Algebraic approach for subspace decomposition and clustering of neural activity
Name
1-s2.0-S2666166722007213-main.pdf
Description
Published version
Size
2.53 MB
Format
Adobe PDF
Checksum (MD5)
cbb58f63ab16cfcc763496f2d77f41ad
Author(s)
Adam, Elie M
Sur, Mriganka
Date Issued
December 2022
Journal
STAR Protocols
Publisher
Elsevier BV
Citation
Adam, Elie M and Sur, Mriganka. 2022. "Algebraic approach for subspace decomposition and clustering of neural activity." STAR Protocols, 3 (4).
Version
Final published version
Abstract
We developed an approach to decompose neuronal signals into disjoint components, corresponding to task- or event-based epochs. This protocol describes how to project behavioral templates onto a low-dimensional subspace of neuronal responses to derive neuronal templates, then how to decompose and cluster neuronal responses using these derived templates. We outline these steps on complementary datasets of calcium imaging and spiking activity. Our approach relies on fundamental, linear algebraic principles and is adaptive to the temporal structure of the neural data. For complete details on the use and execution of this protocol, please refer to Adam et al. (2022).1.
MIT Department
Massachusetts Institute of Technology. Department of Brain and Cognitive Sciences
Terms of Use
Creative Commons Attribution-NonCommercial-NoDerivs License
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1016/j.xpro.2022.101841
