The rapid progress of modern neurosciences strongly relies on technological breakthroughs, both for stimulation, where a large effort is driven towards the production of complex (natural-like) sensory environments, and for neural recordings, where the main challenge is to obtain long-term measurements of the activity of a significant fraction of the neurons with single-cell resolution on intact animals. We aim at developing experimental tools to address both issues on a specific animal model, namely zebrafish larvae, and also, recently, Danionella translucida.

 Zebrafish, which was originally developed as a model for embryo development, has recently emerged as a similarly important animal model for neurosciences. Zebrafish larvae exhibit stereotyped behavioral responses to various stimuli associated with several sensory modalities (e.g. visual, hydromechanical, auditive, gustatory, olfactory). However, most of the current researches focus on the visual system alone, owing to the lack of experimental protocols to deliver well-controlled stimuli to other modalities. In particular, very few data are currently available on the functioning and neural processing associated with the lateral line – the organ that mediates flow perception in fish and amphibians. We take advantage of the rapid development of microfluidic technologies to design devices that will allow for the precise delivering of complex spatio-temporal flow patterns onto the lateral line of a partially tethered zebrafish larva. Stimulation patterns can range from very localized stimuli to complex flows spanning a large portion of the animal's body and mimicking natural stimuli.

On the observation side, the rapid development of calcium imaging during the last two decades – tightly related to the progress of genetics – has led to remarkable improvements on the number of neurons whose activity can be simultaneously monitored. However, most current imaging setups (confocal and two-photon) exhibit intrinsic limitations – essentially related to their point-scanning nature – which impose a severe trade-off between the number of accessible neurons and the acquisition rate. Recently, Single-Plane Illumination Microscopy (SPIM) approaches, in which the optical sectioning is obtained through side-on illumination of the specimen by a thin laser-sheet, yielded spectacular progress for structural imaging during the first developmental stages of zebrafish larvae. We are adaptating this technique to 3D functional imaging of GCaMP transgenic larvae in order to reach simultaneous recordings at standard acquisition rates of an unprecedented amount of neurons. Here is a picture of a larva's brain obtained with SPIM:

Figure 1 : Brain slice of a live and intact 6 d.p.f.GCaMP3 larva obtained by SPIM. Kernels appear in dark while somata are brighter. The image contains more than 5000 neurons.

Recordings the activity of a large fraction of the brain opens the way to new approaches in understanding how perceptive information is processed. In particular, large datasets allow for the search of brain-wide patterns via statistical correlations.

In the news

• "Observer en direct le fonctionnement du cerveau d’une larve de poisson-zèbre intacte" (French - Actualié de l'INP du CNRS, April 24, 2013)
• "Lumière sur les neurones" (French - Le Monde Science & techno, April 20, 2013)

PhD students (defense 2018->)

• Geoffrey Migault (2020)
• Sophia Karpenko (2020)
• Hugo Trentesaux (2020)
• Guillaume Le Goc (2021)
• Benjamin Gallois (2021)
• Julie Lafaye (2022)
• Natalia Beiza Canelo (2022)
  
• Hippolyte Moule (2023)
• Sharbatanu Chatterjee (2024)
• Matteo Dommanget Kott (2024)
• Leonardo Demarchi (2024)
• Monica Coraggioso (2024)

Post-docs (since 2018)

• Kristen Severie (2020)
• Thomas Panier (2016 - 2018)
• Thomas Pujol (2020)
• Marcus Ghosh (2021 - 2023)
• Antoine Hubert (2021 - present)

Master students (since 2018)

Master 1:

• 2018 Loann Collet
• 2018 Sahar Aghakhani
• 2019 Pierre Tapie  
• 2020 Muntasir Callachand  
• 2020 Emile Boré
• 2023 Elias Benyahia  

Master 2:

• 2018 Julie Lafaye 
• 2019 Patrik Turzak
• 2020 Matteo Dommaget-Kott
• 2020 Alexandre Nauleau

Programmes open-source

• SPIM Image processing