Network NeuroscienceNeurosciencePeer-reviewed journal article
Spontaneous eye-movements during eyes-open rest reduce resting-state-network modularity by increasing visual-sensorimotor connectivity
Cemal KobaiD, Giuseppe NotaroiD, Sandra TammiD, Gustav NilsonneiD, Uri HassoniD
Abstract
During wakeful rest, individuals make small eye movements when asked to fixate. We examined how these endogenously-driven oculomotor patterns impact topography and topology of functional brain networks. We used a dataset consisting of eyes-open resting-state (RS) fMRI data with simultaneous eye-tracking (Nilsonne et al., 2016). The eye-tracking data indicated minor movements during rest, on the order of 1.0 degree on average when analyzed over 2sec epochs, which correlated modestly with RS BOLD data. However, the eye-tracking data correlated well with echo-planar imaging (EPI) time series sampled from the area of the Eye-Orbit (EO-EPI), which is a signal previously used to identify eye movements during exogenous saccades and movie viewing. We found that EO-EPI data correlated with activity in an extensive motor and sensory-motor network, but also some components of the dorsal attention network including the frontal and supplementary eye fields. Partialling out variance related to EO-EPI from RS data reduced connectivity, primarily between sensory-motor and visual areas. For three different network sparsity levels, the resulting RS connectivity networks showed higher modularity, lower mean connectivity strength, and lower mean clustering coefficient. Our results highlight new aspects of endogenous eye movement control during wakeful rest. They show that oculomotor-related contributions form an important component of RS network topology, and that those should be considered in interpreting differences in network structure between populations, or as a function of different experimental conditions.
- organism: human
- assay: imaging
- research focus: spatial domain detection
- research focus: differential expression
- approach: statistical model
- approach: experimental assay
- Citations
- 14
- FWCI
- 1.31
- Field percentile
- top 23%
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