resting-state-network modularity by increasing visual-sensorimotor

During wakeful rest, individuals make small eye movements during fixation. We examined how these 13 endogenously-driven oculomotor patterns impact topography and topology of functional brain networks. 14 We used a dataset consisting of eyes-open resting-state (RS) fMRI data with simultaneous eye-tracking 15 (Nilsonne et al., 2016). The eye-tracking data indicated minor movements during rest, which correlated 16 modestly with RS BOLD data. However, eye-tracking data correlated well with echo-planar imaging 17 time series sampled from the area of the Eye-Orbit (EO-EPI), which is a signal previously used to 18 identify eye movements during exogenous saccades and movie viewing. Further analyses showed that 19 EO-EPI data were correlated with activity in an extensive motor and sensory-motor network, including 20 components of the dorsal attention network and the frontal eye fields. Partialling out variance related to 21 Koba, C., Notaro, G., Tamm, S., Nilsonne, G. & Hasson, U. (2021). Spontaneous eye movements during eyesopen rest reduce resting-state-network modularity by increasing visual-sensorimotor connectivity. Network Neuroscience. Advance publication. https://doi.org/10.1162/netn_a_00186 == D R A F T == Journal: NETWORK NEUROSCIENCE / Title: Spontaneous eye-movements and resting-state connectivity Authors: Koba et al. EO-EPI from RS data reduced connectivity, primarily between sensory-motor and visual areas. It also 22 produced networks with higher modularity, lower mean connectivity strength, and lower mean clustering 23 coefficient. Our results highlight new aspects of endogenous eye movement control during wakeful rest. 24 They show that oculomotor-related contributions form an important component of RS network topology, 25 and that those should be considered in interpreting differences in network structure between populations, 26 or as a function of different experimental conditions. 27 AUTHOR SUMMARY We studied how subtle eye movements made during fixation, in absence of any other task, are related to 28 resting-state connectivity measured using fMRI. We used a dataset for which eye-tracking and BOLD 29 resting-state were acquired simultaneously. We correlated brain activity with both eye-tracking metrics as 30 well as timeseries sampled from the area of the Eye Orbits (EO-EPI). Eye-tracking data correlated well 31 with the EO-EPI data. Furthermore, EO-EPI correlated with BOLD signal in sensory-motor and visual 32 brain systems. Removing variance related to EO-EPI reduced connectivity between sensory-motor and 33 visual areas and resulted in more modular resting-state networks. Our findings show that 34 oculomotor-related contributions are an important component of resting-state network topology, and that 35 they can be studied using EPI data from the eye orbits. 36 INTRODUCTION The study of human brain activity during resting state (RS) is of considerable interest in both basic and 37 clinical brain research. For mechanistically-oriented perspectives, RS activity patterns identify 38 constraints that may govern task-evoked activity as seen by relations between RS connectivity and 39 inter-individual differences in various cognitive tasks (e.g., Kelly, Uddin, Biswal, Castellanos, & Milham, 4