Objective
Measuring the electrical activity of neurons in vivo is of paramount importance to understand the underlying principles of the brain. Current imaging techniques fail to capture this activity across the entire brain with sufficient spatial or temporal resolutions, while leaving brain tissue intact. Non-linear fluorescence microscopy, the most widespread optical imaging modality in system neurobiology, provides optical diffraction limited resolution and high frame rate, but is limited to shallow depth due to light scattering in tissue. Single-neuron activity in brain regions deeper than one millimeter can therefore not be probed.
Combining widefield optical excitation and ultrasonic detection, photoacoustic imaging has emerged in the last decades as a powerful technique to image of optically contrasted objects embedded deep inside biological tissue. It relies on the emission of ultrasound waves upon the absorption of a light pulse. As ultrasound are only weakly scattered when propagating in soft tissue, optically absorbing structures can be reconstructed from the sole measurement of the ultrasound field at the tissue surface.
The highest spatial resolution is currently achieved using optical sensors of pressure waves, which exhibit a better sensitivity to high ultrasound frequencies compared to conventional piezoelectric detectors. However, single-cell resolution is still beyond the reach of such sensors, and the underlying sequential acquisition process prevent from imaging at sufficient frame rate.
To address this challenge, I will develop new sensors and associated interrogation techniques with 1) high acquisition speed and 2) high sensitivity at high acoustic frequencies, to resolve temporally and spatially the activity of single neurons. This will enable to 3) image non-invasively neuronal activity at unprecedented depth of several millimeters in vivo in the mouse brain.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- natural sciencesbiological sciencesneurobiology
- natural sciencesphysical sciencesopticsmicroscopy
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensors
- natural sciencesphysical sciencesacousticsultrasound
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Topic(s)
Funding Scheme
HORIZON-ERC - HORIZON ERC GrantsHost institution
75794 Paris
France