Multi-scale mapping along the auditory hierarchy using high-resolution functional UltraSound in the awake ferret

A major challenge in neuroscience is to longitudinally monitor whole brain activity across multiple spatial scales in the same animal. Functional UltraSound (fUS) is an emerging technology that offers images of cerebral blood volume over large brain portions. Here we show for the first time its capability to resolve the functional organization of sensory systems at multiple scales in awake animals, both within small structures by precisely mapping and differentiating sensory responses, and between structures by elucidating the connectivity scheme of top-down projections. We demonstrate that fUS provides stable (over days), yet rapid, highly-resolved 3D tonotopic maps in the auditory pathway of awake ferrets, thus revealing its unprecedented functional resolution (100/300µm). This was performed in four different brain regions, including very small (1–2 mm3 size), deeply situated subcortical (8 mm deep) and previously undescribed structures in the ferret. Furthermore, we used fUS to map long-distance projections from frontal cortex, a key source of sensory response modulation, to auditory cortex

<i>In vivo</i> real-time cavitation imaging in moving organs

International audienceThe stochastic nature of cavitation implies visualization of the cavitation cloud in real-time and in a discriminative manner for the safe use of focused ultrasound therapy. This visualization is sometimes possible with standard echography, but it strongly depends on the quality of the scanner, and is hindered by difficulty in discriminating from highly reflecting tissue signals in different organs. A specific approach would then permit clear validation of the cavitation position and activity. Detecting signals from a specific source with high sensitivity is a major problem in ultrasound imaging. Based on plane or diverging wave sonications, ultrafast ultrasonic imaging dramatically increases temporal resolution, and the larger amount of acquired data permits increased sensitivity in Doppler imaging. Here, we investigate a spatiotemporal singular value decomposition of ultrafast radiofrequency data to discriminate bubble clouds from tissue based on their different spatiotemporal motion and echogenicity during histotripsy. We introduce an automation to determine the parameters of this filtering. This method clearly outperforms standard temporal filtering techniques with a bubble to tissue contrast of at least 20 dB in vitro in a moving phantom and in vivo in porcine liver

Combined genetic, genomic and physiological approaches to characterize flowering in Fragaria

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A simple novel approach for detecting blood–brain barrier permeability using GPCR internalization

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