Mapping intrinsic functional connectivity using large-scale voltage-sensitive dye imaging in anesthetized mice

Abstract

Despite of the enthusiasm towards intrinsic functional connectivity observed in the brain at rest, currently available approaches to study iFC are limited due to a number of technical limitations. First, the brain imaging modalities such as fMRI, EEG and MEG have either poor temporal resolution or spatial resolution, limiting the way of analysis. This has lead fMRI studies to focus on the spatial patterns of activations at rest, whereas EEG and MEG studies exploited the temporal information embedded in signals within diverse frequency ranges. This is partly due to volume conduction, which makes it harder to study the spatial patterns in EEG and MEG. Second, it is hard to couple these modalities in animal models that allow powerful genetic and molecular approaches, along with diverse invasive experimental methods. To overcome these limitations, large-scale voltage-sensitive dye imaging has been performed in mice cortex, revealing the spatiotemporal details of the neuronal activities that were unable to observe in other modalities. However, previous studies relied on visual inspection and counting to analyze the dynamics of the activities. In this study, I performed large-scale voltage-sensitive dye imaging in urethane anesthetized mice that offer functional signals with high spatiotemporal resolution, but without volume conduction effect. I then applied network analysis such as spatial independent component analysis that was able to couple the spatial information and temporal information of the functional networks within diverse frequency ranges, describing the activity level changes at network level. This enabled me to investigate the dynamics of intrinsic functional connectivity with superior spatiotemporal resolution while maximizing the amount of information under analysis. I propose that this approach can bridge the gap between human and animal studies as well as providing a useful platform to investigate the brain dynamics. This platform could also be use...