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Example Data for "A Low-Power Band of Neuronal Spiking Activity Dominated by Local Single Units Improves the Performance of Brain-Machine Interfaces"

Creator:

Nason, Samuel R., Vaskov, Alex K., Willsey, Matthew S., Welle, Elissa J., An, Hyochan, Vu, Philip P., Bullard, Autumn J., Nu, Chrono S., Kao, Jonathan C., Shenoy, Krishna V., Jang, Taekwang, Kim, Hun-Seok, Blaauw, David, Patil, Parag G., and Chestek, Cynthia A.

Description:

This data is a subset of the data used to generate figures similar to figures 1, 2, 3, and 4 in Nason et al., 2020, Nature Biomedical Engineering. The purpose of the study was to demonstrate the benefits of using spiking band power, a low-power but single unit specific recording signal, for brain-machine interfaces with nonhuman primates with the potential to impact low-power brain-machine interfaces with humans. All of the data is contained in .mat files, which can be commonly opened by Matlab and the Python scipy library.

Keyword:

Brain-machine interface, Prosthesis, and Neural recording

Citation to related publication:

Nason, S.R., Vaskov, A.K., Willsey, M.S., Welle, E.J., An, H., Vu, P.P., Bullard, A.J., Nu, C.S., Kao, J.C., Shenoy, K.V., Jang, T., Kim, H.-S., Blaauw, D., Patil, P.G., and Chestek, C.A. (2020). A low-power band of neuronal spiking activity dominated by local single units improves the performance of brain–machine interfaces. Nat. Biomed. Eng. 4, 973–983. https://doi.org/10.1038/s41551-020-0591-0

Discipline:

Engineering
Example Data and Code for "Real-Time Linear Prediction of Simultaneous and Independent Movements of Two Finger Groups Using an Intracortical Brain-Machine Interface"

Creator:

Nason, Samuel R., Mender, Matthew J., Vaskov, Alex K., Willsey, Matthew S., Ganesh Kumar, N., Kung, Theodore A., Patil, Parag G., and Chestek, Cynthia A.

Description:

This data is a subset of the data used to generate components of all figures in the manuscript and supplement in Nason et al., 2021, Neuron. The purpose of the study was to demonstrate the first-ever simultaneous brain-control of two independent groups of fingers in one hand with some analysis of cortical tuning to finger movements in nonhuman primates. This advises future brain-machine interfaces for the control of finger movements with humans. All of the data is contained in .mat files, which can be commonly opened by Matlab and the Python scipy library. The Matlab packages (and versions) used for the manuscript are: MATLAB (9.4), Signal Processing Toolbox (8.0), Statistics and Machine Learning Toolbox (11.3), and Curve Fitting Toolbox (3.5.7).

Keyword:

Brain-machine interface, Prosthesis, and Upper extremity

Citation to related publication:

Nason, S.R., Mender, M.J., Vaskov, A.K., Willsey, M.S., Ganesh Kumar, N., Kung, T.A., Patil, P.G., and Chestek, C.A. (2021). Real-Time Linear Prediction of Simultaneous and Independent Movements of Two Finger Groups Using an Intracortical Brain-Machine Interface. Neuron (accepted).

Discipline:

Engineering

Example Data for "A Low-Power Band of Neuronal Spiking Activity Dominated by Local Single Units Improves the Performance of Brain-Machine Interfaces"

Example Data and Code for "Real-Time Linear Prediction of Simultaneous and Independent Movements of Two Finger Groups Using an Intracortical Brain-Machine Interface"

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Example Data for "A Low-Power Band of Neuronal Spiking Activity Dominated by Local Single Units Improves the Performance of Brain-Machine Interfaces"

Example Data and Code for "Real-Time Linear Prediction of Simultaneous and Independent Movements of Two Finger Groups Using an Intracortical Brain-Machine Interface"

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