Publications by authors named "Antoine Bergel"

Functional Ultrasound (fUS) provides spatial and temporal frames of the vascular activity in the brain with high resolution and sensitivity in behaving animals. The large amount of resulting data is underused at present due to the lack of appropriate tools to visualize and interpret such signals. Here we show that neural networks can be trained to leverage the richness of information available in fUS datasets to reliably determine behavior, even from a single fUS 2D image after appropriate training.

View Article and Find Full Text PDF

Rapid-eye-movement sleep (REMS) or paradoxical sleep is associated with intense neuronal activity, fluctuations in autonomic control, body paralysis and brain-wide hyperemia. The mechanisms and functions of these energy-demanding patterns remain elusive and a global picture of brain activation during REMS is currently missing. In the present work, we performed functional ultrasound imaging on rats over multiple coronal and sagittal brain sections during hundreds of spontaneous REMS episodes to provide the spatiotemporal dynamics of vascular activity in 259 brain regions spanning more than 2/3 of the total brain volume.

View Article and Find Full Text PDF

During locomotion, theta and gamma rhythms are essential to ensure timely communication between brain structures. However, their metabolic cost and contribution to neuroimaging signals remain elusive. To finely characterize neurovascular interactions during locomotion, we simultaneously recorded mesoscale brain hemodynamics using functional ultrasound (fUS) and local field potentials (LFP) in numerous brain structures of freely-running overtrained rats.

View Article and Find Full Text PDF

Rapid eye movement sleep (REMS) is a peculiar brain state combining the behavioral components of sleep and the electrophysiological profiles of wake. After decades of research our understanding of REMS still is precluded by the difficulty to observe its spontaneous dynamics and the lack of multimodal recording approaches to build comprehensive datasets. We used functional ultrasound (fUS) imaging concurrently with extracellular recordings of local field potentials (LFP) to reveal brain-wide spatiotemporal hemodynamics of single REMS episodes.

View Article and Find Full Text PDF

4D ultrasound microvascular imaging was demonstrated by applying ultrafast Doppler tomography (UFD-T) to the imaging of brain hemodynamics in rodents. In vivo real-time imaging of the rat brain was performed using ultrasonic plane wave transmissions at very high frame rates (18,000 frames per second). Such ultrafast frame rates allow for highly sensitive and wide-field-of-view 2D Doppler imaging of blood vessels far beyond conventional ultrasonography.

View Article and Find Full Text PDF

Ultrafast imaging using plane or diverging waves has recently enabled new ultrasound imaging modes with improved sensitivity and very high frame rates. Some of these new imaging modalities include shear wave elastography, ultrafast Doppler, ultrafast contrast-enhanced imaging and functional ultrasound imaging. Even though ultrafast imaging already encounters clinical success, increasing even more its penetration depth and signal-to-noise ratio for dedicated applications would be valuable.

View Article and Find Full Text PDF

We developed an integrated experimental framework that extends the brain exploration capabilities of functional ultrasound imaging to awake and mobile rats. In addition to acquiring hemodynamic data, this method further allows parallel access to electroencephalography (EEG) recordings of neuronal activity. We illustrate this approach with two proofs of concept: a behavioral study on theta rhythm activation in a maze running task and a disease-related study on spontaneous epileptic seizures.

View Article and Find Full Text PDF
Article Synopsis
  • Ultrafast ultrasonic imaging is a new technique that improves ultrasound data collection by using unfocused waves, which enhances the ability to differentiate between tissue and blood motion in Doppler imaging.* -
  • The proposed method uses spatiotemporal singular value decomposition (SVD) to reject noise in the ultrasound data, providing a more effective approach than traditional filters by analyzing multiple dimensions of data.* -
  • Tests showed that SVD filtering significantly improves blood flow detection, revealing previously unnoticed flows in various applications, including small animal brain imaging and clinical cases like neonate and organ Doppler imaging.*
View Article and Find Full Text PDF