Abstract
Abstract Functional ultrasound (fUS) has received growing attention in preclinical research in the past decade, providing a new tool to measure functional connectivity (FC) and brain task-evoked responses with single-trial detection capability in both anesthetized and awake conditions. Most fUS studies rely on 2D linear arrays to acquire one slice of the brain. Volumetric fUS using 2D matrix or row-column arrays has recently been demonstrated in rats and mice but requires invasive craniotomy to expose the brain due to a lack of sensitivity. In a previous study, we proposed the use of motorized linear arrays, allowing imaging through the skull in mice for multiple slices with high sensitivity. However, the tradeoff between the field of view and temporal resolution introduced by motorized scanning prevents acquiring brain-wide resting-state FC data with a sufficient volume rate for resting-state FC analysis. Here, we propose a new hybrid solution optimized and dedicated to brain-wide transcranial FC studies in mice, based on a newly developed multi-array transducer allowing simultaneous multi-slicing of the entire mouse cerebrum. We first demonstrate that our approach provides a better imaging quality compared to other existing methods. Then, we show the ability to image the whole mouse brain non-invasively through the intact skin and skull during visual stimulation under light anesthesia to validate this new approach. Significant activation was detected along the whole visual pathway, at both single and group levels, with more than 10% of augmentation of the cerebral blood volume (CBV) signal during the visual stimulation compared to baseline. Finally, we assessed resting-state FC in awake head-fixed animals. Several robust and long-ranged FC patterns were identified in both cortical and sub-cortical brain areas, corresponding to functional networks already described in previous fMRI studies. Together, these results show that the multi-array probe is a valuable approach to measure brain-wide hemodynamic activity in mice with an intact skull. Most importantly, its ability to identify robust resting-state networks is paving the way towards a better understanding of the mouse brain functional organization and its breakdown in genetic models of neuropsychiatric diseases.
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