@article{6314a14d9f304e0e9ce0451a4e443760,
title = "Scaling Properties of Dimensionality Reduction for Neural Populations and Network Models",
abstract = "Recent studies have applied dimensionality reduction methods to understand how the multi-dimensional structure of neural population activity gives rise to brain function. It is unclear, however, how the results obtained from dimensionality reduction generalize to recordings with larger numbers of neurons and trials or how these results relate to the underlying network structure. We address these questions by applying factor analysis to recordings in the visual cortex of non-human primates and to spiking network models that self-generate irregular activity through a balance of excitation and inhibition. We compared the scaling trends of two key outputs of dimensionality reduction—shared dimensionality and percent shared variance—with neuron and trial count. We found that the scaling properties of networks with non-clustered and clustered connectivity differed, and that the in vivo recordings were more consistent with the clustered network. Furthermore, recordings from tens of neurons were sufficient to identify the dominant modes of shared variability that generalize to larger portions of the network. These findings can help guide the interpretation of dimensionality reduction outputs in regimes of limited neuron and trial sampling and help relate these outputs to the underlying network structure.",
author = "Williamson, {Ryan C.} and Cowley, {Benjamin R.} and Ashok Litwin-Kumar and Brent Doiron and Adam Kohn and Smith, {Matthew A.} and Yu, {Byron M.}",
note = "Funding Information: RCW is supported by National Institute of Drug Abuse (NIDA, https://www.drugabuse.gov/, DA022762), National Institute of General Medical Sciences (NIGMS, https://www.nigms.nih.gov/, GM008208), and a Richard King Mellon Foundation (http://foundationcenter.org/grantmaker/rkmellon/) Presidential Fellowship in the Life Sciences. BRC is supported by National Defense Science and Engineering Graduate Fellowship (https://ndseg.asee.org/, 32 CFR 168a). ALK, BD, AK, and BMY are supported by Simons Foundation (https://www.simonsfoundation.org/, 325293, 364994). ALK is also supported by NIH National Institute on Deafness and Other Communication Disorders (NIDCD, https://www.nidcd.nih.gov/, F32DC014387). BD, MAS, and BMY are supported by a Carnegie Mellon University ProSEED / Brainhub seed grant. BD is also supported by National Science Foundation (NSF, http://www.nsf.gov/, DMS-1313225, DMS-1517082). AK and MAS are supported by National Eye Institute (NEI, https://nei.nih.gov/, EY016774, EY022928, P30EY008098) and Research to Prevent Blindness (https://www.rpbusa.org/). AK is also supported by a Irma T. Hirschl Career Scientist Award (https://www.einstein.yu.edu/administration/grant-support/Hirschl.aspx). MAS is also supported by Eye and Ear Foundation of Pittsburgh (http://eyeandear.org/). BMY is also supported by National Institute of Child Health and Human Development (NICHD, https://www.nichd.nih.gov/, HD071686) and National Science Foundation (NSF, http://www.nsf.gov/, BCS-1533672). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.",
year = "2016",
month = dec,
doi = "10.1371/journal.pcbi.1005141",
language = "English (US)",
volume = "12",
journal = "PLoS Computational Biology",
issn = "1553-734X",
publisher = "Public Library of Science",
number = "12",
}