Controlling the familywise error rate in widefield optical neuroimaging of functional connectivity in mice

Intact-skull cranial windows for widefield optical imaging in juvenile mice: complications and consequences

Functional neuroimaging with widefield optical imaging (WOI) is potentially useful for studying developmental disorders in juvenile mice. However, WOI requires an intact-skull cranial window, and the effects of such windows on young mice are unknown. We performed intact-skull cranial window placement on mice as young as P7 to study the effects of chronic placement. Cranial windows placed at young ages (P7 and P10) were not longitudinally stable, resulting in significant attrition. Windows placed at ages P14 or less resulted in significant impairment to skull growth, which in turn caused artifacts in resting-state functional connectivity analysis. Longitudinal cranial windows should likely be avoided under P30.

Spatial nonstationarity of image noise in widefield optical imaging and its effects on cluster-based inference for resting-state functional connectivity

BACKGROUND

Resting-state functional connectivity (RSFC) analysis with widefield optical imaging (WOI) is a potentially powerful tool to develop imaging biomarkers in mouse models of disease before translating them to human neuroimaging with functional magnetic resonance imaging (fMRI). The delineation of such biomarkers depends on rigorous statistical analysis. However, statistical understanding of WOI data is limited. In particular, cluster-based analysis of neuroimaging data depends on assumptions of spatial stationarity (i.e., that the distribution of cluster sizes under the null is equal at all brain locations). Whether actual data deviate from this assumption has not previously been examined in WOI.

NEW METHOD

In this manuscript, we characterize the effects of spatial nonstationarity in WOI RSFC data and adapt a "two-pass" technique from fMRI to correct cluster sizes and mitigate spatial bias, both parametrically and nonparametrically. These methods are tested on multi-institutional data.

RESULTS AND COMPARISON WITH EXISTING METHODS

We find that spatial nonstationarity has a substantial effect on inference in WOI RSFC data with false positives much more likely at some brain regions than others. This pattern of bias varies between imaging systems, contrasts, and mouse ages, all of which could affect experimental reproducibility if not accounted for.

CONCLUSIONS

Both parametric and nonparametric corrections for nonstationarity result in significant improvements in spatial bias. The proposed methods are simple to implement and will improve the robustness of inference in optical neuroimaging data.