M., & Ashton-Miller, J. A. (2020). On the importance of the hip abductors during a clinical one legged balance test: A theoretical study. PLOS ONE, 15(11), e0242454. https://doi.org/10.1371/journal.pone.0242454
