Webinar: Multimodal neuroimaging using functional ultrasound

Join us for a webinar on 7 February 2023, when we’ll be finding out how the latest neuroimaging methods can be coupled with fUS to study neurovascular coupling across vigilance states.

multimodal neuroimaging using functional ultrasound (fus) sm1

Functional ultrasound is showing great potential to understand brain function, and in this webinar we’ll find out how it can be partnered with other neuroimaging methods to study brain function.

Dr Davide Boido (NeuroSpin; CEA Paris) will begin the webinar by describing how fUS relates to BOLD fMRI and the link between a single voxel fUS signal and neuronal activation inside that voxel. This data provides information about the linearity of the neurovascular coupling, and its fast dynamics when assessed at high spatiotemporal resolution and with short sensory stimuli. He will also highlight novel research directions allowed by fUS neuroimaging and the limitations imposed by cerebral blood-flow regulation.

In the second part of the webinar, Dr Antoine Bergel (McGill University) will discuss how fUS can be combined with EEG and video for behavioral neuroscience studies in rodents. He will also address the current challenges that must be overcome to perform longitudinal studies (days to months). Using specific examples, he will demonstrate how combining the large field of view of fUS (depth imaging) with the temporal resolution of electrophysiology can help understand brain function.

Webinar details​

Title: Multimodal neuroimaging using functional ultrasound (fUS) Date: Tuesday 7 February 2023 Time:
  • 11:00 am ET (Eastern Time – North America)
  • 4:00 pm GMT (Greenwich Mean Time)
  • 5:00 pm CET (Central European Time)
Duration: 60 min

Key topics:

  • How fUS can be combined with other modalities, including fMRI, electrophysiology, two-photon microscopy and behavioral assays
  • Important considerations for longitudinal studies, including surgical preparation, signal processing and analysis pipelines
  • Examples of multimodal measurements acquired during sleep and running episodes.

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