Index Catalog // Deep Blue Data

Start Over

Filtering by: Creator Bullard, Autumn J. 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"

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

Limit your search

Resource type

Creator

Discipline

Language

Search Results

Search Constraints

Search Results

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

Limit your search

Resource type

Creator

Discipline

Language