TY - JOUR
T1 - Model-based decoupling of evoked and spontaneous neural activity in calcium imaging data
AU - Triplett, Marcus A.
AU - Pujic, Zac
AU - Sun, Biao
AU - Avitan, Lilach
AU - Goodhill, Geoffrey J.
N1 - Funding Information:
This work was supported by Australian Research Council Discovery Projects 170102263 and 180100636 awarded to G.J.G (www.arc.gov. au). M.A.T. was supported by an Australian Government Research Training Program Scholarship. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Publisher Copyright:
© 2020 Triplett et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2020/11/30
Y1 - 2020/11/30
N2 - The pattern of neural activity evoked by a stimulus can be substantially affected by ongoing spontaneous activity. Separating these two types of activity is particularly important for calcium imaging data given the slow temporal dynamics of calcium indicators. Here we present a statistical model that decouples stimulus-driven activity from low dimensional spontaneous activity in this case. The model identifies hidden factors giving rise to spontaneous activity while jointly estimating stimulus tuning properties that account for the confounding effects that these factors introduce. By applying our model to data from zebrafish optic tectum and mouse visual cortex, we obtain quantitative measurements of the extent that neurons in each case are driven by evoked activity, spontaneous activity, and their interaction. By not averaging away potentially important information encoded in spontaneous activity, this broadly applicable model brings new insight into population-level neural activity within single trials.
AB - The pattern of neural activity evoked by a stimulus can be substantially affected by ongoing spontaneous activity. Separating these two types of activity is particularly important for calcium imaging data given the slow temporal dynamics of calcium indicators. Here we present a statistical model that decouples stimulus-driven activity from low dimensional spontaneous activity in this case. The model identifies hidden factors giving rise to spontaneous activity while jointly estimating stimulus tuning properties that account for the confounding effects that these factors introduce. By applying our model to data from zebrafish optic tectum and mouse visual cortex, we obtain quantitative measurements of the extent that neurons in each case are driven by evoked activity, spontaneous activity, and their interaction. By not averaging away potentially important information encoded in spontaneous activity, this broadly applicable model brings new insight into population-level neural activity within single trials.
UR - http://www.scopus.com/inward/record.url?scp=85097140121&partnerID=8YFLogxK
U2 - 10.1371/journal.pcbi.1008330
DO - 10.1371/journal.pcbi.1008330
M3 - Article
C2 - 33253161
AN - SCOPUS:85097140121
SN - 1553-734X
VL - 16
JO - PLoS computational biology
JF - PLoS computational biology
IS - 11
M1 - e1008330
ER -